1) The document presents upper and lower bounds on the capacity of MIMO relay channels, which are wireless channels with multiple antennas at the source, relay, and destination nodes.
2) For fixed channel conditions, an upper bound is derived involving maximization over covariance matrices and a scalar parameter capturing signal cooperation. A lower bound is found as the maximum of the direct link and cascaded link capacities.
3) The analysis is extended to Rayleigh fading channels, where the ergodic (average) capacity is considered. It is shown that under certain conditions, the upper and lower bounds meet, characterizing the exact ergodic capacity.
EFFICIENT ANALYSIS OF THE ERGODIC CAPACITY OF COOPERATIVE NON-REGENERATIVE RE...ijwmn
In this paper, we proposed a novel efficient method of analyzing the ergodic channel capacity of the
cooperative amplify-and-forward (CAF) relay system. This is accomplished by employing a very tight
approximate moment generating function (MGF) of end-to-end signal-to-noise ratio of 2-hop multi-relay
system, which is In this paper, we proposed a novel efficient method of analyzing the ergodic channel
capacity of the cooperative amplify-and-forward (CAF) relay system. This is accomplished by employing a
very tight approximate moment applicable to myriad of fading environments including mixed and
composite fading channels. Three distinct adaptive source transmission policies were considered in our
analysis namely: (i) constant power with optimal rate adaptation (ORA); (ii) optimal joint power and rate
adaptation (OPRA); and (iii) fixed rate with truncated channel inversion (TCIFR). The proposed frame
work based on the novel approximate MGF method is sufficiently general to encapsulate all types of fading
environments (especially for the analysis of the mixed fading case)and provides significant advantage to
model wireless system for mixed and composite fading channel. In addition to simplifying computation
complexity of ergodic capacity for CAF relaying schemes treated in literature, we also derive closed form
expressions for the above three adaptive source transmission policies under Nakagami-m fading with i.n.d
statistics. The accuracy of our proposed method has been validated with existing MGF expressions that are
readily available for specific fading environments in terms of bounds, and via Monte Carlo simulations.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Performance Analysis of Enhanced Opportunistic Minimum Cost Routingin Mobile ...IJERA Editor
Mobile Ad-Hoc Network (MANET) is a collection of wireless mobile nodes forming a temporary network with
infrastructure less environment to establish a data transmission between nodes within the network. A routing
protocol is used to discover routes between nodes. In this paper, we study the three existing routing protocols
namely AODV, DSDV and DSR to analyze theirperformance based on set of parameters.AODV and DSR
deliver almost all the packets compared to DSDV. Hence we try to modify the AODVprotocol and use in the
cooperative transmission.
In this paper, we study the cooperative transmission at the network layer and cooperative diversity at the
physical layer as a joint optimization of the transmission power in a Mobile Ad-Hoc Network (MANET) with
static channel. However due to variable wireless channels static routing is suboptimal. Proposed protocol
proactively selects forwarding nodes that work cooperatively forwarding the packet towards the destination.
Cooperative transmission side diversity helps in reducing interference. Diversity can be achieved at the physical
layer by coordinating the multiple nodes. Nodes are equipped with Omni-directional antenna and take the
advantages of transmission side diversity to achieve energy saving, under the assumption that channel gains are
available at the transmitters.
The proposed Opportunistic Minimum Cost Cooperative Transmission Shortest Path (OMCTSP) algorithms
select the best optimum route with minimum cost in terms of energy, number of hops, available bandwidth, link
quality (SNR) and outage probability. As the network becomes larger, finding optimal routes becomes
computationally intractable as the complexity of the dynamic programming (DP) approach increases as o (22n)
where n is the number of nodes in the networks. Hence we develop two suboptimal algorithms have complexity
of o (n2) perform as same as optimal algorithm. Also developthe Opportunistic Cooperative Routing in MANET
(O_CORMAN), which is a network layer opportunistic routing scheme for mobile ad hoc networks. Nodes in
the network use the components proactive routing protocol, forwarder list update and local re-transmission. We
evaluate the performance using NS 2.32 simulator there is significant performance improvement with respect to
energy, throughput packet delivery, and delay compared with Modified AODV (OMCTSP).
INVESTIGATING MULTILAYER OMEGA-TYPE NETWORKS OPERATING WITH THE CUT-THROUGH T...IJCNCJournal
The continuous increase in the complexity of data networks has motivated the development of more effective Multistage Interconnection Networks (MINs) as important factors in providing higher data transfer rates in various switching divisions. In this paper, semi-layer omega-class networks operating with a cut-through forwarding technique are chosen as test-bed subjects for detailed evaluation, and this network architecture is modelled, inspected, and simulated. The results are examined for relevant singlelayer omega networks operating with cut-through or ‘store and forward’ forwarding techniques. Two series of experiments are carried out: one concerns the case of uniform traffic, while the other is related to hotspot traffic. The results quantify the way in which this network outperforms the corresponding singlelayer network architectures for the same network size and buffer size. Furthermore, the effects of the dimensions of the switch elements and their corresponding reliability on the overall interconnection system are investigated, and the complexity and the relevant cost are examined. The data yielded by this investigation can be valuable to MIN engineers and can allow them to achieve more productive networks with lower overall implementation costs.
ROUTING IN OPTICAL MESH NETWORKS-A QOS PERSPECTIVEijasuc
Wireless Ad-Hoc Mesh Networks are characterized by static nodes connected in a mesh topology. A routing
protocol discovers and maintains the route for successful transmission of data in a network. The routing
protocol should also provide load balancing and fault tolerance for improved network performance. In
Free Space Optical networks (FSO) line of sight (LOS) should be maintained between the two
communicating nodes. In a multihop scenario maintaining LOS during routing is a challenge. In this paper
we propose a routing protocol Quality of Service-Directional Routing Protocol (QDRP) - which assures a
certain level of performance to a data flow in terms of delay and implemented on FSO MANET. Through
simulations it is observed that QDRP chooses the path with the least delay and performs satisfactorily
under varying node densities and transmission rates achieving end to end delay of .14 s and packet delivery
percentage of 96% when simulated for an area of 1300 m *1300 m for 100 nodes. This work explores the
potential of the proposed routing protocol for free space optical mesh networks. QDRP is compared with
ORRP (Orthogonal Rendezvous Routing Protocol) and AODV (Ad-Hoc on Demand Distance Vector), a
reactive protocol which is also implemented in free space optical environment. We support our conclusions
that QDRP gains in terms of packet delivery percentage, end to end delay and goodput.
QOS ROUTING AND PERFORMANCE EVALUATION FOR MOBILE AD HOC NETWORKS USING OLSR ...ijasuc
Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure.
As the real-time applications used in today’s wireless network grow, we need some schemes to provide
more suitable service for them. We know that most of actual schemes do not perform well on traffic which
is not strictly CBR. Therefore, in this paper we have studied the impact, respectively, of mobility models
and the density of nodes on the performances (End-to-End Delay, Throughput and Packet Delivery ratio)
of routing protocol (Optimized Link State Routing) OLSR by using in the first a real-time VBR (MPEG-4)
and secondly the Constant Bit Rate (CBR) traffic. Finally we compare the performance on both cases.
Experimentally, we considered the three mobility models as follows Random Waypoint, Random
Direction and Mobgen Steady State. The experimental results illustrate that the behavior of OLSR change
according to the model and the used traffics.
EFFICIENT ANALYSIS OF THE ERGODIC CAPACITY OF COOPERATIVE NON-REGENERATIVE RE...ijwmn
In this paper, we proposed a novel efficient method of analyzing the ergodic channel capacity of the
cooperative amplify-and-forward (CAF) relay system. This is accomplished by employing a very tight
approximate moment generating function (MGF) of end-to-end signal-to-noise ratio of 2-hop multi-relay
system, which is In this paper, we proposed a novel efficient method of analyzing the ergodic channel
capacity of the cooperative amplify-and-forward (CAF) relay system. This is accomplished by employing a
very tight approximate moment applicable to myriad of fading environments including mixed and
composite fading channels. Three distinct adaptive source transmission policies were considered in our
analysis namely: (i) constant power with optimal rate adaptation (ORA); (ii) optimal joint power and rate
adaptation (OPRA); and (iii) fixed rate with truncated channel inversion (TCIFR). The proposed frame
work based on the novel approximate MGF method is sufficiently general to encapsulate all types of fading
environments (especially for the analysis of the mixed fading case)and provides significant advantage to
model wireless system for mixed and composite fading channel. In addition to simplifying computation
complexity of ergodic capacity for CAF relaying schemes treated in literature, we also derive closed form
expressions for the above three adaptive source transmission policies under Nakagami-m fading with i.n.d
statistics. The accuracy of our proposed method has been validated with existing MGF expressions that are
readily available for specific fading environments in terms of bounds, and via Monte Carlo simulations.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Performance Analysis of Enhanced Opportunistic Minimum Cost Routingin Mobile ...IJERA Editor
Mobile Ad-Hoc Network (MANET) is a collection of wireless mobile nodes forming a temporary network with
infrastructure less environment to establish a data transmission between nodes within the network. A routing
protocol is used to discover routes between nodes. In this paper, we study the three existing routing protocols
namely AODV, DSDV and DSR to analyze theirperformance based on set of parameters.AODV and DSR
deliver almost all the packets compared to DSDV. Hence we try to modify the AODVprotocol and use in the
cooperative transmission.
In this paper, we study the cooperative transmission at the network layer and cooperative diversity at the
physical layer as a joint optimization of the transmission power in a Mobile Ad-Hoc Network (MANET) with
static channel. However due to variable wireless channels static routing is suboptimal. Proposed protocol
proactively selects forwarding nodes that work cooperatively forwarding the packet towards the destination.
Cooperative transmission side diversity helps in reducing interference. Diversity can be achieved at the physical
layer by coordinating the multiple nodes. Nodes are equipped with Omni-directional antenna and take the
advantages of transmission side diversity to achieve energy saving, under the assumption that channel gains are
available at the transmitters.
The proposed Opportunistic Minimum Cost Cooperative Transmission Shortest Path (OMCTSP) algorithms
select the best optimum route with minimum cost in terms of energy, number of hops, available bandwidth, link
quality (SNR) and outage probability. As the network becomes larger, finding optimal routes becomes
computationally intractable as the complexity of the dynamic programming (DP) approach increases as o (22n)
where n is the number of nodes in the networks. Hence we develop two suboptimal algorithms have complexity
of o (n2) perform as same as optimal algorithm. Also developthe Opportunistic Cooperative Routing in MANET
(O_CORMAN), which is a network layer opportunistic routing scheme for mobile ad hoc networks. Nodes in
the network use the components proactive routing protocol, forwarder list update and local re-transmission. We
evaluate the performance using NS 2.32 simulator there is significant performance improvement with respect to
energy, throughput packet delivery, and delay compared with Modified AODV (OMCTSP).
INVESTIGATING MULTILAYER OMEGA-TYPE NETWORKS OPERATING WITH THE CUT-THROUGH T...IJCNCJournal
The continuous increase in the complexity of data networks has motivated the development of more effective Multistage Interconnection Networks (MINs) as important factors in providing higher data transfer rates in various switching divisions. In this paper, semi-layer omega-class networks operating with a cut-through forwarding technique are chosen as test-bed subjects for detailed evaluation, and this network architecture is modelled, inspected, and simulated. The results are examined for relevant singlelayer omega networks operating with cut-through or ‘store and forward’ forwarding techniques. Two series of experiments are carried out: one concerns the case of uniform traffic, while the other is related to hotspot traffic. The results quantify the way in which this network outperforms the corresponding singlelayer network architectures for the same network size and buffer size. Furthermore, the effects of the dimensions of the switch elements and their corresponding reliability on the overall interconnection system are investigated, and the complexity and the relevant cost are examined. The data yielded by this investigation can be valuable to MIN engineers and can allow them to achieve more productive networks with lower overall implementation costs.
ROUTING IN OPTICAL MESH NETWORKS-A QOS PERSPECTIVEijasuc
Wireless Ad-Hoc Mesh Networks are characterized by static nodes connected in a mesh topology. A routing
protocol discovers and maintains the route for successful transmission of data in a network. The routing
protocol should also provide load balancing and fault tolerance for improved network performance. In
Free Space Optical networks (FSO) line of sight (LOS) should be maintained between the two
communicating nodes. In a multihop scenario maintaining LOS during routing is a challenge. In this paper
we propose a routing protocol Quality of Service-Directional Routing Protocol (QDRP) - which assures a
certain level of performance to a data flow in terms of delay and implemented on FSO MANET. Through
simulations it is observed that QDRP chooses the path with the least delay and performs satisfactorily
under varying node densities and transmission rates achieving end to end delay of .14 s and packet delivery
percentage of 96% when simulated for an area of 1300 m *1300 m for 100 nodes. This work explores the
potential of the proposed routing protocol for free space optical mesh networks. QDRP is compared with
ORRP (Orthogonal Rendezvous Routing Protocol) and AODV (Ad-Hoc on Demand Distance Vector), a
reactive protocol which is also implemented in free space optical environment. We support our conclusions
that QDRP gains in terms of packet delivery percentage, end to end delay and goodput.
QOS ROUTING AND PERFORMANCE EVALUATION FOR MOBILE AD HOC NETWORKS USING OLSR ...ijasuc
Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure.
As the real-time applications used in today’s wireless network grow, we need some schemes to provide
more suitable service for them. We know that most of actual schemes do not perform well on traffic which
is not strictly CBR. Therefore, in this paper we have studied the impact, respectively, of mobility models
and the density of nodes on the performances (End-to-End Delay, Throughput and Packet Delivery ratio)
of routing protocol (Optimized Link State Routing) OLSR by using in the first a real-time VBR (MPEG-4)
and secondly the Constant Bit Rate (CBR) traffic. Finally we compare the performance on both cases.
Experimentally, we considered the three mobility models as follows Random Waypoint, Random
Direction and Mobgen Steady State. The experimental results illustrate that the behavior of OLSR change
according to the model and the used traffics.
JOINT-DESIGN OF LINK-ADAPTIVE MODULATION AND CODING WITH ADAPTIVE ARQ FOR COO...IJCNCJournal
This paper analyzes the efficiency of a joint-design of an adaptive modulation and coding (AMC) at the
physical (PHY) layer with an adaptive Rmax-truncated selective-repeat automatic repeat request (ARQ)
protocol at the medium access control (MAC) layer to maximize the throughput of cooperative nonregenerative
relay networks under prescribed delay and/or error performance constraints. Particularly, we
generalize the existing design model/results for cross-layer combining of AMC along with truncated ARQ
in non-cooperative diversity networks in three-folds: (i) extension of the cross-layer PHY/MAC design or
optimization to cooperative diversity systems; (ii) generalization/unification of analytical expressions for
various network performance metrics to generalized block fading channels with independent but nonidentically
distributed (i.n.d) fading statistics among the spatially distributed nodes; (iii) analysis of the
effectiveness of joint-adaptation of the maximum retransmission limit Rmax of ARQ protocol and
cooperative diversity order N for delay-insensitive applications. Our insightful numerical results reveal
that the average throughput can be increased significantly by judiciously combining two additional degrees
of freedom (N and Rmax) that are available in cooperative amplify-and-forward (CAF) relay networks
besides employing AMC at the PHY layer, especially in the most challenging low signal-to-noise ratio
(SNR) regime.
Routing in Cognitive Radio Networks - A SurveyIJERA Editor
Cognitive Radio Networks (CRNs) have been emerged as a revolutionary solution to migrate the spectrum
scarcity problem in wireless networks. Due to increasing demand for additional spectrum resources, CRNs have
been receiving significant research to solve issues related with spectrum underutilization. This technology
brings efficient spectrum usage and effective interference avoidance, and also brings new challenges to routing
in multi-hop Cognitive Radio Networks. In CRN, unlicensed users or secondary users are able to use
underutilized licensed channels, but they have to leave the channel if any interference is caused to the primary or
licensed users. So CR technology allows sharing of licensed spectrum band in opportunistic and non-interfering
manner. Different routing protocols have been proposed recently based on different design goals under different
assumptions.
A new clustering technique based on replication for MANET routing protocolsTELKOMNIKA JOURNAL
The cluster head nodes in most mobile ad hoc networks (MANET) clustering protocols take on an extraordinary role in managing routing information. The reliability, efficiency and scalability of the clustering in MANET will ultimately be dramatically impacted. In this work we establish a new approach to form the clusters in MANET called the square cluster-based routing protocol (SCBRP). That protocol is based on the theory of replication. The goal of the protocol is to achieve reliability, availability and scalability with in the MANET. The proposed protocol is evaluated by caring the performance analysis using the NS-3 simulator. The performance shows 50% improvementin data delivering ratio in large network size, also shows an improvement in network stability and availability which is reflected in energy consumption measurements and increase in the system lifetime to 20%.
Design and analysis of routing protocol for cognitive radio ad hoc networks i...IJECEIAES
Multi-hop routing protocol in cognitive radio mobile ad hoc networks (CRMANETs) is a critical issue. Furthermore, the routing metric used in multi-hop CRMANETs should reflect the bands availability, the links quality, the PU activities and quality of service (QoS) requirements of SUs. For the best of our knowledge, many of researchers investigated the performance of the different routing protocols in a homogeneous environment only. In this paper, we propose a heterogeneous cognitive radio routing protocol (HCR) operates in heterogeneous environment (i.e. the route from source to destination utilize the licensed and unlicensed spectrum bands). The proposed routing protocol is carefully developed to make a tradeoff between the channel diversity of the routing path along with the CRMANETs throughput. Using simulations, we discuss the performance of the proposed HCR routing protocol and compare it with the AODV routing protocol using a discrete-event simulation which we developed using JAVA platform.
To increase the network capacity, there is
need to minimize the interference among nodes and
optimum control of topology in the foundation of
network. Recently, technological development helps to
build of mobile ad-hoc networks (MANETs) in order to
improve the quality of service (QoS) in terms of delay. In
contradictory to the objective of minimizing interference,
it is important to concern topology control in delay
constrained environment. The present research work
attempts to control the delay-constrained topology with
jointly considering delay and interference concept.
Additionally, the study proposed an interference oriented
topology control algorithm for delay-constrained
MANETs by taking account of both the interference
constraint and the delay constraint under the specific
condition of transmission delay, contention delay and the
queuing delay. Further, the study investigated the impact
of node mobility on the interference oriented topology
control algorithm. Finally, the results of the present
study shows that the proposed algorithm controls the
topology to convince the interference constraint, and
increases the transmit range to congregate the delay
requirement. Also, the study conclude that the algorithm
could effectively reduce the delay protocol and improve
the performance effectively in delay-constrained mobile
ad hoc networks.
Thus the article offers the model represented by algebraic equations and inequalities for routing and
policing traffic in infocommunication network. The novelty of the model is as follows: multiflow nature of
modern ICN is taken into account (1), i.е. a set of flows circling between different pairs of network routers are
considered simultaneously; coherent formalization of processes of traffic routing and policing within the model
that has lower dimensionality in comparison to known earlier is provided; the choice of optimality criterion, use
of which allows to implement multipath routing with consequent inclusion of paths as well as to organize
limitation of flow intensity on all the used routs simultaneously depending on their characteristics and flow
priority. According to the results of the analysis conducted we offer recommendations for choosing relation in
numerical values of routing metrics and service denial regarding the provision of the given values for the main
QoS characteristics, e.g. average packet delay. The model can be used as a basis for perspective protocol
decisions aimed at coherence of solutions for the tasks of traffic routing and policing. Further development of
the given model is possible under full account of stochastic characteristics of packet flows circling in the
network.
Performance of cluster-based cognitive multihop networks under joint impact o...TELKOMNIKA JOURNAL
In this paper, we evaluate outage probability (OP) of a cluster-based multi-hop protocol operating
on an underlay cognitive radio (CR) mode. The primary network consists of multiple independent
transmit/receive pairs, and the primary transmitters seriously cause co-channel interference (CCI) to the
secondary receivers. To improve the outage performance for the secondary network under the joint impact
of the CCI and hardware imperfection, we employ the best relay selection at each hop. Moreover, the
destination is equipped with multiple antennas and uses the selection combining (SC) technique to
enhance the reliability of the data transmission at the last hop. For performance evaluation, we first derive
an exact formula of OP for the primary network which is used to calculate the transmit power of the
secondary transmitters. Next, an exact closed-form expression of the end-to-end OP for the secondary
network is derived over Rayleigh fading channels. We then perform Monte-Carlo simulations to validate
the derivations. The results present that the CCI caused by the primary operations significantly impacts on
the outage performance of the secondary network.
PERFORMANCE IMPROVEMENT OF NONREGENERATIVE COOPERATIVE RELAY NETWORKS WITH OP...ijwmn
This paper analyzes the performance of Channel Side Information (CSI)-assisted cooperative amplify-andforward
(CAF) relay networks that employ both the node placement (i.e., relay position) based optimal
power allocation policy among collaborating nodes and adaptive M-ary quadrature amplitude modulation
(M-QAM)/ M-ary phase shift keying (M-PSK) techniques in generalized wireless fading environments. In
particular, we advocate a simple yet unified numerical approach based on the marginal moment generating
function (MGF) of the total received Signal to Noise Ratio (SNR) to derive analytical expressions for the
average bit error rate (ABER), mean achievable spectral efficiency, and outage probability performance
metrics. The proposed analytical framework is sufficiently general and flexible to characterize the
performance of adaptive-link CAF relay networks over a wide range of fading distributions (i.e., not
restricted to Rayleigh fading or independent identically distributed (i.i.d) Nakagami-m fading ) with
independent but non-identically distributed (i.n.d) fading statistics across the spatially distributed diversity
paths. Additionally, we further simplify the computational complexity, by employing the use of an
“approximate MGF expression” to compute the system performance metrics over the generalized fading
channel. Employing the above novel approach based on “approximate MGF” in conjunction derived
analytical frameworks allows us to simplify the computation complexity of achievable spectral efficiency as
well as ABER of CAF relay system in the generalized fading environments by simply replacing appropriate
single channel MGF which is readily available
PERFORMANCE OF OLSR MANET ADOPTING CROSS-LAYER APPROACH UNDER CBR AND VBR TRA...IJCNCJournal
The routing protocols play an important role in Mobile Ad-Hoc Network (MANET) because of the dynamically change of its topology. Optimized Link State Routing (OLSR), unawareness of Quality of Service (QoS) and power-consumed protocol, is an example of a widely-used routing protocol in MANET.
The Multi-Point Relays (MPR) selection algorithm is very crucial in OLSR. Therefore, firstly, we propose a heuristic method to select the best path based on two parameters; Bit Error Rate (BER) derived from the physical layer and Weighted Connectivity Index (CI) adopted from the network layer. This can be done via the cross-layer design scheme. This is anticipated to enhance the performance of OLSR, provide QoS
guarantee and improve the power consumption. The performances of the proposed scheme are investigated
by simulation of two types of traffics: CBR and VBR (MPEG-4), evaluated by metrics namely Throughput, Packet Delivery Ratio (PDR), Average End-to-End Delay, Control Overhead and Average Total Power Consumption.We compare our results with the typical OLSR and OLSR using only Weighted CI. It is
obvious that our proposed scheme provides superior performances to the typical OLSR and OLSR using only Weighted CI, especially, at high traffic load.
A MANET is an autonomous collection of mobile users that communicate over relatively bandwidth constrained wireless links. When designing mobile ad hoc networks, several interesting and difficult problems arise because of the shared nature of the wireless medium, limited transmission power (range) of wireless devices, node mobility, and battery limitations. This paper aims at providing a new schema to improve Dynamic Source Routing (DSR) Protocol. The aim
behind the proposed enhancement is to find the best route in acceptable time limit without having broadcast storm. Moreover, O-DSR enables network not only to overcome congestion but also maximize the lifetime of mobile nodes. Some simulations results show that the Route Request (RREQ) and the Control Packet Overhead decrease by 15% when O-DSR is used, consequently. Also the global energy consumption in O-DSR is lower until to 60 % , which leads to a long lifetime of the network.
IMPLEMENTATION AND COMPARISION OF DATA LINK QUALITY SCHEME ON ODMRP AND ADMR ...ijngnjournal
An ad hoc network is a collection of wireless mobile nodes dynamically forming a temporary network without the use of any fixed network infrastructure or centralized administration. In order to enable communication within the network, a routing protocol is needed to discover routes between nodes. The primary goal of ad hoc network routing protocols is to establish routes between node pairs so that messages may be delivered reliably and in a timely manner. The objective of any routing protocol is to have packet delivered with least possible cost in terms of receiving power, transmission power, battery energy consumption and distance. All these factors basically effect the establishment of link between the mobile nodes and liability and stability of these links. In this paper, we implement a data link quality scheme on two protocols ODMRP and ADMR and compare them on the bases link quality and link stability.
Mobile ad hoc network is a reconfigurable network of mobile nodes connected by multi-hop wireless links and capable of operating without any fixed infrastructure support. In order to facilitate communication within such self-creating, self-organizing and self administrating network, a dynamic routing protocol is needed. The primary goal of such an ad hoc network routing protocol is to discover and establish a correct and efficient route between a pair of nodes so that messages may be delivered in a timely manner. Route construction should be done with a minimum of overhead and bandwidth consumption. This paper examines two routing protocols, both on-demand source routing, for mobile ad hoc networks– the Dynamic Source Routing (DSR), an flat architecture based and the Cluster Based Routing Protocol (CBRP), a cluster architecture based and evaluates both routing protocols in terms of packet delivery fraction, normalized routing load, average end to end delay, throughput by varying number of nodes per sq. km, traffic sources and mobility. Simulation results show that in high
mobility (pause time 0s) scenarios, CBRP outperforms DSR. CBRP scales well with increasing number of nodes.
Modified q aware scheduling algorithm for improved fairness in 802.16 j networksIJCNCJournal
Deployment of Multi-hop Relays in WiMax based Cellu
lar Networks is considered as a cost effective
solution to increase the Coverage area of Base Stat
ion and also to improve the Network Capacity with h
igh
quality short links. Scheduling became a challengin
g task in these Multi-hop Relay Wireless Cellular
Networks of IEEE 802.16j standard. H. Chen, X. Xie
and H. Wu proposed a Q-aware Scheduling
Algorithm in which back-pressure flow control mecha
nism is used to reflect current Q size of the Relay
s
and considered high back-pressure links to include
in Concurrent Transmission Scenarios, to maximize t
he
throughput. This focus on high back-pressure links,
leads to starvation of Mobile Stations having low
back-
pressure links, resulting unfairness in some cases.
To remedy this situation, a Fair Link Inclusion (F
LI)
mechanism is applied in Greedy Algorithm of Q-aware
Scheduling Algorithm. Simulation results show that
Modified Q-aware Scheduling Algorithm with FLI mech
anism has reasonable improvement in fairness and
maintaining steady throughput when compared with ex
isting algorithms.
AN EFFECTIVE CONTROL OF HELLO PROCESS FOR ROUTING PROTOCOL IN MANETSIJCNCJournal
In the mobile ad hoc network (MANET) update of link connectivity is necessary to refresh the neighbor tables in data transfer. A existing hello process periodically exchanges the link connectivity information, which is not adequate for dynamic topology. Here, slow update of neighbour table entries causes link failures which affect performance parameter as packet drop, maximum delay, energy consumption, and reduced throughput. In the dynamic hello technique, new neighbour nodes and lost neighbour nodes are used to compute link change rate (LCR) and hello-interval/refresh rate (r). Exchange of link connectivity information at a fast rate consumes unnecessary bandwidth and energy. In MANET resource wastage can be controlled by avoiding the re-route discovery, frequent error notification, and local repair in the entire network. We are enhancing the existing hello process, which shows significant improvement in performance.
Distributed MAC Protocol for Cognitive Radio Networks: Design, Analysis, and ...Polytechnique Montreal
In this paper, we investigate the joint optimal sensing and distributed Medium Access Control (MAC) protocol design problem for cognitive radio (CR) networks. We consider both scenarios with single and multiple channels. For each scenario, we design a synchronized MAC protocol for dynamic spectrum sharing among multiple secondary users (SUs), which incorporates spectrum sensing for protecting active primary users (PUs). We perform saturation throughput analysis for the corresponding proposed MAC protocols that explicitly capture the spectrum-sensing performance. Then, we find their optimal configuration by formulating throughput maximization problems subject to detection probability constraints for PUs. In particular, the optimal solution of the optimization problem returns the required sensing time for PUs' protection and optimal contention window to maximize the total throughput of the secondary network. Finally, numerical results are presented to illustrate developed theoretical findings in this paper and significant performance gains of the optimal sensing and protocol configuration.
Bit Error Rate Performance of MIMO Spatial Multiplexing with MPSK Modulation ...ijsrd.com
Wireless communication is one of the most effective areas of technology development of our time. Wireless communications today covers a very wide array of applications. In this, we study the performance of general MIMO system, the general V-BLAST architecture with MPSK Modulation in Rayleigh fading channels. Based on bit error rate, we show the performance of the 2x2 schemes with MPSK Modulation in noisy environment. We also show the bit error rate performance of 2x2, 3x3, 4x4 systems with BPSK modulation. We see that the bit error rate performance of 2x2 systems with QPSK modulation gives us the best performance among other schemes analysed here.
JOINT-DESIGN OF LINK-ADAPTIVE MODULATION AND CODING WITH ADAPTIVE ARQ FOR COO...IJCNCJournal
This paper analyzes the efficiency of a joint-design of an adaptive modulation and coding (AMC) at the
physical (PHY) layer with an adaptive Rmax-truncated selective-repeat automatic repeat request (ARQ)
protocol at the medium access control (MAC) layer to maximize the throughput of cooperative nonregenerative
relay networks under prescribed delay and/or error performance constraints. Particularly, we
generalize the existing design model/results for cross-layer combining of AMC along with truncated ARQ
in non-cooperative diversity networks in three-folds: (i) extension of the cross-layer PHY/MAC design or
optimization to cooperative diversity systems; (ii) generalization/unification of analytical expressions for
various network performance metrics to generalized block fading channels with independent but nonidentically
distributed (i.n.d) fading statistics among the spatially distributed nodes; (iii) analysis of the
effectiveness of joint-adaptation of the maximum retransmission limit Rmax of ARQ protocol and
cooperative diversity order N for delay-insensitive applications. Our insightful numerical results reveal
that the average throughput can be increased significantly by judiciously combining two additional degrees
of freedom (N and Rmax) that are available in cooperative amplify-and-forward (CAF) relay networks
besides employing AMC at the PHY layer, especially in the most challenging low signal-to-noise ratio
(SNR) regime.
Routing in Cognitive Radio Networks - A SurveyIJERA Editor
Cognitive Radio Networks (CRNs) have been emerged as a revolutionary solution to migrate the spectrum
scarcity problem in wireless networks. Due to increasing demand for additional spectrum resources, CRNs have
been receiving significant research to solve issues related with spectrum underutilization. This technology
brings efficient spectrum usage and effective interference avoidance, and also brings new challenges to routing
in multi-hop Cognitive Radio Networks. In CRN, unlicensed users or secondary users are able to use
underutilized licensed channels, but they have to leave the channel if any interference is caused to the primary or
licensed users. So CR technology allows sharing of licensed spectrum band in opportunistic and non-interfering
manner. Different routing protocols have been proposed recently based on different design goals under different
assumptions.
A new clustering technique based on replication for MANET routing protocolsTELKOMNIKA JOURNAL
The cluster head nodes in most mobile ad hoc networks (MANET) clustering protocols take on an extraordinary role in managing routing information. The reliability, efficiency and scalability of the clustering in MANET will ultimately be dramatically impacted. In this work we establish a new approach to form the clusters in MANET called the square cluster-based routing protocol (SCBRP). That protocol is based on the theory of replication. The goal of the protocol is to achieve reliability, availability and scalability with in the MANET. The proposed protocol is evaluated by caring the performance analysis using the NS-3 simulator. The performance shows 50% improvementin data delivering ratio in large network size, also shows an improvement in network stability and availability which is reflected in energy consumption measurements and increase in the system lifetime to 20%.
Design and analysis of routing protocol for cognitive radio ad hoc networks i...IJECEIAES
Multi-hop routing protocol in cognitive radio mobile ad hoc networks (CRMANETs) is a critical issue. Furthermore, the routing metric used in multi-hop CRMANETs should reflect the bands availability, the links quality, the PU activities and quality of service (QoS) requirements of SUs. For the best of our knowledge, many of researchers investigated the performance of the different routing protocols in a homogeneous environment only. In this paper, we propose a heterogeneous cognitive radio routing protocol (HCR) operates in heterogeneous environment (i.e. the route from source to destination utilize the licensed and unlicensed spectrum bands). The proposed routing protocol is carefully developed to make a tradeoff between the channel diversity of the routing path along with the CRMANETs throughput. Using simulations, we discuss the performance of the proposed HCR routing protocol and compare it with the AODV routing protocol using a discrete-event simulation which we developed using JAVA platform.
To increase the network capacity, there is
need to minimize the interference among nodes and
optimum control of topology in the foundation of
network. Recently, technological development helps to
build of mobile ad-hoc networks (MANETs) in order to
improve the quality of service (QoS) in terms of delay. In
contradictory to the objective of minimizing interference,
it is important to concern topology control in delay
constrained environment. The present research work
attempts to control the delay-constrained topology with
jointly considering delay and interference concept.
Additionally, the study proposed an interference oriented
topology control algorithm for delay-constrained
MANETs by taking account of both the interference
constraint and the delay constraint under the specific
condition of transmission delay, contention delay and the
queuing delay. Further, the study investigated the impact
of node mobility on the interference oriented topology
control algorithm. Finally, the results of the present
study shows that the proposed algorithm controls the
topology to convince the interference constraint, and
increases the transmit range to congregate the delay
requirement. Also, the study conclude that the algorithm
could effectively reduce the delay protocol and improve
the performance effectively in delay-constrained mobile
ad hoc networks.
Thus the article offers the model represented by algebraic equations and inequalities for routing and
policing traffic in infocommunication network. The novelty of the model is as follows: multiflow nature of
modern ICN is taken into account (1), i.е. a set of flows circling between different pairs of network routers are
considered simultaneously; coherent formalization of processes of traffic routing and policing within the model
that has lower dimensionality in comparison to known earlier is provided; the choice of optimality criterion, use
of which allows to implement multipath routing with consequent inclusion of paths as well as to organize
limitation of flow intensity on all the used routs simultaneously depending on their characteristics and flow
priority. According to the results of the analysis conducted we offer recommendations for choosing relation in
numerical values of routing metrics and service denial regarding the provision of the given values for the main
QoS characteristics, e.g. average packet delay. The model can be used as a basis for perspective protocol
decisions aimed at coherence of solutions for the tasks of traffic routing and policing. Further development of
the given model is possible under full account of stochastic characteristics of packet flows circling in the
network.
Performance of cluster-based cognitive multihop networks under joint impact o...TELKOMNIKA JOURNAL
In this paper, we evaluate outage probability (OP) of a cluster-based multi-hop protocol operating
on an underlay cognitive radio (CR) mode. The primary network consists of multiple independent
transmit/receive pairs, and the primary transmitters seriously cause co-channel interference (CCI) to the
secondary receivers. To improve the outage performance for the secondary network under the joint impact
of the CCI and hardware imperfection, we employ the best relay selection at each hop. Moreover, the
destination is equipped with multiple antennas and uses the selection combining (SC) technique to
enhance the reliability of the data transmission at the last hop. For performance evaluation, we first derive
an exact formula of OP for the primary network which is used to calculate the transmit power of the
secondary transmitters. Next, an exact closed-form expression of the end-to-end OP for the secondary
network is derived over Rayleigh fading channels. We then perform Monte-Carlo simulations to validate
the derivations. The results present that the CCI caused by the primary operations significantly impacts on
the outage performance of the secondary network.
PERFORMANCE IMPROVEMENT OF NONREGENERATIVE COOPERATIVE RELAY NETWORKS WITH OP...ijwmn
This paper analyzes the performance of Channel Side Information (CSI)-assisted cooperative amplify-andforward
(CAF) relay networks that employ both the node placement (i.e., relay position) based optimal
power allocation policy among collaborating nodes and adaptive M-ary quadrature amplitude modulation
(M-QAM)/ M-ary phase shift keying (M-PSK) techniques in generalized wireless fading environments. In
particular, we advocate a simple yet unified numerical approach based on the marginal moment generating
function (MGF) of the total received Signal to Noise Ratio (SNR) to derive analytical expressions for the
average bit error rate (ABER), mean achievable spectral efficiency, and outage probability performance
metrics. The proposed analytical framework is sufficiently general and flexible to characterize the
performance of adaptive-link CAF relay networks over a wide range of fading distributions (i.e., not
restricted to Rayleigh fading or independent identically distributed (i.i.d) Nakagami-m fading ) with
independent but non-identically distributed (i.n.d) fading statistics across the spatially distributed diversity
paths. Additionally, we further simplify the computational complexity, by employing the use of an
“approximate MGF expression” to compute the system performance metrics over the generalized fading
channel. Employing the above novel approach based on “approximate MGF” in conjunction derived
analytical frameworks allows us to simplify the computation complexity of achievable spectral efficiency as
well as ABER of CAF relay system in the generalized fading environments by simply replacing appropriate
single channel MGF which is readily available
PERFORMANCE OF OLSR MANET ADOPTING CROSS-LAYER APPROACH UNDER CBR AND VBR TRA...IJCNCJournal
The routing protocols play an important role in Mobile Ad-Hoc Network (MANET) because of the dynamically change of its topology. Optimized Link State Routing (OLSR), unawareness of Quality of Service (QoS) and power-consumed protocol, is an example of a widely-used routing protocol in MANET.
The Multi-Point Relays (MPR) selection algorithm is very crucial in OLSR. Therefore, firstly, we propose a heuristic method to select the best path based on two parameters; Bit Error Rate (BER) derived from the physical layer and Weighted Connectivity Index (CI) adopted from the network layer. This can be done via the cross-layer design scheme. This is anticipated to enhance the performance of OLSR, provide QoS
guarantee and improve the power consumption. The performances of the proposed scheme are investigated
by simulation of two types of traffics: CBR and VBR (MPEG-4), evaluated by metrics namely Throughput, Packet Delivery Ratio (PDR), Average End-to-End Delay, Control Overhead and Average Total Power Consumption.We compare our results with the typical OLSR and OLSR using only Weighted CI. It is
obvious that our proposed scheme provides superior performances to the typical OLSR and OLSR using only Weighted CI, especially, at high traffic load.
A MANET is an autonomous collection of mobile users that communicate over relatively bandwidth constrained wireless links. When designing mobile ad hoc networks, several interesting and difficult problems arise because of the shared nature of the wireless medium, limited transmission power (range) of wireless devices, node mobility, and battery limitations. This paper aims at providing a new schema to improve Dynamic Source Routing (DSR) Protocol. The aim
behind the proposed enhancement is to find the best route in acceptable time limit without having broadcast storm. Moreover, O-DSR enables network not only to overcome congestion but also maximize the lifetime of mobile nodes. Some simulations results show that the Route Request (RREQ) and the Control Packet Overhead decrease by 15% when O-DSR is used, consequently. Also the global energy consumption in O-DSR is lower until to 60 % , which leads to a long lifetime of the network.
IMPLEMENTATION AND COMPARISION OF DATA LINK QUALITY SCHEME ON ODMRP AND ADMR ...ijngnjournal
An ad hoc network is a collection of wireless mobile nodes dynamically forming a temporary network without the use of any fixed network infrastructure or centralized administration. In order to enable communication within the network, a routing protocol is needed to discover routes between nodes. The primary goal of ad hoc network routing protocols is to establish routes between node pairs so that messages may be delivered reliably and in a timely manner. The objective of any routing protocol is to have packet delivered with least possible cost in terms of receiving power, transmission power, battery energy consumption and distance. All these factors basically effect the establishment of link between the mobile nodes and liability and stability of these links. In this paper, we implement a data link quality scheme on two protocols ODMRP and ADMR and compare them on the bases link quality and link stability.
Mobile ad hoc network is a reconfigurable network of mobile nodes connected by multi-hop wireless links and capable of operating without any fixed infrastructure support. In order to facilitate communication within such self-creating, self-organizing and self administrating network, a dynamic routing protocol is needed. The primary goal of such an ad hoc network routing protocol is to discover and establish a correct and efficient route between a pair of nodes so that messages may be delivered in a timely manner. Route construction should be done with a minimum of overhead and bandwidth consumption. This paper examines two routing protocols, both on-demand source routing, for mobile ad hoc networks– the Dynamic Source Routing (DSR), an flat architecture based and the Cluster Based Routing Protocol (CBRP), a cluster architecture based and evaluates both routing protocols in terms of packet delivery fraction, normalized routing load, average end to end delay, throughput by varying number of nodes per sq. km, traffic sources and mobility. Simulation results show that in high
mobility (pause time 0s) scenarios, CBRP outperforms DSR. CBRP scales well with increasing number of nodes.
Modified q aware scheduling algorithm for improved fairness in 802.16 j networksIJCNCJournal
Deployment of Multi-hop Relays in WiMax based Cellu
lar Networks is considered as a cost effective
solution to increase the Coverage area of Base Stat
ion and also to improve the Network Capacity with h
igh
quality short links. Scheduling became a challengin
g task in these Multi-hop Relay Wireless Cellular
Networks of IEEE 802.16j standard. H. Chen, X. Xie
and H. Wu proposed a Q-aware Scheduling
Algorithm in which back-pressure flow control mecha
nism is used to reflect current Q size of the Relay
s
and considered high back-pressure links to include
in Concurrent Transmission Scenarios, to maximize t
he
throughput. This focus on high back-pressure links,
leads to starvation of Mobile Stations having low
back-
pressure links, resulting unfairness in some cases.
To remedy this situation, a Fair Link Inclusion (F
LI)
mechanism is applied in Greedy Algorithm of Q-aware
Scheduling Algorithm. Simulation results show that
Modified Q-aware Scheduling Algorithm with FLI mech
anism has reasonable improvement in fairness and
maintaining steady throughput when compared with ex
isting algorithms.
AN EFFECTIVE CONTROL OF HELLO PROCESS FOR ROUTING PROTOCOL IN MANETSIJCNCJournal
In the mobile ad hoc network (MANET) update of link connectivity is necessary to refresh the neighbor tables in data transfer. A existing hello process periodically exchanges the link connectivity information, which is not adequate for dynamic topology. Here, slow update of neighbour table entries causes link failures which affect performance parameter as packet drop, maximum delay, energy consumption, and reduced throughput. In the dynamic hello technique, new neighbour nodes and lost neighbour nodes are used to compute link change rate (LCR) and hello-interval/refresh rate (r). Exchange of link connectivity information at a fast rate consumes unnecessary bandwidth and energy. In MANET resource wastage can be controlled by avoiding the re-route discovery, frequent error notification, and local repair in the entire network. We are enhancing the existing hello process, which shows significant improvement in performance.
Distributed MAC Protocol for Cognitive Radio Networks: Design, Analysis, and ...Polytechnique Montreal
In this paper, we investigate the joint optimal sensing and distributed Medium Access Control (MAC) protocol design problem for cognitive radio (CR) networks. We consider both scenarios with single and multiple channels. For each scenario, we design a synchronized MAC protocol for dynamic spectrum sharing among multiple secondary users (SUs), which incorporates spectrum sensing for protecting active primary users (PUs). We perform saturation throughput analysis for the corresponding proposed MAC protocols that explicitly capture the spectrum-sensing performance. Then, we find their optimal configuration by formulating throughput maximization problems subject to detection probability constraints for PUs. In particular, the optimal solution of the optimization problem returns the required sensing time for PUs' protection and optimal contention window to maximize the total throughput of the secondary network. Finally, numerical results are presented to illustrate developed theoretical findings in this paper and significant performance gains of the optimal sensing and protocol configuration.
Bit Error Rate Performance of MIMO Spatial Multiplexing with MPSK Modulation ...ijsrd.com
Wireless communication is one of the most effective areas of technology development of our time. Wireless communications today covers a very wide array of applications. In this, we study the performance of general MIMO system, the general V-BLAST architecture with MPSK Modulation in Rayleigh fading channels. Based on bit error rate, we show the performance of the 2x2 schemes with MPSK Modulation in noisy environment. We also show the bit error rate performance of 2x2, 3x3, 4x4 systems with BPSK modulation. We see that the bit error rate performance of 2x2 systems with QPSK modulation gives us the best performance among other schemes analysed here.
ENERGY EFFICIENCY OF MIMO COOPERATIVE NETWORKS WITH ENERGY HARVESTING SENSOR ...ijasuc
This paper addresses the maximizing network lifetime problem in wireless sensor networks (WSNs) taking
into account the total Symbol Error rate (SER) at destination. Therefore, efficient power management is
needed for extend network lifetime. Our approach consists to provide the optimal transmission power
using the orthogonal multiple access channels between each sensor. In order to deeply study the
properties of our approach, firstly, the simple case is considered; the information sensed by the source
node passes by a single relay before reaching the destination node. Secondly, global case is studied; the
information passes by several relays. We consider, in the previous both cases, that the batteries are nonrechargeable. Thirdly, we spread our work the case where the batteries are rechargeable with unlimited
storage capacity. In all three cases, we suppose that Maximum Ratio Combining (MRC) is used as a
detector, and Amplify and Forward (AF) as a relaying strategy. Simulation results show the viability of
our approach which the network lifetime is extended of more than 70.72%when the batteries are non
rechargeable and 100.51% when the batteries are rechargeable in comparison with other traditional
method.
ENERGY EFFICIENCY OF MIMO COOPERATIVE NETWORKS WITH ENERGY HARVESTING SENSOR ...ijasuc
This paper addresses the maximizing network lifetime problem in wireless sensor networks (WSNs) taking
into account the total Symbol Error rate (SER) at destination. Therefore, efficient power management is
needed for extend network lifetime. Our approach consists to provide the optimal transmission power
using the orthogonal multiple access channels between each sensor. In order to deeply study the
properties of our approach, firstly, the simple case is considered; the information sensed by the source
node passes by a single relay before reaching the destination node. Secondly, global case is studied; the
information passes by several relays. We consider, in the previous both cases, that the batteries are nonrechargeable. Thirdly, we spread our work the case where the batteries are rechargeable with unlimited
storage capacity. In all three cases, we suppose that Maximum Ratio Combining (MRC) is used as a
detector, and Amplify and Forward (AF) as a relaying strategy. Simulation results show the viability of
our approach which the network lifetime is extended of more than 70.72%when the batteries are non
rechargeable and 100.51% when the batteries are rechargeable in comparison with other traditional
method.
Pilot Decontamination over Time Frequency and Space Domains in Multi-Cell Ma...IJECEIAES
In this article, we show that Pilot contamination problem can be seen as a source separation problem using time, frequency, and space domains. Our method capitalizes on a nonunitary joint diagonalization of spatial quadratic time-frequency (STFD) signal representation to identify the desired and interfering users. We first compute the noise subspace from the STFD matrices selected appropriately. Secondly, we use the noise subspace obtained to estimate the Elevation (El) and the Azimuth (Az) angles for which the MUSIC cost function is maximized. Numerical simulations are provided to illustrate the effectiveness and the behavior of the proposed approach.
Efficiency of two decoders based on hash techniques and syndrome calculation ...IJECEIAES
The explosive growth of connected devices demands high quality and reliability in data transmission and storage. Error correction codes (ECCs) contribute to this in ways that are not very apparent to the end user, yet indispensable and effective at the most basic level of transmission. This paper presents an investigation of the performance and analysis of two decoders that are based on hash techniques and syndrome calculation over a Rayleigh channel. These decoders under study consist of two main features: a reduced complexity compared to other competitors and good error correction performance over an additive white gaussian noise (AWGN) channel. When applied to decode some linear block codes such as Bose, Ray-Chaudhuri, and Hocquenghem (BCH) and quadratic residue (QR) codes over a Rayleigh channel, the experiment and comparison results of these decoders have shown their efficiency in terms of guaranteed performance measured in bit error rate (BER). For example, the coding gain obtained by syndrome decoding and hash techniques (SDHT) when it is applied to decode BCH (31, 11, 11) equals 34.5 dB, i.e., a reduction rate of 75% compared to the case where the exchange is carried out without coding and decoding process.
EFFICIENT ANALYSIS OF THE ERGODIC CAPACITY OF COOPERATIVE NON-REGENERATIVE RE...ijwmn
In this paper, we proposed a novel efficient method of analyzing the ergodic channel capacity of the
cooperative amplify-and-forward (CAF) relay system. This is accomplished by employing a very tight
approximate moment generating function (MGF) of end-to-end signal-to-noise ratio of 2-hop multi-relay
system, which is In this paper, we proposed a novel efficient method of analyzing the ergodic channel
capacity of the cooperative amplify-and-forward (CAF) relay system. This is accomplished by employing a
very tight approximate moment applicable to myriad of fading environments including mixed and
composite fading channels. Three distinct adaptive source transmission policies were considered in our
analysis namely: (i) constant power with optimal rate adaptation (ORA); (ii) optimal joint power and rate
adaptation (OPRA); and (iii) fixed rate with truncated channel inversion (TCIFR). The proposed frame
work based on the novel approximate MGF method is sufficiently general to encapsulate all types of fading
environments (especially for the analysis of the mixed fading case)and provides significant advantage to
model wireless system for mixed and composite fading channel. In addition to simplifying computation
complexity of ergodic capacity for CAF relaying schemes treated in literature, we also derive closed form
expressions for the above three adaptive source transmission policies under Nakagami-m fading with i.n.d
statistics. The accuracy of our proposed method has been validated with existing MGF expressions that are
readily available for specific fading environments in terms of bounds, and via Monte Carlo simulations.
A broadband MIMO antenna's channel capacity for WLAN and WiMAX applicationsIJICTJOURNAL
This paper describes the findings of a research into the multiple input multiple output (MIMO) channel capacity of a broadband dual-element printed inverted F-antenna (PIFA) antenna array. The dual-element antenna array is made up of two PIFAs that are meant to fit on a teeny-tiny and small wireless communication device that runs at 5 GHz. The device's frequency range is between 3.5 and 4.5 GHz. These PIFAs are also loaded into the device during the installation process. In order to investigate the channel capacity, the ray tracing method is employed in two different kinds of circumstances. For the purpose of carrying out this analysis of the channel capacity, both the simulated and measured mutual couplings of the broadband MIMO antenna are utilized.
Dynamic Manycasting in Optical Split-Incapable WDM NetworksfAlyciaGold776
Dynamic Manycasting in Optical Split-Incapable WDM Networks
for Supporting High-Bandwidth Applications
Jeremy Plante, Arush Gadkar, and Vinod Vokkarane
Department of Computer and Information Science, University of Massachusetts, Dartmouth, MA
Email: {jplante, agadkar, vvokkarane}@umassd.edu
Abstract—With the advent of bandwidth intensive applications,
the demand for manycast networking capabilities has become an
essential component of wavelength division multiplexed (WDM)
optical networks. Traditionally, the manycast functionality is
accomplished by splitting a signal all-optically, thereby creating
a light-tree, which originates from the source node and reaches
a subset of the destination nodes. To support the manycasting
functionality in an optical network that is Split-Incapable, i.e., the
optical cross connects are incapable of switching an incoming
optical signal to more than one output interface, one must
implement a logical overlay to the underlying optical layer. A
naı̈ve approach to accomplish this is by creating a set of unicast
lightpaths that originate at the source node and terminate at a
subset of the destination nodes of the manycast request. However,
for a large number of requests this approach leads to a poor
utilization of network resources. To overcome this problem, we
propose two overlay approaches: Manycasting with Drop at
Member Node (MA-DAMN) and Manycasting with Drop at Any
Node (MA-DAAN). In these solutions, we achieve manycasting
by creating a set of lightpath routes (possibly multiple hops)
in the overlay layer. We consider a dynamic traffic model and
propose efficient heuristics to solve the MA-DAMN and MA-
DAAN problems with a goal of minimizing the total number
of wavelengths required to satisfy the requests. Moreover, we
present a simple heuristic to approximate the unicast approach
of the naı̈ve method. Our results demonstrate that both the
overlay approaches reduce the wavelength consumption by ap-
proximately 33 − 45% over the naı̈ve manycasting via WDM
unicast approach for real-world large-scale networks.1
Index Terms—Manycasting, WDM, Overlay, Lightpath Routes,
Split-Incapable, O-E-O.
I. INTRODUCTION
Optical wavelength division multiplexed (WDM) networks
have proven to be an important technology to provide high-
bandwidth and services to the next-generation Internet. Many-
casting has caught the attention of several researchers during
the recent past, due to the emergence of many distributed
applications [1], [2]. Distributed applications, such as video
conferencing, distributed interactive simulations (DIS), grid
computing, storage area network (SAN), and distributed con-
tent distribution network (CDN) applications require large
amounts of bandwidth and an effective communication be-
tween a single source and a set of destinations. For example,
the data generated by the Large Hadron Collider is frequently
sent to multiple Department of Energy (DOE) laboratories
across the United States over the DOE’ ...
Performance Analysis of Enhanced Opportunistic Minimum Cost Routingin Mobile ...IJERA Editor
Mobile Ad-Hoc Network (MANET) is a collection of wireless mobile nodes forming a temporary network with
infrastructure less environment to establish a data transmission between nodes within the network. A routing
protocol is used to discover routes between nodes. In this paper, we study the three existing routing protocols
namely AODV, DSDV and DSR to analyze theirperformance based on set of parameters.AODV and DSR
deliver almost all the packets compared to DSDV. Hence we try to modify the AODVprotocol and use in the
cooperative transmission.
In this paper, we study the cooperative transmission at the network layer and cooperative diversity at the
physical layer as a joint optimization of the transmission power in a Mobile Ad-Hoc Network (MANET) with
static channel. However due to variable wireless channels static routing is suboptimal. Proposed protocol
proactively selects forwarding nodes that work cooperatively forwarding the packet towards the destination.
Cooperative transmission side diversity helps in reducing interference. Diversity can be achieved at the physical
layer by coordinating the multiple nodes. Nodes are equipped with Omni-directional antenna and take the
advantages of transmission side diversity to achieve energy saving, under the assumption that channel gains are
available at the transmitters.
The proposed Opportunistic Minimum Cost Cooperative Transmission Shortest Path (OMCTSP) algorithms
select the best optimum route with minimum cost in terms of energy, number of hops, available bandwidth, link
quality (SNR) and outage probability. As the network becomes larger, finding optimal routes becomes
computationally intractable as the complexity of the dynamic programming (DP) approach increases as o (2
2n)
where n is the number of nodes in the networks. Hence we develop two suboptimal algorithms have complexity
of o (n2) perform as same as optimal algorithm. Also developthe Opportunistic Cooperative Routing in MANET
(O_CORMAN), which is a network layer opportunistic routing scheme for mobile ad hoc networks. Nodes in
the network use the components proactive routing protocol, forwarder list update and local re-transmission. We
evaluate the performance using NS 2.32 simulator there is significant performance improvement with respect to
energy, throughput packet delivery, and delay compared with Modified AODV (OMCTSP).
PERFORMANCE ANALYSIS OF THE LINK-ADAPTIVE COOPERATIVE AMPLIFY-AND-FORWARD REL...IJCNCJournal
This paper analyzes the performance of cooperative amplify-and-forward (CAF) relay networks that
employ adaptive M-ary quadrature amplitude modulation (M-QAM)/M-ary phase shift keying (M-PSK)
digital modulation techniques in Nakagami-m fading channel. In particular, we present and compared the
analysis of CAF relay networks with different cooperative diversity and opportunistic routing strategies
such as regular Maximal Ratio Combining (MRC), Selection Diversity Combining (SDC), Opportunistic
Relay Selection with Maximal Ratio Combining (ORS-MRC) and Opportunistic Relay Selection with
Selection Diversity Combining (ORS-SDC). We advocate a simple yet unified numerical approach based on
the marginal moment generating function (MGF) of the total received SNR to compute the average symbol
error rate (ASER), mean achievable spectral efficiency, and outage probability performance metrics.
Transferring quantum information through theijngnjournal
Transmission of information in the form of qubits much faster than the speed of light is the important
aspects of quantum information theory. Quantum information processing exploits the quantum nature of
information that needs to be stored, encoded, transmit, receive and decode the information in the form of
qubits. Bosonic channels appear to be very attractive for the physical implementation of quantum
communication. This paper does the study of quantum channels and how best it can be implemented with
the existing infrastructure that is the classical communication. Multiple access to the quantum network is
the requirement where multiple users want to transmit their quantum information simultaneously without
interfering with each others.
Transferring Quantum Information through the Quantum Channel using Synchronou...josephjonse
Transmission of information in the form of qubits much faster than the speed of light is the important aspects of quantum information theory. Quantum information processing exploits the quantum nature of information that needs to be stored, encoded, transmit, receive and decode the information in the form of qubits. Bosonic channels appear to be very attractive for the physical implementation of quantum communication. This paper does the study of quantum channels and how best it can be implemented with the existing infrastructure that is the classical communication. Multiple access to the quantum network is the requirement where multiple users want to transmit their quantum information simultaneously without interfering with each others.
The aim of this paper is to determine the viability of Indoor Optical Wireless Communication System. This paper introduces Visible Light Communication along with its merits, demerits and applications. Then the main characteristics of VLC system are described, around which the project is designed. Multiple Input-Multiple Output (MIMO) technique is used in the project in order to enhance the data rate of transmission. Instead of using a system of only one LED and one APD, which transmits only one bit at a time, a system of 4 LEDs and 4 APDs is introduced, which increases the data rates by 300% from the previous case. We observe the signal, noise, SNR, BER etc. across the room dimension. Finally, in the last chapter we summarize our results on the basis of MATLAB simulations and propose some modifications to this model that can be implemented in future.
Channel characterization and modulation schemes of ultra wideband systemsijmnct
Channel measurements are generally the basis for channel models. Strictly speaking, channel models do
not exclusively require measurements, but it is a fact that all standardized models are derived from
measurements. This licentiate paper is focused on the characterization of ultra-wideband wireless channels.
The paper presents the characterization of ultra wide band system with their benefits and drawbacks within
the telecommunication industry. Furthermore with the advantages of Ultra wideband several modulation
techniques for UWB are discussed in this paper.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
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Bob Boule
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1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
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Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
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2. 30 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 51, NO. 1, JANUARY 2005
Fig. 1. MIMO relay channel.
the destination node). We present algorithms to compute the
bounds accordingly. We also provide in Appendix B another
lower bound by using the water-filling technique.
Next, we generalize the study to a more interesting case—the
Rayleigh fading case. We focus on the ergodic capacity of the
MIMO relay channel, assuming receiver channel state informa-
tion (CSI) only. It is somewhat surprising that the upper bound
can meet the lower bound under certain conditions (not neces-
sarily degradedness), indicating that the ergodic capacity can be
characterized exactly. Thus motivated, we investigate conditions
for capacity achievability. In particular, we identify sufficient
conditions to achieve the ergodic capacity when all nodes have
the same number of antennas; and our intuition for this finding
is as follows. The source node and the relay node can function as
a “virtual” transmit antenna array when the relay node is located
close to the source node, thus making it possible to achieve the
capacity.
We note that the findings on the ergodic capacity point to
independent coding strategies at the source node and the relay
node. Such independence of coding strategies is due to the
channel uncertainty (randomness) at the transmitters. Com-
pared to the direct link, the relay channel offers a significant
capacity gain, thanks to the multiple-access gain from the MAC
part and the multiuser broadcast gain from the BC part. We note
that both the multiple-access gain and the broadcast gain benefit
from the full duplexity at the relay node. Needless to say, a key
step to reap the capacity gain is to develop coding strategies for
the cooperative MAC and the cooperative BC. We also provide
numerical examples to illustrate the upper bound and the lower
bound on the ergodic capacity. Motivated by the capacity gain
by using the relay node, we finally discuss the utility of the
MIMO relay channel in cooperative communications in ad hoc
networks.
During the final stage of our preparation for this paper, we
were informed of independent work [13], which presents an
elegant proof for the independence of the signals from the
source node and the relay node for the fading case. Building
on this result and our preliminary works [27], [28], we have
obtained the results in Theorems 4.1 and 4.2. As noted above,
we have also investigated in depth the sufficient conditions
for capacity achievability for two interesting cases, i.e., the
high-signal–to–noise-ratio (SNR) regime and the scalar case.
Loosely speaking, our capacity results for the Rayleigh fading
case can be viewed as a generalization of Theorem 2 in [12].
Throughout this paper, we use to denote the expectation op-
erator (in some cases, subscripts are used to specify the random
variable); “ ” stands for the conjugate transpose; denotes an
identity matrix; is an all-zero matrix of proper dimensions; the
distribution of a circularly symmetric complex Gaussian vector
with mean and covariance matrix is denoted as ;
, , , and are used in the matrix positive (semi)definite
ordering sense [11].
The rest of the paper is organized as follows. In Section II,
we present the system model. We derive in Section III upper
bounds and lower bounds on the capacity of the Gaussian
MIMO relay channel with fixed channel gains. Next, we gen-
eralize the study to the Rayleigh fading case. We present in
Section IV an upper bound and a lower bound on the ergodic
capacity and give numerical results for different SNR cases.
We then discuss sufficient conditions for achieving the ergodic
capacity in Section V. Finally, a potential application of the
relay channel in cooperative communications in ad hoc net-
works is discussed in Section VI.
II. SYSTEM MODEL
Consider a general MIMO relay channel where the received
signals at the relay and destination nodes can be written as
=
=
(1)
where
• , are and transmitted signals
from the source node and the relay node; the power con-
straints on the transmit signals are and
;
• and are and received signals at the
destination node and the relay node. We assume that
— the relay node has two sets of antennas, one for recep-
tion and the other for transmission. That is, the relay
node operates in the full-duplex mode;
— since the relay node has full knowledge of what to
transmit therein, it can cancel out the interference
from its own transmit antennas at its receive antennas.
• , , and are , , and
channel gain matrices, as depicted in Fig. 1. In what fol-
lows, we consider two scenarios for the channel matrices:
— all the channel matrices are fixed and known at both
the transmitters and the receivers;
— all the channel matrices are random and independent,
where the entries of each matrix are independent and
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3. WANG et al.: ON THE CAPACITY OF MIMO RELAY CHANNELS 31
identically distributed (i.i.d.) complex Gaussian vari-
ables with zero mean, independent real and imagi-
nary parts, each with variance , and they are avail-
able at the corresponding receivers only (i.e., receiver
CSI only).
• , , and are parameters related to the SNR [16]
SNR SNR SNR
(2)
where SNR and SNR are the normalized power ratios of
to the noise (after fading) at each receiver antenna of
the relay node and the destination node, and SNR is the
normalized power ratio of to the noise at each antenna
of the destination node;
• and are independent and circularly
symmetric complex Gaussian noise vectors with distribu-
tions and , and are uncorrelated
to and .
III. CAPACITY BOUNDS: THE FIXED CHANNEL CASE
In the following, we derive upper bounds and lower bounds
on the capacity of the Gaussian MIMO relay channel with fixed
channel gains.
A. Upper Bounds and Lower Bounds
Recall from [4] that the channel capacity of a general
Gaussian relay channel is upper-bounded by
(3)
where the first term in can be treated as the sum rate
from the source node to the relay node and the destination node,
corresponding to a BC part; and the second term can be viewed
as the sum rate from the source node and the relay node to the
destination node, corresponding to a MAC part. Indeed, (3) has
an interesting max-flow min-cut interpretation [5], as illustrated
in Fig. 2. Roughly speaking, the rate of the information flow
transmitted on the relay channel is constrained by the bottle-
neck corresponding to either the first cut (BC) or the second one
(MAC).
Without loss of generality, let and be random vec-
tors with zero-mean and covariance matrices , defined as
for . Throughout, we assume that
and . Define .
First, we need the following lemmas (the proof of Lemma 3.1
is relegated to Appendix A).
Lemma 3.1: There exists such that
(4)
and the equality can be achieved by a matrix
when .
Fig. 2. The relay channel: max-flow min-cut.
Intuitively speaking, Lemma 3.1 reveals that for any given
and , we can find codebooks for and such that
the covariance matrix satisfies the following inequality:
Furthermore, if , then for any given , there
exists such that the equality is achieved.
Lemma 3.2: For any two complex random vectors and ,
, we have that
(5)
the equality is achieved if .
The proof follows simply from the fact that the covariance
matrix of a random vector is always positive semidef-
inite. That is,
Let and . It fol-
lows that
If signals and are chosen such that , then
Applying Lemma 3.2, for , we have that
(6)
It is clear that the optimal distribution in (3) is
Gaussian [4], [24 ] (see, e.g., Step following (19) and
Step following (22)). Observe that if Gaussian codebooks
are applied, the maximization problem on the RHS of (3)
would be with respected to three covariance matrices ,
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4. 32 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 51, NO. 1, JANUARY 2005
, and ; and this is nonconvex and highly nontrivial
in general. In Lemmas 3.1 and 3.2, we use one parameter
to capture the correlation between and (in contrast
to the cross-covariance matrix ), and this enables us to
solve the optimization by convex programming techniques (in
Appendix A, we present the definition for ). In what follows,
we present our results for the upper bound on the capacity of
Gaussian MIMO relay channels.
Theorem 3.1: [Fixed Channel Case] An upper bound on the
capacity of the MIMO relay channel is given by
(7)
where , ; and are given by
(8)
(9)
Remarks: To find the upper bound, we need to characterize
the optimal input covariance matrices and . Define
It can be seen that is concave in and that is con-
cave in . It follows that is concave in
[1]. More precisely, for a given , the upper bound is
concave in ; and it can be found by convex program-
ming. In what follows, we present an algorithm to compute the
upper bound.
Algorithm I
1. Carry out a quantization of interval , and denote the
corresponding set of (ascending) values as
;
2. For a given , apply convex programming to find the op-
timal value of and corresponding optimal and
, by solving the following optimization problem:
maximize
subject to
3. Pick another and repeat Step 2. Go to the next step when
the set is exhausted;
Algorithm I (Continued)
4. Compare all the values of associated with
, and find the largest and identify the
corresponding optimal parameters , and ;
5. Quantize and go to Step 2 using
for a new search;
6. Compare the refined results from the new search with the
old ones. If the error requirement is met, end the proce-
dures; otherwise, go to previous steps for another new
search.
A few more words on Algorithm I. Since there is no a priori
information about in the initialization step, the quantization is
equal-span. After the first iteration, we choose the “best guess”
of (namely, ), and then refine the search around it. To guar-
antee the convergency to the optimal point, the quantization
level should be reasonably large (e.g., ).
In the above, we use to capture the correlation between
signals transmitted from the source node and the relay node.
Now, we discuss the structure of the corresponding codebooks.
We can rewrite the transmitted signal as
with . Observe that is independent
of . Intuitively speaking, the vector signal can be decom-
posed into two orthogonal parts, which are independent of each
other. The second part, , stands for the projection of
onto the direction of . Thus,
can be viewed as a generalization of [4, Theorem 5].
For the special case where all the channel coefficients are
scalars (denoted as , , and , respectively), we have that
. Accordingly, we have that
and
(10)
It follows that
(11)
which boils down to a result in [6].
Consider channel models where the relay node may or may
not be used to aid the transmissions. If not used, the channel
becomes a point-to-point Gaussian MIMO channel. On the other
hand, if the relay node is used to aid the transmission and the
destination node treats the information directly from the source
node as noise, the channel boils down to a cascaded channel.
We have the following lower bound by finding the maximum
between the information rates for the two channel models.
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5. WANG et al.: ON THE CAPACITY OF MIMO RELAY CHANNELS 33
Theorem 3.2: [Fixed Channel Case] A lower bound on the
capacity of the Gaussian MIMO relay channel is given by
(12)
where
(13)
(14)
(15)
with
We outline the procedure to compute the lower bound
as follows:
Algorithm II
1. Use the water-filling technique to find [24];
2. Use the water-filling technique to find and the corre-
sponding optimal ;
3. Substitute into (15) to find by using the water-
filling technique.
In Appendix B, we provide another lower bound by using the
fact that the following rate is achievable for any given distribu-
tion [4]:
(16)
We note that this lower bound does not admit to a closed-form
solution, but it may yield a tighter bound.
B. Proofs of Theorems 3.1 and 3.2
Proof of Theorem 3.1:
Proof: Define
Given , we can rewrite the channel model as follows:
(17)
The sum rate of the corresponding BC channel is given by
(18)
(19)
where
follows from the definition of conditional entropy;
from the fact that circularly symmetric complex
Gaussian distribution maximizes entropy [24];
from the fact that
which is based on that given , the vector
is the sum of two independent circularly sym-
metric complex Gaussian vectors;
is because that is the conditional covari-
ance matrix of given that , and
which is independent of ;
from the following proof.
Applying Lemma 3.1, we have that
Then, by [11, p. 470]
It follows that
Observing that both sides in the above expression are positive
definite, we have that
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6. 34 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 51, NO. 1, JANUARY 2005
We conclude that
In summary, we have shown that
(20)
Next, we turn the attention to the sum rate of the MAC part.
Observe (21) and (22) at the bottom of the page, where
from the fact that the circularly symmetric complex
Gaussian distribution maximizes entropy [24] as men-
tioned before;
can be shown as follows. First, by Lemma 3.2, we have
that for
Next, following the same procedures as above, it is easy to show
that
Finally, taking the infimum on both sides yields (22).
Proof of Theorem 3.2:
Proof: If there is no relay node, the channel is a point-to-
point MIMO channel, and the corresponding channel capacity
is given by
(23)
Consider the case where the destination node treats the signal
from the source node as noise. In this case, the source node
optimizes its transmission only for the source–relay link, and
the relay node optimizes the transmission corresponding to the
relay–destination link. That is, the channel boils down to a cas-
caded channel. The following information rate is achievable for
the source–relay link:
(24)
and the corresponding optimal covariance matrix is . For
the relay–destination link, the received signal at the destination
is distorted by both noise and the signal from the source node.
Since the (optimal) signal from the source is also Gaussian, with
covariance matrix , the covariance matrix for noise plus the
source signal is . Therefore, the achievable
information rate for the relay–destination link is given by
(25)
The lower bound follows by combining (23) with (24)
and (25).
(21)
(22)
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7. WANG et al.: ON THE CAPACITY OF MIMO RELAY CHANNELS 35
IV. CAPACITY BOUNDS: THE RAYLEIGH FADING CASE
Now consider channel models where all the channel gain ma-
trices are random, and suppose that the channel gains are known
at the corresponding receivers only. In this scenario, we study
the ergodic capacity of the MIMO relay channel with receiver
CSI only. Simply put, the ergodic capacity is the highest achiev-
able data rate by coding the transmission symbols over infinitely
many blocks [34, p. 11].
Theorem 4.1: [Rayleigh Fading Case] An upper bound on
the ergodic capacity of the MIMO relay channel is given by
(26)
with
(27)
(28)
where the expectations are taken with respect to channel ma-
trices , , and .
Proof: Because of fading, the channel matrices are now
random. Then it follows that
(29)
where the expectations are taken with respect to corresponding
channel coefficients.
In the proof for Theorem 3.1, we have shown that
(30)
where
(31)
(32)
with .
Observe the power constraints on input signals
and
Then it follows that
Along the same lines as in [13], we conclude that the optimal
signal covariance matrices which maximize are iden-
tity matrices, i.e., , , and .
Therefore,
(33)
Note that is nonnegative with proba-
bility [9, Theorem 3.2]. Along the same line of the proof of
Theorem 3.1, we have that
Furthermore, by [24, Theorem 1], can also maxi-
mize the RHS of the preceding equation. We conclude that the
covariance matrices that maximize can also maximize
, i.e.,
(34)
In a nutshell, the mutual information rates in (29) are max-
imized by choosing and to be independent circularly
symmetric complex Gaussian vectors with ,
, and .
In what follows, we present a lower bound on the ergodic
capacity.
Theorem 4.2: [Rayleigh Fading Case] A lower bound on
the ergodic capacity of the MIMO relay channel is given by
(35)
with
(36)
(37)
where the expectations are taken with respect to corresponding
channel matrices.
Proof: Based on [4, Sec. VI], the following rate is achiev-
able by using block Markov coding:
(38)
Since the receivers have full CSI, it follows that
(39)
(40)
where the expectations are taken with respect to the corre-
sponding channel matrices. Note that
Let and be independent circularly symmetric complex
Gaussian random vectors with , , and
. Then, the lower bound in (35) follows along the same
line of the proof of Theorem 4.1.
Remarks: Interestingly, Theorems 4.1 and 4.2 reveal that
in a Rayleigh-fading channel, the corresponding codebooks at
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8. 36 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 51, NO. 1, JANUARY 2005
Fig. 3. Capacity bounds versus SNR for the case = = .
the source node and the relay node are independent, i.e.,
and are independent. (As shown later, the upper bound
and the lower bound can “converge” under certain conditions,
indicating that the ergodic capacity of the MIMO relay channel
can be characterized exactly.) In contrast, and are cor-
related for the fixed channel cases. Indeed, the capacity of the
MAC part is achieved when the source node and the relay node
have “complete” cooperation for the fixed channel case [4].
Our intuition for this finding is as follows. Since we consider
the relay channel with receiver CSI only, the transmitters have
no knowledge about the channel realizations. As a result, the
optimal codebooks at the source node and the relay node are
independent, due to the channel uncertainty at the transmitters.
Intuitively speaking, it is the uncertainty (randomness) of
and at the transmitters that makes and independent.
Recall that in a single-user MIMO channel with receiver CSI
only, the capacity is achieved when the power allocation across
transmit antennas is equal and the signals are independent [24,
Theorem1]. If we treated the relay node and the source node
as an antenna-clustering transmitter [7], the optimal signaling
would indicate independent signals across transmit antennas.
It is clear that the communications between the source node
and the destination node can be improved by using relaying (see,
e.g., Case III in Section IV-A). From (27) and (28), the capacity
gain for the MAC part is due to the multiple-access gain; and the
capacity gain for the BC part originates from the broadcast gain.
Needless to say, a key to reap the capacity gains is to develop
coding strategies for the cooperative MAC and the cooperative
BC therein.
A. Numerical Examples
We now illustrate via numerical examples the bounds in
Theorems 4.1 and 4.2. For the sake of clarity, we consider the
case where the numbers of antennas at all the transmitters and
receivers are equal (e.g., in ad hoc networks, all the nodes are
equipped with identical RF devices). We study the upper bound
and the lower bound with different SNR parameters (namely,
, , and ). The SNR parameters play a key role in the
upper bound and the lower bound. In what follows, we study
three cases with different SNR parameters. The number of the
antennas is assumed to be two in all cases, and SNR ,
with SNR being the SNR for the direct link.
Case I: In this case, ; this models the scenario
where the source node, the relay node, and the destination node
are separated by equal distances. Fig. 3 depicts the upper bound
and the lower bound.
Case II: In this case, and , which “cap-
tures” that the relay node is closer to the destination node than
to the source node. Comparing Fig. 4 with Fig. 3, we observe
that the upper bound and the lower bound for Case I and Case II
are the same. We will elaborate further on this in Section V (see
Lemma 5.3).
Case III: In this case, and , which “cap-
tures” a scenario that the relay node is closer to the source node
than to the destination node. Surprisingly, as shown in Fig. 5,
the upper bound and the lower bound “converge.” That is to say,
the ergodic capacity of the MIMO relay channel over Rayleigh
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9. WANG et al.: ON THE CAPACITY OF MIMO RELAY CHANNELS 37
Fig. 4. Capacity bounds versus SNR for the case = and = 10 .
Fig. 5. Capacity bounds versus SNR for the case = and = 10 .
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10. 38 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 51, NO. 1, JANUARY 2005
fading can be characterized under this SNR condition. We will
discuss in Section V sufficient conditions under which the er-
godic capacity can be achieved.
V. DISCUSSIONS ON CAPACITY ACHIEVABILITY
The Gaussian MIMO relay channel with fixed channel
gains can be viewed as a vector generalization of the classical
Gaussian relay channel in [4], and is not degraded in general.
Characterizing the corresponding capacity remains open. In
the following, we turn our attention to the fading case. Specif-
ically, we investigate in Section V-A sufficient conditions that
give exact characterization of the ergodic capacity. Since the
ergodic capacity involves expectations with respect to random
matrices and does not admit an “explicit” expression, we study
in Section V-B the high-SNR regime and use approximations
to identify SNR conditions for achieving the capacity; in
Section V-C, we examine the scale case, for which we derive
explicit conditions for capacity achievability and the explicit
capacity expression.
A. Regularity Conditions for Capacity Achievability
In Section IV, we have presented a lower bound and an upper
bound on the ergodic capacity of the MIMO relay channel and
also provided numerical examples for different SNR cases. In-
terestingly, the upper bound and the lower bound in Fig. 5 “con-
verge,” which indicates that under certain regularity conditions,
the ergodic capacity of the MIMO relay channel can be charac-
terized exactly. Indeed, we observe that in (26) and (35), there is
a common term . If is smaller than both and , the
ergodic capacity of the MIMO relay channel is given by . We
state this important observation in the following proposition.
Proposition 5.1: If and , then the
ergodic capacity of the MIMO relay channel is given by .
In what follows, we study the conditions in Proposition 5.1
in terms of SNR parameters. For tractability, we assume that all
the numbers of antennas are equal, i.e.,
(for simplicity, we use to denote the number of the antennas).
We first need the following lemma.
Lemma 5.1: The upper bound on the ergodic capacity of the
MIMO relay channel is , if .
Proof: Under the assumption on equal numbers of
antennas, it follows that and have identical
probability distributions, for . Therefore,
The second equality follows the fact that , ,
and are i.i.d. Wishart matrices, and accordingly
and follow identical prob-
ability laws. Furthermore, since increases monotonically
with , we have that if .
Lemma 5.1 gives the conditions under which the upper bound
is . It remains to examine when would meet the lower
bound, that is, (it is easy to show that is always
greater than ), and thus, the ergodic capacity can be charac-
terized. In general, it is nontrivial to determine in terms of ,
, and if (except the scalar case), because the
ergodic capacity expressions involve expectations with respect
to random matrices. In light of this fact, we first find an upper
bound on and compare it with . The following lemma
provides an upper bound on .
Lemma 5.2: For any and
Proof: First, we rewrite as
Along the same line of the proof in [24, Theorem 1], it can
be shown that if the total power is kept constant, i.i.d. input
signals with the equal power allocation can maximize the mutual
information. It then follows that
It is clear that the equality can be achieved if .
In Section V-B, we will derive sufficient conditions for
capacity achievability by combining Proposition 5.1 with
Lemmas 5.1 and 5.2, building on which we elaborate further
on the numerical results exhibited in Case III in Section IV-A.
Next, we present in Lemma 5.3 the conditions under which
the upper bound and the lower bound diverge. This sheds light
on the existence of the gap between the upper bound and the
lower bound in Figs. 3 and 4.
Lemma 5.3: If and , then the upper bound
on the ergodic capacity of the MIMO relay channel is , and
the lower bound is .
Proof: The first statement directly follows Lemma 5.1,
and it remains to show the second one. We have that
where follows from the fact that with proba-
bility [9, Theorem 3.2]; and follows from the facts that
, and and are i.i.d. random matrices, as
mentioned earlier.
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11. WANG et al.: ON THE CAPACITY OF MIMO RELAY CHANNELS 39
Fig. 6. Capacity bounds versus SNR for the case of = and = 3 .
Next, we examine two cases where the capacity-achieving
conditions can be expressed in explicit form.
B. Achievability of Ergodic Capacity: The High SNR Regime
In the high-SNR regime [19, Proposition 2], i.e., , , and
are large, can be approximated as
(41)
where is Euler’s constant. The same approxi-
mation can be applied to the upper bound on in Lemma 5.2;
i.e.,
(42)
Comparing the RHS of (41) with that of (42), we note that
if the following condition holds:
(43)
or equivalently
where (44)
Combining (44) with the conditions in Lemma 5.1, we have that
the ergodic capacity of the MIMO relay channel is .
Recall that in Section IV-A, Case III reveals a somewhat sur-
prising result that the upper bound meets the lower bound (in
Case III, and ). Based on (44) and Lemma 5.1,
it follows that if (which also implies ),
then and . That is to say, the threshold
value for this case is , at which the upper bound and the
lower bound “converge.” Accordingly, in Fig. 5, where
and , the upper bound meets the lower bound and
the ergodic capacity is achieved. To elaborate further on this,
we present two different SNR parameters (cf. Case III in Sec-
tion IV-A). As shown in Fig. 6, when , the upper bound
is very close to the lower bound. Fig. 7 shows that the upper
bound “meets” the lower bound perfectly when , in-
dicating that the capacity can be characterized exactly.
C. Achievability of Ergodic Capacity:
If all the number of the antennas is one, the MIMO relay
channel boils down to a scalar relay channel. In this case
Since has distribution with freedom of (namely,
exponential distribution), and , has
the probability density function
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12. 40 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 51, NO. 1, JANUARY 2005
Fig. 7. Capacity bounds versus SNR for the case of = and = 3:5 .
We can find by
(45)
Using the integral in [8, p. 568], we have that
(46)
where is the exponential integral function in [8, p. 875].
Next, consider the random variable .
Since , we have that
(47)
Hence, can be computed by
(48)
(49)
Combining (46) with (49), we conclude that if
(50)
and , then the ergodic capacity of the relay channel is
given by
VI. AN APPLICATION OF MIMO RELAY CHANNELS IN
COOPERATIVE COMMUNICATIONS IN AD HOC NETWORKS
In what follows, we explore the utility of the MIMO relay
channel for cooperative communications in ad hoc networks.
We consider ad hoc networks using the IEEE 802.11 CSMA/CA
standard. In such a context, the medium access control protocol
uses the RTS (request-to-send)/CTS (clear-to-send) handshake
to set up a communication link. More specifically, as shown in
Fig. 8, source node S transmits an RTS packet to request the
channel and destination node D replies with a CTS packet. If
the RTS/CTS dialogue is successful, S and D begin their data
communication, whereas all other nodes that hear either the RTS
packet or the CTS packet are kept silent for a specified duration.
A key observation is that the silent node (node R in Fig. 8
within the shaded area) can be exploited to relay information.
We use the capacity results on MIMO relay channel to charac-
terize the performance gain therein over the direct transmission
without relaying. The union of the transmission region of S and
D is the so-called RTS/CTS reserved floor; R would have been
kept silent while S communicates with D as RTS/CTS dialogue
dictates; is the distance between S and D. Note that if R lies in
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13. WANG et al.: ON THE CAPACITY OF MIMO RELAY CHANNELS 41
Fig. 8. A sketch of RTS/CTS dialogue.
the shaded area depicted in Fig. 8, it would have a shorter dis-
tance to both S and D than . Thus, during the communication
between S and D, R can function as a relay station to aid the data
transmission. Thus motivated, we call this shaded area a “relay
region,” because any silent node within such a region can act as
a relay node. Moreover, if R is equipped with multiple antennas,
S, R, and D form a MIMO relay channel.
Consider the Rayleigh-fading channel. Define the relative
gain of the capacity by using node R to relay data as
where is the relay channel capacity, and is the channel
capacity corresponding to the direct link given in Theorem 4.2.
Applying Theorems 4.1 and 4.2, we have that
(51)
Observe that and depend on the coordinates of the relay
node. Without loss of generality, let the coordinates of S, D, and
R be , , and . It follows that
and
where is the path loss parameter in wireless links; and and
are constants.
Since and change while the relay station moves,
and are functions of accordingly. Assume that R
occurs with equal probability at any position within the shaded
area (defined as ) depicted in Fig. 8. Then it follows that
where is the area of , given by ; and
, , , and are areas defined as
By using the lower bound and upper bound on the ergodic ca-
pacity of the relay channel, we have the corresponding lower
and upper bounds on average relaying gain
(52)
VII. CONCLUSION
The relay channel is a basic model for multiuser communi-
cations in wireless networks. In this paper, we first study ca-
pacity bounds for the Gaussian MIMO relay channel with fixed
channel gains. We derive an upper bound that involves convex
optimization over two covariance matrices and one scalar pa-
rameter . Loosely speaking, parameter “captures” the coop-
eration between the source node and the relay node, and leads to
solving the maximization problem using convex programming.
We give an algorithm to computer the upper bound. We also
present lower bounds on the MIMO relay channel capacity and
provide algorithms to compute the bounds.
Next, we consider the Rayleigh fading case. We give an upper
bound and a lower bound on the ergodic capacity. It is somewhat
surprising that the upper bound can meet the lower bound under
certain conditions (not necessarily degraded), indicating that the
ergodic capacity can be characterized exactly. In particular, we
identify sufficient conditions to achieve the ergodic capacity
when all nodes have the same number of antennas; and our in-
tuition for this finding is that the source node and the relay node
can function as a “virtual” transmit antenna array when the relay
node is located close to the source node, thus making it possible
to achieve the capacity. Then we study the sufficient conditions
under which the ergodic capacity can be characterized exactly.
We examine two interesting cases, namely the high-SNR regime
and the scalar relay channel case, and present the SNR condi-
tions for achieving the capacity. The capacity results we obtain
indicate independent coding schemes at the source node and
the relay node; and our intuition is that the channel uncertainty
(randomness) at transmitters results in such independence of
the codebooks. We finally discuss a potential application of the
MIMO relay channel in cooperative communications in ad hoc
networks by using the capacity results.
We are currently pursuing to generalize the study to the partial
transmitter CSI case.
APPENDIX A
PROOF OF LEMMA 3.1
Since , it follows from [11, 7.7.2] that
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14. 42 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 51, NO. 1, JANUARY 2005
is positive semidefinite. Therefore, we have that
where “ ” is in terms of positive semidefinite ordering [11].
Given , the covariance matrix of
is also positive semidefinite. It is easy to see that
In summary, we have that
Thus, by the continuity of in the vector space, there always
exists such that
or equivalently
(53)
The equality in (53) can be achieved if .
The converse of Lemma 3.1 holds by the continuity. That is
to say, for a given , there exists such that .
APPENDIX B
ANOTHER LOWER BOUND FOR THE FIXED CHANNEL CASE
Following [4], we can find another lower bound on the
capacity for the fixed channel case. By using block-Markov
coding, the following rate is achieved for any given distribution
:
(54)
Recall that the optimal distribution is Gaussian [5], [4]; and
the transmitted signal at the source node can be decomposed
as
(55)
where, for brevity, we define . Based on the
decomposition above and Lemma 3.1, the power constraints on
and are given by
and
(56)
We can choose the signal to maximize the informa-
tion rate for the source–relay link because
. Then the corresponding solution for can be
found by using the water-filling technique [23]. More specif-
ically, let the singular value decomposition (SVD) of be
Accordingly, the water-filling solution for is
given by
(57)
where is a circularly symmetric complex Gaussian vector
satisfying
(58)
with being a diagonal matrix (see [23]).
Now consider the multiple-access link from the source node
and the relay node to the destination node, i.e., .
We can view this as a MIMO channel with
transmit antennas and receive antennas. Define
. Since ,
we can choose the joint distribution to maximize
the sum information rate for the multiple-access link. To this
end, the received signal at the destination node can be written as
(59)
Let be a whitening matrix for , and
define
Let be the SVD of . Rewrite the transmitted
signal as
(60)
where is a circularly symmetric complex Gaussian vector
satisfying
(61)
with being a diagonal matrix (see [23]).
Then the sum information rate for the multiple-access link of
the MIMO relay channel is given by
(62)
This is a water-filling problem with respect to except that
each terminal has its own power constraint. Let denote the
first rows of , and the remaining rows. Then the
power constraints are as follows:
(63)
(64)
where is the nonzero eigenvalue of , and is the
nonzero eigenvalue of ; and denotes the th
element along the diagonal of .
The problem can be solved by using the Lagrange dual func-
tion
(65)
where and are Lagrange multipliers.
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15. WANG et al.: ON THE CAPACITY OF MIMO RELAY CHANNELS 43
Alternatively, we can find a suboptimal solution by first
finding the standard water-filling solution subject to a total
power constraint, following by scaling this to satisfy the indi-
vidual power constraints. That is to say, rewrite
(66)
where and satisfy
(67)
(68)
Then, we can maximize the achievable rate with respect to pa-
rameter after plugging and into (54).
ACKNOWLEDGMENT
The authors wish to thank Dr. Gerhard Kramer for [13] and
helpful comments on the proof of Theorem 4.1. They would also
like to thank the anonymous reviewers for their helpful com-
ments that greatly improved the presentation of the paper.
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