The document proposes a new Adaptive Handover Margin algorithm called AHOM-NWF that automatically adjusts the handover margin level in LTE-Advanced systems using carrier aggregation. The algorithm considers three key functions - f(SINR), f(TL), and f(v) - which are evaluated based on signal-to-interference-plus-noise ratio, traffic load, and user velocity respectively. It assigns a weight to each function to estimate an accurate margin level. Simulation results show the proposed algorithm enhances system performance like SINR, cell edge throughput, and outage probability by an average of 24.4%, 14.6%, and 17.9% respectively over other existing algorithms.
Ns 2 based simulation environment for performance evaluation of umts architec...Makhdoom Waseem Hashmi
Ns 2 based simulation environment for performance evaluation of umts architecture.
NS2, UMTS, 3G, EURANE, scheduling, architecture and umts simultation and NS2 simulation and EURANE SIMULATION
Novel Position Estimation using Differential Timing Information for Asynchron...IJCNCJournal
Positioning techniques have been a common objective since the early development of wireless networks. However, current positioning methods in cellular networks, for instance, are still primarily focused on the use of the Global Navigation Satellite System (GNSS), which has several limitations, like high power drainage and failure in indoor scenarios. This study introduces a novel approach employing standard LTE signaling in order to provide high accuracy positioning estimation. The proposed technique is designed in analogy to the human sound localization system, eliminating the need of having information from three spatially diverse Base Stations (BSs). This is inspired by the perfect human 3D sound localization with two ears. A field study is carried out in a dense urban city to verify the accuracy of the proposed technique, with more than 20 thousand measurement samples collected. The achieved positioning accuracy is meeting the latest Federal Communications Commission (FCC) requirements in the planner dimension.
Ns 2 based simulation environment for performance evaluation of umts architec...Makhdoom Waseem Hashmi
Ns 2 based simulation environment for performance evaluation of umts architecture.
NS2, UMTS, 3G, EURANE, scheduling, architecture and umts simultation and NS2 simulation and EURANE SIMULATION
Novel Position Estimation using Differential Timing Information for Asynchron...IJCNCJournal
Positioning techniques have been a common objective since the early development of wireless networks. However, current positioning methods in cellular networks, for instance, are still primarily focused on the use of the Global Navigation Satellite System (GNSS), which has several limitations, like high power drainage and failure in indoor scenarios. This study introduces a novel approach employing standard LTE signaling in order to provide high accuracy positioning estimation. The proposed technique is designed in analogy to the human sound localization system, eliminating the need of having information from three spatially diverse Base Stations (BSs). This is inspired by the perfect human 3D sound localization with two ears. A field study is carried out in a dense urban city to verify the accuracy of the proposed technique, with more than 20 thousand measurement samples collected. The achieved positioning accuracy is meeting the latest Federal Communications Commission (FCC) requirements in the planner dimension.
MAR SECURITY: IMPROVED SECURITY MECHANISM FOR EMERGENCY MESSAGES OF VANET USI...IJCNCJournal
Vehicular Ad-hoc network (VANET) is one of the emerging technologies for research community to get various research challenges to construct secured framework for autonomous vehicular communication. The prime concern of this technology is to provide efficient data communication among registered vehicle nodes. The several research ideas are implemented practically to improve overall communication in VANETs by considering security and privacy as major aspects of VANETs. Several mechanisms have been implemented using cryptography algorithms and methodologies. However, these mechanisms provide a solution only for some restricted environments and to limited security threats. Hence, the proposed novel mechanism has been introduced, implemented and tested using key management technique. It provides secured network environment for VANET and its components. Later, this mechanism provides security for data packets of emergency messages using cryptography mechanism. Hence, the proposed novel mechanism is named Group Key Management & Cryptography Schemes (GKMC). The experimental analysis shows significant improvements in the network performance to provide security and privacy for emergency messages. This GKMC mechanism will help the VANET user’s to perform secured emergency message communication in network environment.
A Novel Routing Strategy Towards Achieving Ultra-Low End-to-End Latency in 6G...IJCNCJournal
Compared to 5G, 6G networks will demand even more ambitious reduction in endto-end latency for packet communication. Recent attempts at breaking the barrier of end-to-end millisecond latencies have focused on re-engineering networks using a hybrid approach consisting of an optical-fiber based backbone network architecture coupled with high-speed wireless networks to connect end-devices to the backbone network. In our approach, a wide area network (WAN) is considered with a high-speed optical fiber grid network as its backbone. After messages from a source node enter the backbone network through a local wireless network, these are delivered very fast to an access point in the backbone network closest to the destination node, followed by its transfer to the local wireless network for delivery to the destination node. We propose a novel routing strategy which is based on distributing the messages in the network in such a way that the average queuing delay of the messages through the backbone network is minimized, and also the route discovery time at each router in the backbone network is drastically reduced. Also, multiple messages destined towards a particular destination router in the backbone network are packed together to form a mailbag, allowing further reductions in processing overheads at intermediate routers and pipelining of mailbag formation and route discovery operations in each router. The performance of the proposed approach green based on these ideas has been theoretically analyzed and then simulated using the ns-3 simulator. Our results show that the average end-to-end latency is less than 380 µs (with only 46-79 µs within the backbone network under varying traffic conditions) for a 1 KB packet size, when using a 500 Gbps optical fiber based backbone network laid over a 15 Km × 15 Km area, a 50 Mbps uplink channel from the source to the backbone network, and a 1 Gbps downlink channel from the backbone network to the destination. The significant reduction in end-to-end latency as compared to existing routing solutions clearly demonstrates the potential of our proposed routing strategy for meeting the ultra-low latency requirements of current 5G and future 6G networks, particularly for mobile edge computing (MEC) application scenarios.
Performance evaluation of 1 tbps qpsk dwdm system over isowceSAT Journals
Abstract Optical wireless communications has been in latest trends of high speed communications. They enable the use of optical wireless channel in applications like inter satellite links and underwater communications etc. In this paper, we communicate an ultra high bit rate i.e. 1 Tbps (10 x 100 Gbps) QPSK WDM System over optical Wireless communication Link. The system is a Line of Sight optical wireless link incorporating Coherent QPSK modulation Scheme for10 channels each at 100 Gbps The performance is evaluated in terms of Q-Factor and Minimum Bit Error Rate which are noticed to be in acceptable standards. The Link is analyzed under various parameters such as Power, Distance etc and maximum achievable distance is noticed to be 50,000 km at power values ranging from 0 dBm to 40 dBm
Performance evaluation of interference aware topology power and flow control ...IJECEIAES
Multi-Radio Multi-Channel Wireless Mesh Network (MRMC-WMN) has been considered as one of the key technology for the enhancement of network performance. It is used in a number of real-time applications such as disaster management system, transportation system and health care system. MRMC-WMN is a multi-hop network and allows simultaneous data transfer by using multiple radio interfaces. All the radio interfaces are typically assigned with different channels to reduce the effect of co-channel interference. In MRMC-WMN, when two nodes transmit at the same channel in the range of each other, generates co-channel interference and degrades the network throughput. Co-channel interference badly affects the capacity of each link that reduces the overall network performance. Thus, the important task of channel assignment algorithm is to reduce the co-channel interference and enhance the network performance. In this paper, the problem of channel assignment has been addressed for MRMC-WMN. We have proposed an Interference Aware, Topology, Power and Flow Control (ITPFC) Channel Assignment algorithm for MRMC-WMN. This algorithm assignes the suitable channels to nodes, which provides better link capacity and reduces the co-channel interference. In the previous work performance of the proposed algorithm has been evaluated for a network of 30 nodes. The aim of this paper is to further evaluate the performance of proposed channel assignment algorithm for 40 and 50 nodes network. The results obtained from these networks show the consistent performance in terms of throughput, delay, packet loss and number of channels used per node as compared to LACA, FCPRA and IATC Channel Assignment algorithms.
Proportional fair buffer scheduling algorithm for 5G enhanced mobile broadband IJECEIAES
The impending next generation of mobile communications denoted 5G intends to interconnect user equipment, things, vehicles, and cities. It will provide an order of magnitude improvement in performance and network efficiency, and different combinations of use cases enhanced mobile broadband (eMBB), ultra reliable low latency communications (URLLC), massive internet of things (mIoT) with new capabilities and diverse requirements. Adoption of advanced radio resource management procedures such as packet scheduling algorithms is necessary to distribute radio resources among different users efficiently. The proportional fair (PF) scheduling algorithm and its modified versions have proved to be the commonly used scheduling algorithms for their ability to provide a tradeoff between throughput and fairness. In this article, the buffer status is combined with the PF metric to suggest a new scheduling algorithm for efficient support for eMBB. The effectiveness of the proposed scheduling strategy is proved through à comprehensive experimental analysis based on the evaluation of different quality of service key performance indicators (QoS KPIs) such as throughput, fairness, and buffer status.
IOSR Journal of Applied Physics (IOSR-JAP) is an open access international journal that provides rapid publication (within a month) of articles in all areas of physics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in applied physics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Project Report Submitted in Partial Fulfillment of the Requirements for the Degree of BACHELOR OF ENGINEERING in
(COMMUNICATION)
BY
AKRM ABDULAH RASSAM (91048)
AMAL ABDULRAHMAN HAMOUD (10003)
MOHAMMED ABDULJABBAR QAID (10029)
MOHAMMED ABDUL-RAHMAN (91028)
NADA YASIN ABDULSALAM (10038)
SAMAR ABDULKAWE ALSHARAIE (10016)
SUPERVISOR
DR. REDHWAN QASEM SHADDAD
TAIZ, YEMEN
2015
An Efficient and Stable Routing Algorithm in Mobile Ad Hoc NetworkIJCNCJournal
Mobile Ad hoc Network (MANET) is mainly designed to set up communication among devices in infrastructure-less wireless communication network. Routing in this kind of communication network is highly affected by its restricted characteristics such as frequent topological changes and limited battery power. Several research works have been carried out to improve routing performance in MANET. However, the overall performance enhancement in terms of packet delivery, delay and control message overhead is still not come into the wrapping up. In order to overcome the addressed issues, an Efficient and Stable-AODV (EFST-AODV) routing scheme has been proposed which is an improvement over AODV to establish a better quality route between source and destination. In this method, we have modified the route request and route reply phase. During the route request phase, cost metric of a route is calculated on the basis of parameters such as residual energy, delay and distance. In a route reply phase, average residual energy and average delay of overall path is calculated and the data forwarding decision is taken at the source node accordingly. Simulation outcomes reveal that the proposed approach gives better results in terms of packet delivery ratio, delay, throughput, normalized routing load and control message overhead as compared to AODV.
ADAPTIVE RANDOM SPATIAL BASED CHANNEL ESTIMATION (ARSCE) FOR MILLIMETER WAVE ...IJCNCJournal
Millimeter-wave and mMIMO communications are the most essential success systems for next-generation wireless sensor networks to have enormous amounts of accessible throughput and spectrum. Through installing huge antenna arrays at the base station and performing coherent transceiver processing, mMIMO is a potential technology for enhancing the bandwidth efficiency of wireless sensor networks. The use of mmWave frequencies for mMIMO systems solves the problem of high path-loss through offering greater antenna gains. In this work, we provide a design with a random spatial sample structure that incorporates a totally random step before the analogue is received. It contains a totally random step before the analogue received signals are sent into the digital component of the HBF receiver. Adaptive random spatial based channel estimation (ARSCE) is proposed for channel session measurement collection, and an analogue combiner with valves has been used to estimate the signals at each receiving antenna. The proposed optimization problem formulation attempts to discover the orientations and gains of wideband channel routes. In addition, our proposed model has compared to various state-of-art techniques while considering error minimization.
A Cluster-Based Routing Protocol and Fault Detection for Wireless Sensor NetworkIJCNCJournal
In Wireless Sensors Networks (WSN) based application, a large number of sensor devices must be deployed. Energy efficiency and network lifetime are the two most challenging issues in WSN. As a consequence, the main goal is to reduce the overall energy consumption using clustering protocols which have to ensure reliability and connectivity in large-scale WSN. This work presents a new clustering and routing algorithm based on the properties of the sensor networks. The main goal of this work is to extend the network lifetime via charge equilibration in the WSN. According to many errors with sensing devices and to have greater data accuracy, we use a quorum mechanism. The proposed algorithms are evaluated widely and the results are compared with related works. The experimental results show that the proposed algorithm provides an effective improvement in terms of energy consumption, data accuracy and network lifetime.
5G Coupler Design for Intelligent Transportation System (ITS) Application IJECEIAES
Aiming to achieve 3-dB coupling, operating in fifth generation (5G) technologies, this paper introduces a new design of tight coupling coupler that will be operated in 5G technologies. Two stubs and two slots have been implemented into the 3-dB coupler design in order to achieve impedance matching between the ports and to give better coupling performances, respectively. Moreover, a study on the stubs’ and slots’ effects towards the S31 of the 3-dB coupler has also been presented in this paper. The proposed coupler is designed on Rogers RO4003C substrate. The simulation results and the analytical study on the stubs and slots implementation show that both stubs and slots affect the performance of the coupling coefficient.
Bit Error Rate Analysis in WiMAX Communication at Vehicular Speeds using mod...IJMER
At high vehicular speeds, rapid changes in surrounding environments, cause severe fading at
the receiver, resulting a drastic fall in throughput and unless any proactive measure is taken to combat
this problem, throughput becomes insufficient to support many applications, particularly those with
multimedia contents. Bit Error Rate (BER) estimation is an integral part of any proactive measure and
recent studies suggest that Nakagami-m model performs better for modelling channel fading in wireless
communications at high vehicular speeds. No work has been reported in literature that estimates BER
at high vehicular speeds in WiMAX communication using Nakagami-m model. In this thesis, we develop
and present an analytical model to estimate BER in WiMAX at vehicular speeds using Nakagami-m
fading model. The proposed model is adaptive and can be used with resource management schemes
designed for fixed, nomadic, and mobile WiMAX communications.
MPR selection to the OLSR quality of service in MANET using minmax algorithmIJECEIAES
Optimized link state routing (OLSR) is a routing protocol that has a small delay, low traffic control, support the application of denser networks, and adopts the concept of multipoint relays (MPR). The problem of OLSR is routing table updating which continually causes excessive packet delivery, and energy consumption becomes increased. This article proposes the improvement of OLSR performance using the min-max algorithm based on the quality of service (QoS) with considering the density of the node. The Min-max algorithm works in selecting MPR nodes based on the largest signal range. The QoS parameters analyzed with a different number of nodes are packet delivery ratio (PDR), throughput, delay, energy consumption, and topology control (TC). Simulation result of network simulator version 2 (NS-2) shows that OLSR performance using the min-max algorithm can increase PDR of 91.17%, packet loss of 60.77% and reduce topology control packet of 8.07%, energy consumption of 16.82% compared with standard OLSR.
MOBILITY LOAD BALANCING BASED ADAPTIVE HANDOVER IN DOWNLINK LTE SELF-ORGANIZI...ijwmn
This article investigates mobility load balancing (MLB) algorithm implementation through network
simulator (ns-3) in long term evolution (LTE) systems employing orthogonal frequency division multiple
access (OFDMA) for downlink (DL) data transmission. MLB is introduced by the third generation
partnership project (3GPP) as a key target of LTE self-organizing networks (SONs) [1]. Our contribution
is twofold. First, we implemented elementary procedures (EPs) related to load management (LM) function
of the X2-application protocol (X2AP) as specified in TS 136.423 [2]. We particularly focused on EPs
’Resource Status Reporting Initiation Procedure’ and 'Resource Status Reporting Procedure’. Second, we
implemented a MLB based adaptive handover (HO) algorithm enabling to configure adaptively HO
hysteresis threshold for each neighbouring cell, of an overloaded cell, according to its current load
information. Numerical results show how, through suitable simulation scenarios, MLB enables enhancing
network performance in terms of overall throughput, packet loss ratio (PLR) and fairness without incurring
HO overhead.
MAR SECURITY: IMPROVED SECURITY MECHANISM FOR EMERGENCY MESSAGES OF VANET USI...IJCNCJournal
Vehicular Ad-hoc network (VANET) is one of the emerging technologies for research community to get various research challenges to construct secured framework for autonomous vehicular communication. The prime concern of this technology is to provide efficient data communication among registered vehicle nodes. The several research ideas are implemented practically to improve overall communication in VANETs by considering security and privacy as major aspects of VANETs. Several mechanisms have been implemented using cryptography algorithms and methodologies. However, these mechanisms provide a solution only for some restricted environments and to limited security threats. Hence, the proposed novel mechanism has been introduced, implemented and tested using key management technique. It provides secured network environment for VANET and its components. Later, this mechanism provides security for data packets of emergency messages using cryptography mechanism. Hence, the proposed novel mechanism is named Group Key Management & Cryptography Schemes (GKMC). The experimental analysis shows significant improvements in the network performance to provide security and privacy for emergency messages. This GKMC mechanism will help the VANET user’s to perform secured emergency message communication in network environment.
A Novel Routing Strategy Towards Achieving Ultra-Low End-to-End Latency in 6G...IJCNCJournal
Compared to 5G, 6G networks will demand even more ambitious reduction in endto-end latency for packet communication. Recent attempts at breaking the barrier of end-to-end millisecond latencies have focused on re-engineering networks using a hybrid approach consisting of an optical-fiber based backbone network architecture coupled with high-speed wireless networks to connect end-devices to the backbone network. In our approach, a wide area network (WAN) is considered with a high-speed optical fiber grid network as its backbone. After messages from a source node enter the backbone network through a local wireless network, these are delivered very fast to an access point in the backbone network closest to the destination node, followed by its transfer to the local wireless network for delivery to the destination node. We propose a novel routing strategy which is based on distributing the messages in the network in such a way that the average queuing delay of the messages through the backbone network is minimized, and also the route discovery time at each router in the backbone network is drastically reduced. Also, multiple messages destined towards a particular destination router in the backbone network are packed together to form a mailbag, allowing further reductions in processing overheads at intermediate routers and pipelining of mailbag formation and route discovery operations in each router. The performance of the proposed approach green based on these ideas has been theoretically analyzed and then simulated using the ns-3 simulator. Our results show that the average end-to-end latency is less than 380 µs (with only 46-79 µs within the backbone network under varying traffic conditions) for a 1 KB packet size, when using a 500 Gbps optical fiber based backbone network laid over a 15 Km × 15 Km area, a 50 Mbps uplink channel from the source to the backbone network, and a 1 Gbps downlink channel from the backbone network to the destination. The significant reduction in end-to-end latency as compared to existing routing solutions clearly demonstrates the potential of our proposed routing strategy for meeting the ultra-low latency requirements of current 5G and future 6G networks, particularly for mobile edge computing (MEC) application scenarios.
Performance evaluation of 1 tbps qpsk dwdm system over isowceSAT Journals
Abstract Optical wireless communications has been in latest trends of high speed communications. They enable the use of optical wireless channel in applications like inter satellite links and underwater communications etc. In this paper, we communicate an ultra high bit rate i.e. 1 Tbps (10 x 100 Gbps) QPSK WDM System over optical Wireless communication Link. The system is a Line of Sight optical wireless link incorporating Coherent QPSK modulation Scheme for10 channels each at 100 Gbps The performance is evaluated in terms of Q-Factor and Minimum Bit Error Rate which are noticed to be in acceptable standards. The Link is analyzed under various parameters such as Power, Distance etc and maximum achievable distance is noticed to be 50,000 km at power values ranging from 0 dBm to 40 dBm
Performance evaluation of interference aware topology power and flow control ...IJECEIAES
Multi-Radio Multi-Channel Wireless Mesh Network (MRMC-WMN) has been considered as one of the key technology for the enhancement of network performance. It is used in a number of real-time applications such as disaster management system, transportation system and health care system. MRMC-WMN is a multi-hop network and allows simultaneous data transfer by using multiple radio interfaces. All the radio interfaces are typically assigned with different channels to reduce the effect of co-channel interference. In MRMC-WMN, when two nodes transmit at the same channel in the range of each other, generates co-channel interference and degrades the network throughput. Co-channel interference badly affects the capacity of each link that reduces the overall network performance. Thus, the important task of channel assignment algorithm is to reduce the co-channel interference and enhance the network performance. In this paper, the problem of channel assignment has been addressed for MRMC-WMN. We have proposed an Interference Aware, Topology, Power and Flow Control (ITPFC) Channel Assignment algorithm for MRMC-WMN. This algorithm assignes the suitable channels to nodes, which provides better link capacity and reduces the co-channel interference. In the previous work performance of the proposed algorithm has been evaluated for a network of 30 nodes. The aim of this paper is to further evaluate the performance of proposed channel assignment algorithm for 40 and 50 nodes network. The results obtained from these networks show the consistent performance in terms of throughput, delay, packet loss and number of channels used per node as compared to LACA, FCPRA and IATC Channel Assignment algorithms.
Proportional fair buffer scheduling algorithm for 5G enhanced mobile broadband IJECEIAES
The impending next generation of mobile communications denoted 5G intends to interconnect user equipment, things, vehicles, and cities. It will provide an order of magnitude improvement in performance and network efficiency, and different combinations of use cases enhanced mobile broadband (eMBB), ultra reliable low latency communications (URLLC), massive internet of things (mIoT) with new capabilities and diverse requirements. Adoption of advanced radio resource management procedures such as packet scheduling algorithms is necessary to distribute radio resources among different users efficiently. The proportional fair (PF) scheduling algorithm and its modified versions have proved to be the commonly used scheduling algorithms for their ability to provide a tradeoff between throughput and fairness. In this article, the buffer status is combined with the PF metric to suggest a new scheduling algorithm for efficient support for eMBB. The effectiveness of the proposed scheduling strategy is proved through à comprehensive experimental analysis based on the evaluation of different quality of service key performance indicators (QoS KPIs) such as throughput, fairness, and buffer status.
IOSR Journal of Applied Physics (IOSR-JAP) is an open access international journal that provides rapid publication (within a month) of articles in all areas of physics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in applied physics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Project Report Submitted in Partial Fulfillment of the Requirements for the Degree of BACHELOR OF ENGINEERING in
(COMMUNICATION)
BY
AKRM ABDULAH RASSAM (91048)
AMAL ABDULRAHMAN HAMOUD (10003)
MOHAMMED ABDULJABBAR QAID (10029)
MOHAMMED ABDUL-RAHMAN (91028)
NADA YASIN ABDULSALAM (10038)
SAMAR ABDULKAWE ALSHARAIE (10016)
SUPERVISOR
DR. REDHWAN QASEM SHADDAD
TAIZ, YEMEN
2015
An Efficient and Stable Routing Algorithm in Mobile Ad Hoc NetworkIJCNCJournal
Mobile Ad hoc Network (MANET) is mainly designed to set up communication among devices in infrastructure-less wireless communication network. Routing in this kind of communication network is highly affected by its restricted characteristics such as frequent topological changes and limited battery power. Several research works have been carried out to improve routing performance in MANET. However, the overall performance enhancement in terms of packet delivery, delay and control message overhead is still not come into the wrapping up. In order to overcome the addressed issues, an Efficient and Stable-AODV (EFST-AODV) routing scheme has been proposed which is an improvement over AODV to establish a better quality route between source and destination. In this method, we have modified the route request and route reply phase. During the route request phase, cost metric of a route is calculated on the basis of parameters such as residual energy, delay and distance. In a route reply phase, average residual energy and average delay of overall path is calculated and the data forwarding decision is taken at the source node accordingly. Simulation outcomes reveal that the proposed approach gives better results in terms of packet delivery ratio, delay, throughput, normalized routing load and control message overhead as compared to AODV.
ADAPTIVE RANDOM SPATIAL BASED CHANNEL ESTIMATION (ARSCE) FOR MILLIMETER WAVE ...IJCNCJournal
Millimeter-wave and mMIMO communications are the most essential success systems for next-generation wireless sensor networks to have enormous amounts of accessible throughput and spectrum. Through installing huge antenna arrays at the base station and performing coherent transceiver processing, mMIMO is a potential technology for enhancing the bandwidth efficiency of wireless sensor networks. The use of mmWave frequencies for mMIMO systems solves the problem of high path-loss through offering greater antenna gains. In this work, we provide a design with a random spatial sample structure that incorporates a totally random step before the analogue is received. It contains a totally random step before the analogue received signals are sent into the digital component of the HBF receiver. Adaptive random spatial based channel estimation (ARSCE) is proposed for channel session measurement collection, and an analogue combiner with valves has been used to estimate the signals at each receiving antenna. The proposed optimization problem formulation attempts to discover the orientations and gains of wideband channel routes. In addition, our proposed model has compared to various state-of-art techniques while considering error minimization.
A Cluster-Based Routing Protocol and Fault Detection for Wireless Sensor NetworkIJCNCJournal
In Wireless Sensors Networks (WSN) based application, a large number of sensor devices must be deployed. Energy efficiency and network lifetime are the two most challenging issues in WSN. As a consequence, the main goal is to reduce the overall energy consumption using clustering protocols which have to ensure reliability and connectivity in large-scale WSN. This work presents a new clustering and routing algorithm based on the properties of the sensor networks. The main goal of this work is to extend the network lifetime via charge equilibration in the WSN. According to many errors with sensing devices and to have greater data accuracy, we use a quorum mechanism. The proposed algorithms are evaluated widely and the results are compared with related works. The experimental results show that the proposed algorithm provides an effective improvement in terms of energy consumption, data accuracy and network lifetime.
5G Coupler Design for Intelligent Transportation System (ITS) Application IJECEIAES
Aiming to achieve 3-dB coupling, operating in fifth generation (5G) technologies, this paper introduces a new design of tight coupling coupler that will be operated in 5G technologies. Two stubs and two slots have been implemented into the 3-dB coupler design in order to achieve impedance matching between the ports and to give better coupling performances, respectively. Moreover, a study on the stubs’ and slots’ effects towards the S31 of the 3-dB coupler has also been presented in this paper. The proposed coupler is designed on Rogers RO4003C substrate. The simulation results and the analytical study on the stubs and slots implementation show that both stubs and slots affect the performance of the coupling coefficient.
Bit Error Rate Analysis in WiMAX Communication at Vehicular Speeds using mod...IJMER
At high vehicular speeds, rapid changes in surrounding environments, cause severe fading at
the receiver, resulting a drastic fall in throughput and unless any proactive measure is taken to combat
this problem, throughput becomes insufficient to support many applications, particularly those with
multimedia contents. Bit Error Rate (BER) estimation is an integral part of any proactive measure and
recent studies suggest that Nakagami-m model performs better for modelling channel fading in wireless
communications at high vehicular speeds. No work has been reported in literature that estimates BER
at high vehicular speeds in WiMAX communication using Nakagami-m model. In this thesis, we develop
and present an analytical model to estimate BER in WiMAX at vehicular speeds using Nakagami-m
fading model. The proposed model is adaptive and can be used with resource management schemes
designed for fixed, nomadic, and mobile WiMAX communications.
MPR selection to the OLSR quality of service in MANET using minmax algorithmIJECEIAES
Optimized link state routing (OLSR) is a routing protocol that has a small delay, low traffic control, support the application of denser networks, and adopts the concept of multipoint relays (MPR). The problem of OLSR is routing table updating which continually causes excessive packet delivery, and energy consumption becomes increased. This article proposes the improvement of OLSR performance using the min-max algorithm based on the quality of service (QoS) with considering the density of the node. The Min-max algorithm works in selecting MPR nodes based on the largest signal range. The QoS parameters analyzed with a different number of nodes are packet delivery ratio (PDR), throughput, delay, energy consumption, and topology control (TC). Simulation result of network simulator version 2 (NS-2) shows that OLSR performance using the min-max algorithm can increase PDR of 91.17%, packet loss of 60.77% and reduce topology control packet of 8.07%, energy consumption of 16.82% compared with standard OLSR.
MOBILITY LOAD BALANCING BASED ADAPTIVE HANDOVER IN DOWNLINK LTE SELF-ORGANIZI...ijwmn
This article investigates mobility load balancing (MLB) algorithm implementation through network
simulator (ns-3) in long term evolution (LTE) systems employing orthogonal frequency division multiple
access (OFDMA) for downlink (DL) data transmission. MLB is introduced by the third generation
partnership project (3GPP) as a key target of LTE self-organizing networks (SONs) [1]. Our contribution
is twofold. First, we implemented elementary procedures (EPs) related to load management (LM) function
of the X2-application protocol (X2AP) as specified in TS 136.423 [2]. We particularly focused on EPs
’Resource Status Reporting Initiation Procedure’ and 'Resource Status Reporting Procedure’. Second, we
implemented a MLB based adaptive handover (HO) algorithm enabling to configure adaptively HO
hysteresis threshold for each neighbouring cell, of an overloaded cell, according to its current load
information. Numerical results show how, through suitable simulation scenarios, MLB enables enhancing
network performance in terms of overall throughput, packet loss ratio (PLR) and fairness without incurring
HO overhead.
MOBILITY LOAD BALANCING BASED ADAPTIVE HANDOVER IN DOWNLINK LTE SELF-ORGANIZI...ijwmn
This article investigates mobility load balancing (MLB) algorithm implementation through network
simulator (ns-3) in long term evolution (LTE) systems employing orthogonal frequency division multiple
access (OFDMA) for downlink (DL) data transmission. MLB is introduced by the third generation
partnership project (3GPP) as a key target of LTE self-organizing networks (SONs) [1]. Our contribution
is twofold. First, we implemented elementary procedures (EPs) related to load management (LM) function
of the X2-application protocol (X2AP) as specified in TS 136.423 [2]. We particularly focused on EPs
’Resource Status Reporting Initiation Procedure’ and 'Resource Status Reporting Procedure’. Second, we
implemented a MLB based adaptive handover (HO) algorithm enabling to configure adaptively HO
hysteresis threshold for each neighbouring cell, of an overloaded cell, according to its current load
information. Numerical results show how, through suitable simulation scenarios, MLB enables enhancing
network performance in terms of overall throughput, packet loss ratio (PLR) and fairness without incurring
HO overhead.
MECC scheduling algorithm in vehicular environment for uplink transmission in...IJECEIAES
Single Carrier Frequency Division Multiple Access (SC-FDMA) is chosen because of the lower peak-to-average power ratio (PAPR) value in uplink transmission. However, the contiguity constraint is one of the major constraint presents in uplink packet scheduling, where all RBs allocated to a single UE must be contiguous in the frequency-domain within each time slot to maintain its single carrier. This paper proposed an uplink-scheduling algorithm namely the Maximum Expansion with Contiguity Constraints (MECC) algorithm, which supports both the RT and NRT services. The MECC algorithm is deployed in two stages. In the first stage, the RBs are allocated fairly among the UEs. The second stage allocates the RBs with the highest metric value and expands the allocation on both sides of the matrix, M with respect to the contiguity constraint. The performance of the MECC algorithm was observed in terms of throughput, fairness, delay, and Packet Loss Ratio (PLR) for VoIP, video and best effort flows. The MECC scheduling algorithm is compared to other algorithms namely the Round Robin (RR), Channel-Dependent First Maximum Expansion (CD-FME), and Proportional Fairness First Maximum Expansion (PF-FME). From here, it can be concluded that the MECC algorithm shows the best results among other algorithms by delivering the highest throughput which is up to 81.29% and 90.04% than CD-FME and RR scheduler for RT and NRT traffic respectively, having low PLR and delay which is up to 93.92% and 56.22% of improvement than CD-FME for the RT traffic flow. The MECC also has a satisfactory level of fairness for the cell-edge users in a vehicular environment of LTE network.
ADAPTIVE HANDOVER HYSTERESIS AND CALL ADMISSION CONTROL FOR MOBILE RELAY NODESIJCNCJournal
The aim of equipping a wireless network with a mobile relay node is to support broadband wireless communications for vehicular users and their devices. The high mobility of vehicular users, possibly at a very high velocity in the area in which two cells overlap, could cause the network to suffer from a reduced handover success rate and, hence, increased radio link failure. The combined impact of these problems is service interruptions to vehicular users. Thus, the handover schemes are crucial in solving these problems. In this work, we first present the adaptive handover hysteresis scheme for the wireless network with mobile relay nodes in the high-speed train scenario. Specifically, our proposed adaptive hysteresis scheme is based on the velocity of the train. Second, the handover call dropping probability is reduced by introducing a modified call admission control scheme to support radio resource reservation for handover calls that prioritizes handover calls of mobile relay over the other calls. The proposed solution in which adaptive parameter is combined with call admission control is evaluated by system level simulation. Our simulation results illustrate an increased handover success rate and reduced radio link failures.
Traffic offloading impact on the performanceIJCNCJournal
Long Term Evolution (LTE) is defined by the Third Generation Partnership Project (3GPP) standards as
Release 8/9. The LTE supports at max 20 MHz channel bandwidth for a carrier. The number of LTE users
and their applications are increasing, which increases the demand on the system BW. A new feature of the
LTE-Advanced (LTE-A) which is defined in the 3GPP standards as Release 10/11 is called Carrier Aggregation (CA), this feature allows the network to aggregate more carriers in-order to provide a higher bandwidth. Carrier Aggregation has three main cases: Intra-band contiguous, Intra-band non-contiguous, Inter-band contiguous. In addition to the Carrier Aggregation feature, LTE-A supports Heterogeneous Networks (HetNets). HetNets consists of a mix of macro-cells, remote radio heads, and low power nodes such as pico-cells, and femto-cells. HetNets allow cellular network operators to support higher data traffic
by offloading it to a smaller cells such as femto-cells. The aim of this paper is to evaluate the Quality of Service (QoS) performance of the Modified Largest Weighted Delay First (MLWDF), the Exponential Rule (Exp-Rule), and the Logarithmic Rule (Log-Rule) scheduling algorithms while offloading 50% of the macro-cell's traffic to five femto-cells, 100% of the macro-cell's traffic to five femto-cells, 100% of the macro-cell's traffic to ten femto-cells, and to compare it with the case in-which traffic offloading is not
applied. The QoS performance evaluation is based on the system's average throughput, Packet Loss Rate (PLR), average packet delay, and fairness among users. The LTE-Sim-5 with modifications is used in the simulation process. Simulation results show that offloading 100% of the Macro-cell's traffic to five femtocells had the highest maximum throughput, and the best PLR values especially when using the Log-Rule, in-which using it maintained the PLR values around 0.15 despite increasing the number of users. The least average packet delay was achieved when offloading 100% of the Macro-cell's traffic to ten femto-cells, the delay dropped to below 5 ms. The fairness indicators for the three scheduling algorithms while traffic
offloading was applied fluctuated in a linear way between a range of values of 0.7 and 0.9.
Call Admission Control Scheme With Multimedia Scheduling Service in WiMAX Net...Waqas Tariq
WiMAX network introduces a multimedia data scheduling service with different quality of service (QoS) requirements. Transmission opportunities are scheduled by the service according to the types of traffic data for the different connections or users. In the paper, we first propose a uniform definition of QoS level for the multimedia data types in the service. The QoS level of a connection are determined by the type of data of the connection and its allocated resources. Based on these QoS levels, we propose a call admission control (CAC) scheme for the entry admission of a new connection without degrading the network performance and the QoS of ongoing connections. The key idea of this scheme is to regulate the arriving traffic of the network such that the network can work at an optimal point, given under a heavy load traffic. Taking advantage of the simulation experiments, we confirm the fact that the proposed scheme can achieve better trade-off between the overall performance of network system and the QoS level of individual connection.
3GPP has introduced LTE Femtocells to manipulate the traffic for indoor users and to minimize
the charge on the Macro cells. A key mechanism in the LTE traffic handling is the packet
scheduler which is in charge of allocating resources to active flows in both the frequency and
time dimension. So several scheduling algorithms need to be analyzed for femtocells networks.
In this paper we introduce a performance analysis of three distinct scheduling algorithms of
mixed type of traffic flows in LTE femtocells networks. The particularly study is evaluated in
terms of throughput, packet loss ratio, fairness index and spectral efficiency.
PERFORMANCE ANALYSIS OF RESOURCE SCHEDULING IN LTE FEMTOCELLS NETWORKScscpconf
3GPP has introduced LTE Femtocells to manipulate the traffic for indoor users and to minimize the charge on the Macro cells. A key mechanism in the LTE traffic handling is the packet
scheduler which is in charge of allocating resources to active flows in both the frequency and time dimension. So several scheduling algorithms need to be analyzed for femtocells networks. In this paper we introduce a performance analysis of three distinct scheduling algorithms of mixed type of traffic flows in LTE femtocells networks. The particularly study is evaluated in terms of throughput, packet loss ratio, fairness index and spectral efficiency.
Performance evaluation of bandwidth optimization algorithm (boa) in atm networkEditor Jacotech
domains: none of them are suitable, alone, for the wide range of traffic services expected in ATM-based networks. Therefore, some integration of these basic schemes should be considered. In this paper, we propose a new traffic control algorithm, called the Bandwidth optimization Algorithm (BOA). BOA is a multi-level control algorithm that attempts to optimally manage network resources and perform traffic control among a wide range of traffic services in ATM-based networks. The basic objective of BOA is to meet the quality of service requirements for different traffic sources, while making the best possible use of network bandwidth. In addition. BOA attempts to minimize network congestion in a preventive way.
HANDOVER NECESSITY ESTIMATION FOR 4G HETEROGENEOUS NETWORKSijistjournal
One of the most challenges of 4G network is to have a unified network of heterogeneous wireless networks. To achieve seamless mobility in such a diverse environment, vertical hand off is still a challenging problem. In many situations handover failures and unnecessary handoffs are triggered causing degradation of services, reduction in throughput and increase the blocking probability and packet loss. In this paper a new vertical handoff decision algorithm handover necessity estimation (HNE), is proposed to minimize the number of handover failure and unnecessary handover in heterogeneous wireless networks. we have proposed a multi criteria vertical handoff decision algorithm based on two parts: traveling time estimation and time threshold calculation. Our proposed methods are compared against two other methods: (a) the fixed RSS threshold based method, in which handovers between the cellular network and the WLAN are initiated when the RSS from the WLAN reaches a fixed threshold, and (b) the hysteresis based method, in which a hysteresis is introduced to prevent the ping-pong effect. Simulation results show that, this method reduced the number of handover failures and unnecessary handovers up to 80% and 70%, respectively.
HANDOVER NECESSITY ESTIMATION FOR 4G HETEROGENEOUS NETWORKSijistjournal
One of the most challenges of 4G network is to have a unified network of heterogeneous wireless networks. To achieve seamless mobility in such a diverse environment, vertical hand off is still a challenging problem. In many situations handover failures and unnecessary handoffs are triggered causing degradation of services, reduction in throughput and increase the blocking probability and packet loss. In this paper a new vertical handoff decision algorithm handover necessity estimation (HNE), is proposed to minimize the number of handover failure and unnecessary handover in heterogeneous wireless networks. we have proposed a multi criteria vertical handoff decision algorithm based on two parts: traveling time estimation and time threshold calculation. Our proposed methods are compared against two other methods: (a) the fixed RSS threshold based method, in which handovers between the cellular network and the WLAN are initiated when the RSS from the WLAN reaches a fixed threshold, and (b) the hysteresis based method, in which a hysteresis is introduced to prevent the ping-pong effect. Simulation results show that, this method reduced the number of handover failures and unnecessary handovers up to 80% and 70%, respectively.
In mobile ad hoc wireless networks (MANETs), traditional protocol like AODV performs well for low mobility of nodes but not for high node mobility. So, it becomes important to consider mobility factor during the path selection procedure of routing protocol. Here, a fuzzy logic mobility based protocol (FLM-AODV) that considers the mobility factor is proposed. Due to the consideration of mobility factor, the proposed protocol has better performance than the traditional AODV. The experiment results show that the proposed protocol has advantages of improved average end-to-end delay and packet delivery ratio (PDR) over existing AODV protocol.
Exponential MLWDF (EXP-MLWDF) Downlink Scheduling Algorithm Evaluated in LTE ...IJECEIAES
Nowadays, with the advent of smartphones, most of people started to make voice and video conference calls continuously even in a high mobility scenario, the bandwidth requirements have increased considerably, which can cause network congestion phenomena. To avoid network congestion problems and to support high mobility scenario, 3GPP has developed a new cellular standard based packet switching, termed LTE (Long Term Evolution). The purpose of this paper is to evaluate the performance of the new proposed algorithm, named Exponential Modified Largest Weighted Delay First „EXP-MLWDF‟, for high mobility scenario and with the presence of a large number of active users, in comparison with the wellknown algorithms such as a proportional fair algorithm (PF), Exponential Proportional Fairness (EXP/PF), Logarithm Rule (LOG-Rule), Exponential Rule (EXP-Rule) and Modified Largest Weighted Delay First (MLWDF). The performance evaluation is conducted in terms of system throughput, delay and PLR. Finally, it will be concluded that the proposed scheduler satisfies the quality of service (QoS) requirements of the real-time traffic in terms of packet loss ratio (PLR), average throughput and packet delay. Because of the traffic evolution, some key issues related to scheduling strategies that will be considered in the future requirements are discussed in this article.
Adaptive Handoff Initiation Scheme in Heterogeneous NetworkIDES Editor
In wireless heterogeneous network, nodes are mobile
equipment and can move freely from one area to another. A
group of users with a large range of mobility can access around
in the overall network cause high traffic. In these
heterogeneous networks, resources are shared among all users
and the amount of available resources is determined by traffic
load. The traffic load can seriously affect on quality of services
for users thus it requires efficient management in order to
improve service quality. If traffic load is concentrated in a
cell, this cell becomes the hotspot cell. There is a need to have
a proper traffic driven handoff management scheme, so that
users will automatically move from congested cell to allow
the network to dynamically self-balance. This research
proposed an approach which adopts a hard handoff scheme to
dynamically control the handoff time according to the load
status of cells. The result shows that the effect of hotspot
threshold is the most important in initiation the handoff
process. Therefore, by incorporating value of traffic load as
adaptive factors, it shows how the handoff initiation criteria
might be set in accordance with the quality of services
requested by users.
Enhancement of qos in multihop wireless networks by delivering cbr using lb a...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Enhancement of qos in multihop wireless networks by delivering cbr using lb a...eSAT Journals
Abstract One of the most complicated issues is to measuring the delay performance of end to end nodes in Multi-hop Wireless Networks. The two nodes are communicating via hopping over the multiple wireless links. The fact that is each node has to concentrate not only its own generated traffic, but also relayed one. Observing unfairness particularly for transmissions among nodes that are more than one hop Most of the existing works deals with the joint congestion control and scheduling algorithm, which does not focusing the delay performance. In turn, considering the throughput metric alone although for congestion control flows, throughput is the repeated difficult performance metric Packet delay is also important because practical congestion control protocols need to establish the timeouts for the retransmissions based on the packet delay, such parameters could significantly impact the speed of recovery when loss of packets occurred. The related issues on the delay-performance First, for long flows, the end to end delay may grow in terms of square with based on the number of hops. Second, it is difficult to control the end-to-end delay of each flows. TDMA schedules the transmissions in a fair way, in terms of throughput per connection, considering the communication requirements of the active flows of the network. It does not work properly in the multi-hop scenario, because it is generated only for single hop networks, We propose The Leaky Bucket Algorithm, in addition to joint congestion control and scheduling algorithm in multi-hop wireless networks. The proposed algorithm not only achieves the provable throughput and also considering the upper bounds of the delay of each flow. It reduces the transmission time by delivering packets at a constant bit rate even it receives the packet at a busty way. Keywords- Multi-hop wireless networks, congestion control, Performance, Delay, Flow, Throughput.
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2. I. Shayea et al.
1 3
LTE-Advanced System Release 10 to 13 (Rel.10 & Rel.13) based on two contiguous Com-
ponent Carriers (CCs).
In mobile communication systems, several HODAs have been proposed to provide
a seamless connection with good service quality. These algorithms have been proposed
based on different parameters, such as the distance [1, 2], Received Signal Strength (RSS)
[2–4], SINR [5–8] and Interference to other- Interferences-plus-Noise Ratio (IINR) [9].
The most common HODA among those are proposed is taken based on RSS quality, which
is divided into three categories [3, 10, 11]. The first category is taken based on RSS only,
which is decides to initiate the handover procedure once the target RSS become better than
the serving RSS. The second category is deisgned based on RSS with the threshold level. It
decides to initiate handover procedure once the serving RSS level fall below the threshold
level and target RSS become better than the serving RSS. The third category considered
RSS with margin level, which determines the initiation of the handover procedure once the
target RSS becomes better than the serving RSS at a marginal level. It is the most practi-
cal algorithm recently used for taking handover decision [3, 10, 12–15]. The margin level
between the serving and target RSS contributes for reducing the unnecessary handover pro-
cedure, which leads to prevent the ping-pong effect. While the ping-pong effect is a fre-
quent unnecessary handover scenario between two neighbour stations which is caused by
rapid fluctuations in the signal strength from both stations [16]. Thus, HOM is considered a
very sensitive control parameter for taking HOD, as well as a suitable HOM level contrib-
uting to an intact HOD, which in turn contributes to a reduction in throughput degradation
and outage probability.
Decreasing or increasing HOM levels lead to a noticeable effect on system perfor-
mance, both negatively and positively. In the first case, if HOM level is decreased the ping
pong effect will increase [17, 18], which leads to increase the waste of network resources
(throughput degradation) [19] and inefficient communication between the User Equip-
ment (UE) and serving network will be resulted. On the other hand, decreasing HOM leads
to reduction in the handover failure rate [20] and outage probability [17, 21], which are
required in mobile wireless systems. In the second case, if HOM level is increased the
ping pong effect will reduce [17, 18], leading to increased probability of connection stabil-
ity. Meanwhile, increasing HOM level leads to increase users’ outage probability [17, 21],
which is undesirable in mobile communication applications. Therefore, to balance the pro
and cons of varying the HOM level, AHOM Algorithm (AHOMA) has been proposed to
adapt HOM level between a minimum and maximum levels in order to select the suitable
margin level that can contribute for taking a proper HOD.
There have been several AHOM algorithms proposed based on single and multiple
parameters in a homogeneous network. AHOM algorithms based on a single parameter,
such as distance [10, 13], service type [22], velocity [23–25] and traffic load [26], adjust
the margin levels automatically based on variation of the corresponding parameter. The
estimated level can contribute for enhancing system performance compare to the fixed-
HOM level. However, the estimated level cannot be accurate, since it is estimated in per-
spective of single parameter only, while there are other influence parameters which have
not been considered, as explained in the next section. The the AHOM algorithms based on
multiple parameters such as Cost Function (AHOM-CF) [12] the margin level is automati-
cally adjusted based on multiple parameters. In this case, the estimated HOM level may
be more accurate than that is estimated based on a single parameter only. However, there
are uninfluential factors such as service type which should be ignored, and other influence
factors (i.e. distance, channel condition, noise, interferences) which should be considered.
Consequently, a new AHOM algorithm based on multiple influence parameters is needed.
3. New Weight Function for Adapting Handover Margin Level over…
1 3
Furthermore, the sensitivity of high outage probability through the users’ mobility needs
more optimal algorithm that can estimate more accurate HOM level.
In this paper, AHOM-NWF is proposed through CA operation in LTE-Advanced sys-
tem. This algorithm attempts to adjust the margin level automatically based on SINR, traf-
fic load, and UE’s velocity. A mathematical model of the proposed algorithm has been
formulated based on a multiple functions, which are evaluated as a function of SINR, traf-
fic load and UE’s velocity. Moreover, a mathematical formula for estimating the weight of
each function is modelled in this paper. However, this proposed algorithm is designed for
throughput enhancement and outage probability reduction through CA operation in LTE-
Advanced system only. It is investigated and compared to two different adaptive handover
algorithms in order to point out its achievable enhancement.
The remainder of this paper is organized as follows: Sect. 2 describes the Background
and Related Work, while Sect. 3 presents the Proposed Algorithms. System Model is
described in Sect. 4, followed by Results and Discussion in Sect. 5. Finally, Sect. 6 con-
cludes this paper.
2 Background and Related Work
In cellular mobile communication systems, handover is the main and essential Radio
Resource Management (RRM) process that is required to support reliable UE connectiv-
ity at different mobility conditions [27–30]. It always maintains the radio link connection
for the UE to the best serving cell in the coverage area. The term handover, also called as
Handoff, can be defined, in general, as the process of switching a radio link connection
from the source to the target Base Stations (BSs). Therefore, the mobile UE can maintain
its radio connection during its movement within the cells by performing a handover process
from the serving Evolved Node B (eNB) to another eNB that provides better signal qual-
ity. Furthermore, the efficient handover can support service continuity and enhancing UE’s
throughput, ideally, without any service interruption. In wireless systems, there are two
types of handover procedures which can be performed between cells, known as horizontal
and vertical handovers. In horizontal handovers, the procedure can be performed between
cells in a homogeneous network only, such as the handover procedure between two eNBs
in LTE network. In vertical handovers, the procedure can be performed between two cells
from different networks, such as the handover procedure from eNBs under LTE network
to a BS under WiMAX network. However, this paper focuses only on handover decisions
in terms of horizontal handover in a homogeneous network (LTE-Advanced System). In
horizontal handover, several studies have focused on handover decision with a fixed HOM
level [17–21] and AHOM level. Fixed handover margin level means that the margin level is
a constant through all the Transmission Time Intervals (TTIs), while AHOM level means
that the margin level is automatically adjusted periodically based on different factors as
illustrated in Fig. 1.
In [10, 13] AHOM algorithm based on Distance (AHOM-D) has been proposed, sim-
plified as follows:→ max
[
Mmax
(
d
R
)4
, Mmin
]
, where d is the distance between UE and
serving eNB, and R represents the cell radius in meter. Mmax and Mmin represent maxi-
mum and minimum handover margin levels, respectively. However, this algorithm
dynamically determines the HOM level as a function of the distance between the UE
and the serving eNB. Therefore, based on this algorithm, HOM level increases when the
4. I. Shayea et al.
1 3
UE oncoming toward the serving eNB, while it is decreased when the UE going away
from the serving eNB toward the target eNB. It is a useful algorithm when the network
resources and a good channel condition are always available with low UE’s movement
speed, but this not always be available. In such a case, AHOM-D cannot estimate the
suitable HOM level, since this algorithm considers only distance and other influencing
factors have not been considered.
In [23–25], AHOM algorithm based on user’s Velocity (AHOM-V) has been pro-
posed. The algorithm adjusts the margin level (ΔH) by utalizing the following model:
→ ΔH = r ⋅ Thdrop , where r is expressed by → r = log2(1 + v)
, in which v represents
UE’s velocity and Thdrop is the minimum RSS level that the quality of the radio link
below it become unacceptable. In this algorithm, higher margin level is estimated when
the UE speed is increased, while, a lower margin level is estimated when the UE speed is
decreased. It is a useful algorithm since it contributes for reducing the unnecessary hando-
ver procedure through the high UE’s movement speed by estimating high margin level. But
in other hand, it cannot estimate an accurate margin level since it considers UE’s velocity
only, while other influence factors have not been considered for adjusting the margin level.
In [26], AHOM algorithm has been proposed according to the Traffic Load (AHOM-
TL) of the serving and target eNBs in LTE system. The adaptive model is expressed as
a function of serving and target eNBs loads by → MH(e, k) = f(xe − xk) , where xe and xk
represent the loads of the serving and target eNBs, respectively. In this algorithm, the esti-
mated margin level is increased when the serving eNB’s load is decreased and target eNB’s
load is increased, while it is decreased when the serving eNB is overloaded and the tar-
get eNB is less-loaded. Although this algorithm contributes for balancing loads between
cells, but it estimates the margin level in perspective of traffic loads only. That leads to an
Max HO margin value
Average HO margin Value
Min HO margin Value
Qrslevmin
RSS over the Target CC
RSS over serving PCC
Factors
Received
Signal
Strength
(RSS)
Adaptive Margin Value
Fig. 1 Adaptive HO margin level in LTE-Advanced System
5. New Weight Function for Adapting Handover Margin Level over…
1 3
inaccurate estimate of margin level compared to the algorithm that consider multiple influ-
ence factors.
In [12], AHOM-CF has been proposed for adjusting the margin level in LTE Net-
work based on multiple parameters, which are the load difference between the serv-
ing and target cells, UE’s velocity, and the service type. In AHOM-CF, the HOM level
is adaptively estimated by this proposed expression: → M = Mdefault + ΔM , where,
Mdefault is the default margin level, while ΔM represent the margin level between the
serving and target eNB, which is expressed by ΔM = 𝛼.fl,v,s . 𝛼 is a factor expressed by
𝛼 = Mmax − Mdefault or 𝛼 = Mdefault − Mmin . While, fl,v,s represents the cost function,
which is simplified by the following formula:→ fl,v,s = 𝜔lNl + 𝜔vNv + 𝜔sNs . Where Nl , Nv
and Ns represent the normalized functions of the load difference between the serving and
target Cells, UE’s velocity, and the service type respectively. While, 𝜔l, 𝜔v, 𝜔s represent
the weight for the respective normalized function, where the sum of the weights must be
one (𝜔l + 𝜔v + 𝜔s = 1)
. However, these three normalized functions are the main factors
which contribute to adaptation of margin level. Although AHOM-CF considers multiple
parameters for estimating the margin level, it is not an optimal algorithm, as there are other
influencing factors which have not been considered and non-influtential factors have been
considered.
In Munoz et al. [31] proposed Fuzzy Logic Controller (FLC) algorithm to adaptively
modify the handover margin level only, while the Time-To-Trigger (TTT) interval is set
to 100 ms. The FLC adjusts the HOM level based on the average Call Drop Rate (CDR)
and Handover Ratio (HOR) per cell. Based on these ratios, the HOM level is optimized for
each cell individually, and it is restricted between 0 and 12 dB. The optimization opera-
tion is performed systematically in every Transmission Time Interval (TTI). However, the
authors have shown that, adjusting HOM levels based on FLC given a better reduction
gains in terms of call drop rate as compared to the conventional handover parameter opti-
mization algorithm.
In [32], a new handover self-optimization algorithm in LTE system based on a fuzzy
logic controller has been developed. The aim of that developed algorithm is to automati-
cally find out the suitable HOM and TTT. The presented results of the proposed algorithm
was compared with another four algorithms from the literature. The results show that the
proposed algorithm achieves some improvements in terms of handover as compared to
other algorithms.
Based on the presented studies, most of the proposed algorithms adjust the margin level
based on only a single parameter, such as distance [10, 13], service type [22], velocity [23–25],
traffic load [26], and Fuzzy Logic Controller [31, 32]. Since there are several influence factors
that can contribute for taking a proper HOD, such as the distance, channel condition, noise,
interferences, resource availability and UE’s velocity; therefore, estimating HOM margin level
in the perspective of single factor only leads to shortage for estimating a suitable level. That in
turn leads to increase the throughput degradation and outage probability. AHOM-CF consid-
ers multiple parameters for adjusting HOM level, but there are uninfluenced parameters need
to be ignored and other influence parameters to be considered. The uninfluenced parameter
such as service type can be ignored since all eNBs in LTE-Advanced network provides same
service type with same cost. Furthermore, HOD in horizontal handover is not taken based
on the service type, so it is normally taken either based on distance [1, 2], RSS [2–4], SINR
[5–8] or IINR [9]. Thus, there is no point of consideration of service type for adjusting HOM
level in a homogeneous network, while it can be considered in heterogeneous networks, as
each network can provide a different service type (i.e. Wifi provides internet, while LTE pro-
vides voice calls and broadband services) with a different cost. On the other hand, there are
6. I. Shayea et al.
1 3
influence parameters should be considered for adjusting HOM level in horizontal handover,
such as distance, channel condition, noise and interferences from the neighbours’ eNBs. These
parameters are influence factors as both the provided throughput and service continuity are
affected by them and handover decision can be taken based on one or more of these param-
eters. Furthermore, there is a lack of studies that are focused on AHOM based on multiple
factors with horizontal handover compare to vertical handover [33–37]. Adapting HOM level
based on a comprehensive algorithm considering different influence parameters is needed.
Moreover, all the AHOM algorithms in a horizontal handover [12] and vertical handover
[33–37], have not been formulated with any mathematical model for estimating the weight of
each normalize function that has been considered in their cost functions. Therefore, formulat-
ing a mathematical model for estimating the weight of each normalized function is required.
3
Proposed Adaptive HO Margin Algorithms
In this paper, a novel algorithm for adjusting margin level is proposed based on several influ-
ence factors such as distance, channel condition, noise, interferences, cell load, and user veloc-
ity. Since RSS is evaluated as a function of distance and channel condition, while SINR is
evaluated as a ratio of RSS to the interference plus noise ratio, SINR is thus as a factor which
will be suffice for estimating HOM level instead of distance, channel quality, noise and inter-
ferences. In terms of cell loads, the availability of resources at the target cell contributes for
performing successful handover. Also, it considers the traffic load for taking handover deci-
sion contribute for balancing loads between cells. That leads to enhanced user throughput and
reduced disconnection probability. It is considered an influential factor which should be taken
into account for adjusting margin level. According to the velocity, high movement speed of
users principals to increase the unnecessary handover rate [23, 24], which in turn leads to
degrade system performance. Thus, different UE’s velocities give different performance eval-
uations. Therefore, UE’s velocity needs to be considered for adjusting HOM level in order
to prevent the unnecessary handover, especially at the high movement speeds; which in turn
leads to enhanced user throughput and reduced outage probability.
Consequently, an HO algorithm is proposed to adjust the HOM level based on adaptive
function (fAHOM(SINR, TL, v))
, which automatically adjusts HOM level based on three func-
tions f(SINR), f(TL) and f(v)
, which are evaluated as functions of SINR, Traffic Load (TL)
and User’s velocity (v), respectively. The weight of each function is taken into account in order
to estimate an accurate margin level. However, the proposed function fAHOM(SINR, TL, v) can
be simplified by the following expression:
where MAvg represents the average HOM level, which is evaluated by
→ MAvg =
(
Mmax − Mmin
)
∕2 . 𝜔sinr , 𝜔TL and 𝜔v represent the weights of f(SINR) , f(TL)
and f(v) respectively. The value of these three functions is varied between {− 1} and {1},
while the weight of each function varies between {0} and {1}. The sum of all weights is
(1)
fAHOM =
⎧
⎪
⎪
⎨
⎪
⎪
⎩
MAvgx
�
𝜔sinrf(SINR) + 𝜔TLf(TL) + +𝜔vf(v)
�
if SINRT,S ≤ SINRThr
MAvgx
�
1 + 𝜔TLf(TL) + +𝜔vf(v)
� if SINRT SINRThr
SINRS ≥ SINRThr
MAvgx
�
−1 + 𝜔TLf(TL) + +𝜔vf(v)
� if SINRS SINRThr
SINRT ≥ SINRThr
⎫
⎪
⎪
⎬
⎪
⎪
⎭
7. New Weight Function for Adapting Handover Margin Level over…
1 3
equal to one. However, these functions and the weights of each function are explained in
details on the following two subsections respectively.
3.1 The Proposed Functions
3.1.1 A function based on SINR
A function of SINR represents the differences between the target and serving SINR ratios,
which may be expressed by the following formula:
where Max_SINR represents the maximum SINR that can be resulted at the UE. For sim-
plicity Max_SINR is set to 30 dB. SINRS and SINRT represent the SINR over the serving
and target CCs respectively. With the advent of CA technology in LTE-Advanced system
more than one CC can be paired to one UE simultaneously. One CC is configured as Pri-
mary Component Carrier (PCC) and one or more CCs can be configured as Secondary
Component Carriers (SCCs). So, SINRS represents the SINR over the serving PCC only,
while SINRT represents the SINR over the best selected CC among the available CCs.
Since the handover procedure can be occur between two CC in the same sector under the
same eNB to change the PCC, so the target CC can be the serving SCC. Thus, in this case
the SINRT will be the SINR over the serving SCC
(
SINRS−SCC
)
. On the other hand, if the
handover procedure is performed between two sectors under the same eNB or between two
different eNBs the target CC will be the best selected CC among the available CCs, which
can be CC1 or CC2. Thus, in this case the SINRT will be the SINR over the best selected
target CC
(
SINRbT−CC
)
. Therefore, for simplicity SINRT may be simplified by the following
expression:
where SecS and SecT represent the serving and target sectors respectively, while
eNBS and eNBT represent the serving and target eNBs respectively.
3.1.2 A function based on Traffic Loads
The function based on traffic loads is expressed by f(TL)
, which represents the differences
between the target and serving load ratio. The Target load ratio is defined as a ratio of the
occupant target eNB’s load to the maximum eNB’s traffic load capacity
(
TLmax
)
. Similarly,
serving load ratio is defined as a ratio of the occupant serving eNB’s load to the maxi-
mum eNB’s traffic load capacity
(
TLmax
)
. Thereby, the function based on traffic load ratios
(f(TL)) can be simplified by the following expression:
where TLT and TLS represent occupant target and serving traffic loads respectively.
(2)
f(SINR) =
(
SINRT
Max_SINR
)
−
(
SINRS
Max_SINR
)
=
SINRT − SINRS
Max_SINR
(3)
SINRT =
{
SINRS−SCC if eNBT = eNBS and SecT = SecS
SINRbT−CC if
(
eNBT ≠ eNBS or SecT ≠ SecS
)
}
(4)
f(TL) =
(
TLT
TLmax
)
−
(
TLS
TLmax
)
=
TLT − TLS
TLmax
8. I. Shayea et al.
1 3
3.1.3 A function based on Velocity
The function based on velocity is expressed by f(v)
, which is evaluated as a function of UE’s
movement speed v. Higher movement speeds (v) will lead to increase the f(v) maximum up
1, while the lower movement speeds lead to decrease the f(v) minimum to − 1. However, we
may simplify the function of velocity (f(v))(f(v)) using the following expression:
where vmax represents the maximum expected velocity by UE, which is assumed to be con-
stant (
vmax = 200 kmph) in this paper.
3.2 The Proposed Weight Model
In [12, 33–37] different adaptive handover algorithms have been proposed for adjusting
the handover margin level based on Weight Functions. Each weight function considers dif-
ferent normalized functions. The weight of each normalized function is considered in order
to increase the weight of the significant function to estimate an accurate margin level. The
authors did not formulate any mathematical expression to illustrate how the weight of each
normalized function is assigned. Moreover, the user velocity, eNB load and user SINR are
frequently changed. Therefore, there is a need for a mathematical model to estimate the weight
of each normalized function considered in the weight function. Because of that, in this paper
a mathematical model is formulated to meet the target, which is expressed by the following
formula:
where 𝜔n represents the weight of function n, which can be one of the functions:
SINR, TL or v . f(xn), is the corresponding function n that needs to evaluate its weight. It is
also can be one of the functions of SINR, TL or v . F is a metric’s factor, which represents
the total numbers of parameters that are considered for adapting HOM level. In this paper,
we set F = 3 because we considered only SINR, TL and v factors. f(xi) is the function of x
that corresponding to i, whereas i is varied from 1 to F. For simplicity, we define f(x1) as
f(SINR) , while f(x2) as f(TL) and f(x3) as f(v)
. For example, to evaluate the weight of
function f(SINR)
, it can be evaluated as: 𝜔SINR = 1−f(SINR)
(1−f(SINR))+(1−f(TL))+(1−f(𝜈))
.
Consequently, the HOM level may be adaptively estimated using the following expression:
4 System Model
4.1 System Layout Model
The LTE-Advanced system model is shown in Fig. 2 based on 3GPP specifications that
were introduced in [38]. The network consists of 61 macro-hexagonal cell layout models
with an inter-site-distance of 500 m for each cell. Every hexagonal cell contains one eNB
(5)
f(v) = 2log2
(
1 +
v
vmax
)
− 1
(6)
𝜔n =
1 − f
�
xn
�
∑F
i=1
�
1 − f
�
xi
��
(7)
HOM = MAvg + fAHOM(SINR, TL, v)
9. New Weight Function for Adapting Handover Margin Level over…
1 3
located at its centre and each cell divided into three sectors. Two contiguous CCs are con-
figured in each sector. Two CA Deployment Scenarios are considered, as defined by (1) CA
Deployment Scenario number one (CADS-1) as shown in Fig. 3a and (2) Coordinated Con-
tiguous—CA Deployment Scenario (CC-CADS) as shown in Fig. 3b [39–41]. In CADS-1
and CC-CADS both CCs are operating on contiguous bands with operating frequencies of
2 GHz and 2.0203 GHz for CC1 and CC2 respectively. The Frequency Reuse Factor (FRF)
is assumed to be one. In CADS-1, the antennas of both CCs are pointed toward the same
side of the hexagonal cell per Fig. 4a. The beam directions for both antennas in sectors 1,
2, and 3 are aimed with beam angles of 45°, 180° and 300°, respectively, as illustrated in
Fig. 4a. In CC-CADS, the antenna of each CC is pointed toward a different flat side of the
hexagonal cell as shown in Fig. 4b. Therefore, the main beam of each CC is directed in a
different direction. The beam directions for antenna 1 in sectors 1, 2 and 3 are aimed with
beam angles of 30°, 150° and 270°, respectively, and the beam directions for antenna 2 in
sectors 1, 2 and 3 are aimed with beam angles of 90°, 210° and 330°, respectively, as illus-
trated in Fig. 4b.
The transmitted power from the eNB over each CC is assumed to be the same. As
regards to the users, random numbers of UEs are generated and removed randomly at ran-
dom uniform positions in the serving and target cells. This random generation and removal
of UEs is intended to mimic a random generation of traffic in the simulation. The UEs’
directional movements are selected randomly with a fixed speed throughout the simulation,
which contains five different mobile speed scenarios (30, 60, 90, 120 and 140 km/h). The
mobility movement of all users is considered to occur in the first 37 cells only. Thus, when
the UE moves from the serving to the target eNBs, considering Random Waypoint Model,
it should be surrounded by six eNBs. These six eNBs are considered to be the stations that
cause the interference signals for the user. Moreover, the Adaptive Modulation and Coding
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eNB-to-UE X location [m]
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Y
location
[m]
UE
eNB
Fig. 2 LTE-Advanced system model
10. I. Shayea et al.
1 3
(AMC) scheme is considered based on the sets of Modulation Schemes (MS) and Coding
Rate (CR) that were introduced in [42, 43]. In addition, detailed models for the handover
procedure for LTE, the Radio-Link-Failure (RLF) detection, the re-establishment proce-
dure, and the Non-Access Stratum (NAS) recovery procedure are considered through the
simulation in order to achieve accuracy in the high performance evaluation. The essential
parameters that are used in this paper are listed in Table 1 based on an LTE-Advanced sys-
tem profile that was defined by 3GPP specifications in [38, 42, 43].
F1 F2
F1 F2
(a) CADS - 1
(b) CC-CADS
Fig. 3 Contiguous CA Deployment Scenarios
Sector # 1
CC1
B - Angle = 2700
CC1
B - Angle = 300
CC2
B - Angle = 900
CC1
B - Angle = 1500
CC2
B – Angle = 3300
Sector # 2
Sector # 3
Sector # 1
CC1 and CC2
Beam Angle = 450
CC1 and CC2
Beam Angle = 3000
CC1 and CC2
Beam Angle = 1800 Sector # 2
Sector # 3
CC2
B - Angle = 2200
(a) (b)
Fig. 4 Beam direction of CC1 and CC2
11. New Weight Function for Adapting Handover Margin Level over…
1 3
4.2 Handover Scenario
The advent of CA technology in LTE—Advanced system (Rel.10 to Rel.13) has increased the
number of Handover Scenarios (HO-Ss) comparable to LTE Release 8 and 9 (Rel.8 Rel.9).
However, there are five handover scenarios which may occur through the users’ mobility in the
CA environment, as illustrated in Fig. 5. In more detail, these scenarios can be explained by:
(1) HO between CCs at the same sector and same eNB (2) HO between sectors at same eNB,
while the target and serving CCs are operating on the same frequencies, (3) HO between sec-
tors at same eNB, while the target and serving CCs are differentiated from each other, (4) HO
between eNBs, while the serving and target CCs are operating on the same frequencies and (5)
HO between eNBs, while the serving and target CCs are differentiated from each other. All
these handover scenarios are considered in these papers.
The handover decision is taken based on serving and target RSRPs qualities. Once the tar-
get RSRP becomes greater than the serving RSRP by the HOM level during the trigger period
of time (Time-To-Trigger (TTT)), the serving eNB performes a true handover decision and
sends the handover request message to the target eNB. Thus, the considered handover decision
in this paper can be expressed by the following:
(8)
RSRPT ≥
(
RSRPS + HOM
)
Table 1 Simulation parameters
Parameter Assumption
Cellular layout Hexagonal grid, 61 cell sites, 3 sectors
per cell site, 2 CCs per sector
Minimum distance between UE and eNB ≥ 35 m
Total eNB TX power 46 dBm per CC
Shadowing standard deviation 8 dB
White noise power density (Nt) − 174 dBm/Hz
eNBs noise figure 5 dB
Thermal noise power NP = Nt + 10 log (BW × 106) dB
UE noise figure 9 dB
Operation carrier bandwidth 20 MHz for each, carrier PCC and SCC
Total system bandwidth 40 MHz (2CCs × 20 MHz)
Number of PRB/CC 100 PRB/CC
Number subcarriers/RB 12 Subcarriers per RB
Number of OFDM symbols per subframe 7
Sub-carrier spacing 15 kHz
Resource block bandwidth 180 kHz
Q_rxlevmin − 101.5 dB
Measurement Interval 50 ms for PCC and SCC
Time-to-Trigger (TTT) 300 ms
Max HO margin 6 dB
Each X2-interface delay 10 ms
Each eNB process delay 10 ms
T311 10 s
12. I. Shayea et al.
1 3
Once the handover decision becomes true, the serving eNB starts for preparing hando-
ver by sending a Handover Request message to the target eNB; thus, the UE will enter the
handover procedure to establish connection with the target eNB. The handover procedure
is performed based on the handover procedure that has been introduced in LTE-Advanced
system in [44]. However, once the target eNB receives the Handover Request message, it
will start admission control. If the admission control decision is true, the target eNB will
send a Handover Request Acknowledge to the serving eNB, which in turn will begin DL
allocation. Thus, once the UE receives the Radio Resource Control (RRC)—Connection-
Reconfiguration message with the necessary parameters, it will begin to execute the hando-
ver to the target eNB.
5 Results and Discussion
In this section, the performance of the proposed AHOM-NWF algorithm is explained and
compared with other algorithms from the literature. The AHOM-NWF algorithm is com-
pared to (1) Fixed HOM (2) AHOM-D and (3) AHOM-CF. The AHOM-NWF and all the
comparative algorithms are implemented based on a conventional handover decision algo-
rithm →
(
RSRPT ≥
(
RSRPS + HOM
))
, where HOM represent the margin level, which is
the focus of this study as has been discussed in section II. The results are presented based
on two contiguous CA deployment scenarios (CADS-1 and CC-CADS) with different per-
formance metrics. Figures 6, 7 and 8 show the SINR, user’s cell edge spectral efficiency,
and outage probability, respectively, based on different handover margin algorithms with
two different CADSs. In Figs. 6 and 7, the results are presented as a Cumulative Distributed
Fig. 5 Handover Scenarios with the advent of CA technology
13. New Weight Function for Adapting Handover Margin Level over…
1 3
Probability Function (CDF), while in Fig. 8 user’s outage probability is presented versus
different mobile speed scenarios. The evaluation performances of SINR and spectral effi-
ciency are performed based on the evaluation that are analysed in [45], while the outage
probability is evaluated based on the evaluation method that is introduced in [46].
In Fig. 6a, AHOM-NWF achieves around 29.8, 14 and 6.3% as average gains of SINR
based on CADS-1 over the legacy decision algorithm based on Fixed-HOM, AHOM-D
and AHOM-CF respectively. While in Fig. 6b, AHOM-NWF achieves around 18.7, 2.7
and 2.3% as average gains of SINR based on CC-CADS over the legacy decision algorithm
based on Fixed-HOM, AHOM-D and AHOM-CF respectively.
In Fig. 7a, the cell edge spectral efficiency of AHOM-NWF based on CADS-1 can reach
up to 2.5 bps/Hz which shows significance improvement compare to Fixed-HOM, AHOM-
D and AHOM-CF with average gain of 30%, 4.4% and 3%, respectively. The same perfor-
mance is achieved for CC-CADS deployment, where AHOM-NWF has the higher spectral
efficiency of 3.25 bps/Hz among others algorithm as depicted in Fig. 7b. It achieves around
28.5%, 4.5% and 3.8% as average gains over the legacy decision algorithm based on Fixed-
HOM, AHOM-D and AHOM-CF respectively.
(a) (b)
CADS-1 CC-CADS
-20 -15 -10 -5 0 5 10 15 20 25
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
SINR [dB]
SINR
Probability[dB]
Empirical CDF
Fixed-HOM
AHOM-D
AHOM-CF
AHOM-NCF
-10 -5 0 5 10 15
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
SINR [dB]
SINR
Probability[dB]
Empirical CDF
Fixed-HOM
AHOM-D
AHOM-CF
AHOM-NCF
Fig. 6 SINR based on different handover algorithms with two different CADSs
CADS-1 CC-CADS
0 0.5 1 1.5 2 2.5 3
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Cell Edge Spectral Efficeincy [bps/Hz]
Cell
Edge
Spectral
Efficeincy
Probability
Cell Edge Spectral Efficeincy
Fixed-HOM
AHOM-D
AHOM-CF
AHOM-NCF
0.5 1 1.5 2 2.5 3 3.5
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Cell Edge Spectral Efficeincy [bps/Hz]
Cell
Edge
Spectral
Efficeincy
Probability
Cell Edge Spectral Efficeincy
Fixed-HOM
AHOM-D
AHOM-CF
AHOM-NCF
(a) (b)
Fig. 7 User’s cell-edge spectral efficiency
14. I. Shayea et al.
1 3
Figure 8a, b shows that the outage probability of all algorithms increased as the mobile
speed increase. The proposed algorithm, AHOM-NWF is less than FHOM algorithms with
63.7% and 65% as reduction gains of UE’s outage probability for CADS-1 and CC_CADS,
respectively. Compare to AHOM-D and AHOD-CF algorithms, the AHOM-NWF has the
reduction gains of only 9.2% and 14.7%, respectively for CADS-1 algorithm and 3% and
7%, respectively for CC-CADS algorithm.
Consequently, it can be stated that, AHOM-NWF achieves a significant enhancement
gains compare to the others algorithms. The total average enhancement gains that are
achieved by AHOM-NWF around 24.4, 14.6 and 17.9% over the legacy algorithm based
on Fixed-HOM, AHOD-D and AHOD-CF respectively. Thus, as these enhancements will
supports for service continuity and enhancing service quality. These achievable enhance-
ments by AHOM-NWF are mainly due to the three proposed functions, which are f(SINR) ,
traffic load, f(TL) and UE’s velocity, f(v)
. These parameters are influence factors, which
are contributing for taking a proper handover decision. The variations of these parame-
ters are mainly affecting the system performance inversely or extrusive. So that, adjusting
handover margin level based on these factors is particularly useful for taking the proper
HO decision. Thus, the effects of these three parameters on the estimated handover margin
level are further explained in the following paragraphs.
SINR is used as parameter for adjusting HOM level, which is considered sufficient as
a factor instead of channel condition, distance (d), noise and interferences. Since RSS is
evaluated as a function of channel condition and distance, while SINR is evaluated as a
ratio of serving RSS to the neighbours interferences plus noise ratio, thus adapting HOM
based on SINR parameter is more comprehensive than adapting HOM based on any single
parameters only. That contributes for estimating more a suitable HOM level than the other
algorithms. However, the formulated f(SINR) in (2), which is representing the difference
between the target and serving SINR ratios. f(SINR) is automatically varies between {− 1}
and {1} based on the serving and target SINR qualities. For the case of serving SINR is
better than the target SINR quality, the function of SINR will increased (f(SINR) 0)
whereupon the estimated HOM level by (7) become high, which in turn leads to prevent
the unnecessary handover. Because of that, the user’s connection is alaways connected with
the best serving eNB.In the other case, when the target SINR quality become better than
the serving SINR quality that leads to decrease f(SINR) 0
. Whereupon the estimated
CADS-1 CC-CADS
20 40 60 80 100 120 140 160
10
-2
10
-1
10
0
Mobile Speed [km/houre]
Outage
Probability
Fixed-HOM
AHOM-D
AHOM-CF
AHOM-NCF
20 40 60 80 100 120 140 160
10
-2
10
-1
10
0
Mobile Speed [km/houre]
Outage
Probability
Fixed-HOM
AHOM-D
AHOM-CF
AHOM-NCF
(a) (b)
Fig. 8 User’s Outage Probability versus Mobile Speed Scenarios
15. New Weight Function for Adapting Handover Margin Level over…
1 3
HOM level become small, which in turn leads to an advanced handover procedure to the
best target eNB.
Traffic Load is used as parameter for adjusting HOM level which is considered as a suf-
ficient factor since it contributes for balancing loads between CCs and neighbouring eNBs.
However, a mathematical function is simplified as a function of Traffic Load f(TL) in (4),
which is representing the difference between the target and serving loads ratios. f(TL) is
automatically varies between {−
1} and {1} based on the serving and target traffic loads.
In case if the traffic load of serving eNB is less than the traffic load of target eNB, that
leads to increases f(TL)
, which will become greater than zero, whereupon the estimated
HOM level by (7) will be high, which in turn leads to prevent unnecessary handover. This
leads to keep the user’s connection with the serving eNB, which is considered whereupon
the best eNB since it has more resource available. In the other case, when the target traf-
fic loads become less than the serving traffic loads that leads to decrease f(TL) , which
will become smaller than zero, whereupon the estimated HOM level will be small, which
in turn leads to take an early handover decision. This leads to an advanced handover pro-
cedure to the target eNB, which is considered as the best eNB as it enjoys more available
resources. Consequently, traffic load is a useful factor for adjusting margin level, contribut-
ing to an increase in HOM level when the load of target eNB is increased and it contributes
for decreasing HOM level when the load of target eNB is decreased. That leads to take a
proper handover decision, which in turn balancing the loads between CCs and eNBs as
well as the available resources between UEs. It also enhanced user’s SINR, spectral effi-
ciency, and reduced outage probability because the user’s connection with eNB that has
more resource available can be reduced.
UE’s velocity is considered in adjusting margin level. It is a useful consideration since
it can contribute to adjusting the margin level based on UE’s velocity, which can cause pre-
vention of unnecessary handover procedure that maybe occur at high UE movement speeds.
However, a mathematical expression is formulated as a function of UE’s velocity f(v) as in
(5), which can be decreased when the UE’s velocity is decreased and it is increased when
the UE’s movement speed is increased. In case of low mobility speeds a lower level of f(v)
is resulted, which leads to decrease the estimated margin level. That leads to perform an
early handover to the best target eNB when it is needed. On the other hand, when the UE’s
speed is increased f(v) will be increased, which in turn leads to increase HOM level. Thus,
the unnecessary handover that can be resulted by high movement speeds can be prevented.
That leads to prevent resource waste. Thus, considering UE’s velocity for adjusting the
margin level can contribute for enhancing user’s SINR, spectral efficiency and reducing the
user’s outage probability.
6 Conclusions
In this paper, AHOM-NWF has been proposed based on several parameters such as SINR
quality, traffic load and UE’s velocity. Mathematical expression has been formulated for
adjusting margin level based on three functions, which are evaluated as functions of SINR
quality, traffic load and UE’s velocity. Also, a mathematic model for estimating the weight
of each normalized function has been proposed. Simulation results demonstrate that the
proposed AHOM-NWF is optimal from the perspective of User’s SINR, cell edge through-
put enhancement and outage probability reduction compared to Fixed HOM, AHOM-D
and AHOM-CF through CA operation in LTE-Advanced system. Thus, AHOM-NWF
16. I. Shayea et al.
1 3
contributes to estimation of a suitable HOM level, which leads to a proper handover deci-
sion. That has allowed the UE to remain connected to the best eNB that either provides
a better SINR quality with availability of resources, or that has more resources available
with acceptable SINR level. Furthermore, it prevents unnecessary handover that may result
from a high UE’s velocity.
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Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and
institutional affiliations.
Ibraheem Shayea received the B.Sc. degree in Electronic Engineering
from the University of Diyala, Baqubah, Iraq, in 2004, and the M.Sc.
degree in Computer and Communication Engineering and the Ph.D.
degree in Mobile Communication Engineering from The National Uni-
versity of Malaysia, Universiti Kebangsaan Malaysia (UKM), Malay-
sia, in 2010 and 2015, respectively. Since the 1st of January 2011 until
28 February 2014 he worked as Research and Teaching Assistant at
Universiti Kebangsaan Malaysia (UKM), Malaysia. Then, from the 1st
of January 2016 until 30 Jun 2018, he joined Wireless Communication
Center (WCC), University of Technology Malaysia (UTM), Malaysia,
and worked there as a Research Fellow. He is currently working as a
Researcher Fellow at Istanbul Technical University (ITU), Istanbul,
Turkey, since the 1st of September 2018 until now.
Mahamod Ismail received the B.Sc. degree in Electrical and Electron-
ics from University of Strathclyde, U.K. in 1985, the M.Sc. degree in
Communication Engineering and Digital Electronics from UMIST,
Manchester U.K. in 1987, and the Ph.D. from University of Bradford,
U.K. He is currently a Professor with the Department of Electrical,
Electronics and System Engineering, and attach to the Center for
Information Technology as the Deputy Director (Research and Educa-
tion), Universiti Kebangsaan Malaysia. In 1997–1998 he was with the
team engineer building the first Malaysian microsatellite Tiungsat in
Surrey Satellite Technology Ltd., United Kingdom. He became the
Guest Professor in University of Duisburg Essen (formerly known as
Gerhard Mercator Universitat Duisburg), Germany in summer semes-
ter 2002. His research interests include mobile communication and
wireless networking. He published more than 200 technical papers in
journal and proceeding at local and international level. He is the past
chapter chair of IEEE Communication Society, Malaysia and Educa-
tional Activities chairman, IEEE Malaysia Section and currently the
committee member for the Joint chapter Communication and Vehicular Technology Society, IEEE Malay-
sia. He is also actively involved in conference and became the Technical Program Chairman, technical com-
mittee and paper reviewer.
19. New Weight Function for Adapting Handover Margin Level over…
1 3
Rosdiadee Nordin received the B.Sc. degree in Electrical and Elec-
tronics from Electrical and Electronics Engineering department, Uni-
versiti Kebangsaan Malaysia, Malaysia, July, 2001, and the Doctor of
Philosophy (Ph.D.), in Wireless Engineering from University of Bris-
tol, United Kingdom, January, 2011. He is currently a Ass. Professor
with the Department of Electrical, Electronics and System Engineer-
ing, Universiti Kebangsaan Malaysia.
Prof. Dr. Mustafa Ergen is professor of Electrical Engineering in Istan-
bul Technical University, president of venture funded Ambeent Inc.
focusing 5G and Artificial Intelligence plus Chief Technology Advisor
in Türk Telekom. Previously, Mustafa co-founded Silicon Valley
startup WiChorus Inc. to focus on 4G technologies and company is
acquired by Tellabs [now Coriant] for $200 M. Previously, he was a
National Semiconductor Fellow [now TI] at the University of Califor-
nia Berkeley, where he co-founded the Distributed Sensing Lab, focus-
ing on statistical sensor intelligence and vehicular communication.
Mustafa completed four programs from UC Berkeley: Ph.D. and MS
degrees in electrical engineering, MA degree from international stud-
ies and MOT program from HAAS Business School. His BS is from
electrical engineering as Valedictorian from Orta Dogu Technical Uni-
versity with 4.0/4.0 GPA. Prof. Dr. Ergen has more than 40 patent
applications, many publications and authored three books: Girisimci
Kapital: Silikon Vadisi Tarihi ve Startup Ekonomisi (2nd Edition—
KUY, 2017) 移动宽带系统—包括 WiMAX 和 LTE (PHEi, 2011),
Mobile Broadband: Including WiMAX and LTE (Springer, 2009), Multi Carrier Digital Communications:
Theory and Applications of OFDM (Springer, 2004). He is national delegate in 5G Infrastructure Associa-
tion and Horizon2020 ICT Funding Programs of European Union and advisor at Berkeley Program on
Entrepreneurship and Development. He is also an adjunct associate professor at Koç University. He also
served in the board of trustees of TOBB University of Economics and Technology and was cohost in TV
show on BloombergHT about entrepreneurship.
Dr. Norulhusna Ahmad graduated from Universiti Teknologi Malaysia
(UTM) in 2001 with B.Sc. in Electrical Engineering. She joined UTM
as a staff and later pursuing her study at the same university. She
received her Master degree of Electrical Engineering (Telecommuni-
cation) and Ph.D. in Electrical Engineering in 2003 and 2014, respec-
tively. Currently, she is a senior lecturer at Razak Faculty of Technol-
ogy and Informatics, UTM KL. Her expertise is on the area of signal
processing in wireless communication, iterative decoding and error
control coding. Her research interest is on emerging communication,
cognitive radio, internet of things, rural communication and communi-
cation in disaster management.
20. I. Shayea et al.
1 3
Nor Fadzilah Abdullah received an M.Sc. in Communications Engi-
neering from University of Manchester, UK and a B.Sc. in Electrical
and Electronics degree from Universiti Teknologi Malaysia, in 2003
and 2001 respectively. She has worked with major telecommunication
companies such as Ericsson Malaysia and Maxis Communications
Berhad, Malaysia between 2003 and 2008. She received a Ph.D. stu-
dent from the Centre for Communications Research at the University
of Bristol and sponsored by Malaysian Ministry of Higher Education
and Universiti Kebangsaan Malaysia in 2015. She is currently a Senior
lecturer with the Department of Electrical, Electronics and System
Engineering, Universiti Kebangsaan Malaysia.
A. Alhammadi received his BE in Electronic majoring in telecommu-
nications and M.S degree in wireless communication from Multimedia
University, Malaysia, in 2011 and 2015, respectively. He is currently
serving as a research scholar at Multimedia University since 2012. He
is the author of more than 20 papers in international journals and con-
ferences. His main research interests are in heterogeneous networks,
mobility management, D2D communication, cognitive radio networks,
localization, propagation modelling. He is a member of professional
institutes and societies such as IEEE, IEICE, IACSIT and IAENG. He
is also a member of more than ten program committees at international
conferences or workshops.
Hafizal Mohamad received the BE with First Class Honours and Ph.D.
in Electronic Engineering from University of Southampton, UK in
1998 and 2003, respectively. He has been a faculty member at the Mul-
timedia University, Malaysia from 1998. He served a short stint as a
visiting fellow at National Institute of Information and Communication
Technology (NICT), Yokosuka, Japan in 2005. Since 2007, he is a
Senior Staff Researcher at Wireless Communications Cluster, MIMOS
Berhad, where he leads a team of researchers working on cognitive
radio and mesh network. He has published over 50 journal and confer-
ence papers. He has 3 patents granted and 17 patents filed. He is a Sen-
ior Member of IEEE. He was the Vice Chair for IEEE Malaysia Sec-
tion (2013), and the Executive Committee of IEEE Malaysia Section
for Educational Activities (2011–2012). He was the Chair of IEEE
Communication Society and Vehicular Technology Joint Chapter,
Malaysia Section (2009–2011). He has been involved in organizing a
number of conferences since 2005 including; Technical Program Co-
Chairs for APCC 2012 (Jeju, Korea), APCC 2011 (Sabah), MICC
2009 (Kuala Lumpur) and Tutorial Chair for ICT 2007 (Penang).
21. New Weight Function for Adapting Handover Margin Level over…
1 3
Affiliations
Ibraheem Shayea1,2
· Mahamod Ismail1
· Rosdiadee Nordin1
· Mustafa Ergen2
·
Norulhusna Ahmad3
· Nor Fadzilah Abdullah1
· Abdulraqeb Alhammadi4
·
Hafizal Mohamad5
Mahamod Ismail
mahamod@ukm.edu.my
Rosdiadee Nordin
adee@ukm.edu.my
Mustafa Ergen
mustafaergen@itu.edu.tr
Norulhusna Ahmad
norulhusna.kl@utm.my
Nor Fadzilah Abdullah
fadzilah.abdullah@ukm.edu.my
Abdulraqeb Alhammadi
abdulraqeb.alhammadi@gmail.com
Hafizal Mohamad
hafizal.mohamad@mimos.my
1
Department of Electronics, Electrical and System Engineering, Universiti Kebangsaan Malaysia,
43600 Bangi, Selangor, Malaysia
2
Electronics and Communication Engineering Department, Faculty of Electrical and Electronics
Engineering, Istanbul Technical University (ITU), Istanbul, Turkey
3
Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia (UTM),
Kuala Lumpur, Malaysia
4
Multimedia University (MMU), Cyberjaya, Malaysia
5
MIMOS Berhad, Technology Park Malaysia, 57000 Kuala Lumpur, Malaysia