The document discusses cooperative relay based data transmission and proposes a system to select the most energy efficient relay node for a source node to transmit data through. It analyzes different cooperative relaying techniques like amplify-and-forward, decode-and-forward, and compress-and-forward. The proposed system aims to minimize the source node's cost for cooperation by selecting the relay node that provides the highest energy efficiency. This allows high data transmission over long distances with improved energy efficiency compared to direct transmission without a relay.

1. Survey on Cooperative Relay Based
Data Transmission
F.Lalrinfeli1 , Kavitha Balamurugan2
1
PG Scholar, Department of ECE, K.C.G College of Technology, Chennai
2
Associate Professor, Department of ECE, K.C.G College of Technology, Chennai
Abstract-Energy efficiency is becoming more
and more crucial in cooperative communication
systems. The energy efficient transmission
problem needs more focus in a single source-
relay-based cooperative network. A system is
proposed which will aim to find the most energy
efficient relay node for the source node when it
broadcasts a cooperation- request. When the
source node needs cooperation, the relay nodes
compete for it. The one which can minimize the
cost of the source node for cooperating is
selected. This will help achieve high data
transmission over the long distance with
comparatively higher energy efficiency. The
existing system has base station to end user
transmission whose disadvantage is low data
transmission. The proposed method uses
relaying strategies with amplify and forward
method.
Keywords—Cooperative relay, Amplify and
Forward, power allocation
I.INTRODUCTION
Cooperative communication has its history which
finds its deep roots to the groundbreaking work of
Van der Meulen when he introduced the idea of
relay channel model, the channel model consists of
a source, destination and relay, whose major
purpose was to allow the information transfer from
the source to the destination. The relay channel
model was deeply investigated by Cover and El
Gamal after Van der Meulen, which gave a number
of fundamental relaying techniques such as Decode
and Forward (DF) and Compress and Forward
(CF)[1]. In the case of conventional
communication, data is transmitted between the
source and destination, and users do not provide
assistance to one another. A practical wireless
communication network consists of many
neighbouring nodes, which could be of great
assistance. When one node transmits its data, all the
nearby nodes overhears the transmission by this
node. Cooperative Communication aims to process
and forward this overheard information to the
respective destination in order to create spatial
diversity, by which it increases the system
performance.
Basically, cooperative relaying is a technique for
wireless communication which guarantees gains in
throughput and energy efficiency. The basic idea is
that when a device needs to transmit data to its
destination, a third device overhears this signal and
then relays the signal to the destination. The
destination then combines these signals to improve
decoding. The main concept of cooperative relay
gives rise to pure self organizing networks without
any need for base stations. This technique can be
used for various applications of network embedded
systems .It is a promising means to reduce the
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2. effects of small scale fading. The whole concept of
cooperative relay is build on the idea of cooperative
diversity and it uses alternative communication
paths by getting assistance from other nodes in the
vicinity of the sender and the receiver of a
currently affected communication link. These
nodes then act as relays, i.e, a dedicated or
temporary wireless node which helps in forwarding
the information from a source node to a destination
node.In general, Cooperative relaying helps
achieve more efficient usage of resources and also
improves the quality of service. Many systems
from the present and future multi channel based
broadband access systems have adopted the
cooperative relaying technique, such as the 4th
generation (4G) orthogonal frequency division
multiple access (OFDMA) systems with LTE and
LTE-Advanced standards. It also proves to be the
underlying technique for many potential features
for 5G evolution. Such networks typically has
multiple communicating pairs along with available
relays. Efficient physical layer design of
cooperative relaying to support such simultaneous
transmissions is crucial[3].Cooperative
transmission schemes is differentiated by two
features from conventional non-cooperative
systems: 1) multiple users’ resources are used to
transmit the data of a single source; and 2) at the
destination, there is a proper combination of signals
from multiple cooperating users
Fig.1.1: Conventional Communication
Fig 1.2: Cooperative Communication
From fig. 1.2, we can say that the source node is
transmitting the data to the destination node; while
the relay node (another mobile user) is also helping
in the transmission. The relay station also processes
and forward this message to the destination, where
both of the received signals are combined. Since
both of the signals are transmitted through
independent paths, this results into spatial
diversity. Hence, each wireless user is assumed to
transmit its own data as well as act as a cooperative
agent (relay) for the other user in cooperative
communication [4].
II. ADVANTAGES AND SCOPE OF
COOPERATIVE COMMUNICATION
The advantages of cooperation can be exploited in
resource constrained networks, such as wireless
sensor networks by optimally allocating the energy
and bandwidth resources among users on the basis
of the available channel state information (CSI) at
each node. It exploits the spatial diversity inherent
in multiuser systems by allowing users with diverse
channel qualities to cooperate and relay each
other’s messages to the destination. Each
transmitted message is passed through multiple
independent relay paths and thus, the probability
that the message fails to reach the destination is
reduced significantly. In cooperative
communications users share and coordinate their
resources and thus enhance the transmission
quality. This idea is particularly attractive in
wireless environments due to the diverse channel
quality and the limited energy and bandwidth
resources. Cooperation allows the users that
experience a deep fade in their link towards the
destination to utilize quality channels provided by
their partners to achieve the desired quality of
service (QoS).
Suppose the transmission fails when the channel
has a deep fade, i.e., when the signal-to-noise ratio
(SNR) of the received signal falls below a certain
threshold. If the two users cooperate by relaying
each others’ messages provided the inter user
channel is sufficiently reliable, the communication
outage occurs only when both users experience
poor channels simultaneously.
SOURCE
RELAY
DESTINATION
SOURCE DESTINATION
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3. The advantages of relay cooperation usually
depend on sufficiently reliable inter user channels.
For example, in the Decode and Forward scheme,
a node relays the message from the source only if
the decoded message is reliable. Likewise, in the
case of Amplify and Forward scheme, the quality
of the relayed signal is limited by the quality of the
source-relay link since both the signal and noise are
amplified at relays. This means that relays should
be adopted only if the source-relay channel is
sufficiently reliable. These cooperative
communication schemes can be readily extended to
a large network for different applications.
III.COOPERATIVE COMMUNICATION
SCHEMES
As mentioned before, the transmitting user in
cooperative communication not only broadcast
their own message but also relays their
information, to the destination. The schemes by
which the information is being relayed to the
destination can be classified as [5]:
3.1. Amplify and Forward
Amplify-and-forward protocol was formally
introduced by Lane man et al based on the principle
of amplifying repeaters.In this method, the signal
received by a user from the source/transmitter is
first amplified and then forwarded to the
destination. This is the simplest scheme used for
relaying.
3.2. Decode and Forward
Thomas M. Cover and Abbas A.El Gamal are
considered as pioneers of this scheme. Later, the
idea was further explored by many authors with the
name of Decode-and-Forward.Decode and forward
relaying scheme works in such a way that the
partner users decodes the message received from
original transmitter, re-encodes and then forwards
it to the destination.
3.3. Compress and Forward
In Compress and forward relaying scheme, the
message is decoded from the transmitter and the
partner user/ relay node forwards a compressed
version of the message to the destination, so as to
get the diversity benefits.
A multiuser two-way relay network where multiple
pairs of users exchange information with the
assistance of a relay node, using orthogonal
channels per pair is considered[6]. In case of
different two-way relaying mechanisms, such as
decode and-forward (DF), amplify-and-forward
(AF) and compress-and forward(CF), an
investigation is done on the problem of optimally
allocating relay’s power among the user pairs it
assists in such a way that an arbitrary weighted sum
rate of all users is maximized, and the problem is
solved as one or a set of convex problems for each
relaying scheme. It has been observed that different
relaying schemes outperform one another for
different range of relay power. When the relay has
a low power budget, it is seen that three-phase
schemes outperforms two-phase ones. This is due
to the dominating contribution from the direct
links. Two-phase schemes may become better
when the relay-assisted transmissions dominate the
rates as the relay power increases,.
The information rate achievable and relay pre-
coder design of the AF MIMO relay network under
imperfect CSI caused by the presence of CE errors
and FB/FF delay errors have been investigated
[7].The achievable information rate under
imperfect CSI for two CE scenarios have been
derived.: In Case I, both the Source-Relay link and
the Relay-Destination link are estimated at the
destination, whereas in Case II, the Source-Relay
link is estimated at the relay, and the Relay-
Destination link is estimated at the destination.
Relay pre-coders to maximize the approximate
achievable information rate for various setups have
been proposed next. It has been shown by
numerical results that the MIMO relay network in
Case I always achieves better average achievable
information rate than in Case II. The accuracy
associated with the Source-Relay link is much
more important than that of the Relay-Destination
link. It is possible to achieve higher average
information rate compared with the fixed gain
relaying scheme.
Full CSI in a highly dynamic environment is
sometimes difficult to obtain, since all nodes must
continuously track the changes of the channel
states. Power allocation strategies based on partial
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4. CSI have been developed to address this issue.
Here, more power is allocated to Source since it
contributes to both the direct and relay paths.
Suppose that the full CSI is known at the relays, a
pre-coding technique similar to that in MIMO
systems can be used to compensate for both the
channel gain and the phase rotation experienced by
the relays to achieve better detection performance.
In this case, the optimal solution depends on the
orthogonality of the relay channels. For orthogonal
relaying channels, Destination receives N copies of
the source symbol from the relay nodes with no
interference among each other. With knowledge of
the exact channel coefficients, the N symbols can
be combined coherently at Destination to increase
the received SNR. In case of the Amplify and
Forward scheme over non-orthogonal channels,
relays can be viewed as multiple antennas with
complex gains applied to the output of each
antenna.
Of all these schemes, the amplify-and-forward
approach, due to its simplicity, is of particular
interest. The amplify-and-forward approach has
been extended to develop space-time coding
strategies for relay networks. While the
aforementioned cooperative approaches assume
different levels of CSI availability in the network,
they all share the common assumption that the relay
nodes operate at their maximum allowable power.
For different relaying strategies, the problem of
power allocation
between the source and the relay node(s) has been
well studied in the literature[5].
IV.POWER ALLOCATION
A review of power allocation methods under
different network topologies, multiple access
channels, cooperation methods and CSI
assumptions is given in [2].The topology first
studied is three-node topology, then the dual-hop
topology and finally a general multihop topology.
When the CSI is unknown to the transmitter, the
spatial diversity gain is achieved by allowing users
to have a fair share of each others’ resources. With
full or partial knowledge of the CSI, significant
improvements in terms of BER, outage probability
or capacity can be attained by applying optimal
power allocation among cooperating nodes.
The power emitted by each node can be optimally
allocated to improve the efficiency of the
transmission over spatially and temporally varying
channels when full CSI is available to Source,
Relay, and Destinaton, which means that the
complex coefficients are known. This problem has
been studied for both DF and AF cooperation
schemes and their solutions depend upon whether
the direct Source to Destination link is taken into
account or not. In case there exist a direct link
between Source and Destination, more power
should be allocated to Source since its
transmission contributes to the direct path as well
as to the relay path. If the quality of direct channel
is better than the Source-Relay link or the Relay-
Destination link, it is conventional that all the
power is allocated to S alone. The optimal power
allocation of the AF scheme with respect to the
end-to-end capacity can be observed in tha same
way.
When AF scheme is used, the Relay node does not
decode the message but it will simply retransmit an
amplified version of the received signal. As the
signal transmitted by Relay will contain an
amplified version of the noise along the Source-
Relay link, both the noise variance, and the total
power, play an important role in power allocation.
The power allocation problem exists only when the
Source-Relay link and the Relay-Destination link
are sufficiently good when compared to the Source-
Destination link with diversity. If not, one should
simply allocate all the power to the Source. When
the power allocation is required, a similar
dependence on Total Power and Noise variance is
observed.
In case of a dual-hop relay network, the power
allocation becomes much more complicated due to
the increased degree of freedom as a result of more
relay nodes. When the phase information is
unavailable to the relays, it is quite difficult to
compute the beam forming gain accurately and a
noncoherent combination of signals may result in
random constructive or destructive interference at
the Destination.All power maybe allocated only to
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5. one relay while all the other relays remain silent in
order to avoid the random interference among
different relay nodes. If selective relaying is used,
power allocation strategies can be derived to
maximize the lifetime of a wireless sensor network,
where lifetime is defined as the duration of time for
which the system remains operational. However,
the power allocation strategy that maximizes the
capacity or BER of each transmission may not
extend the network lifetime.
Power allocation problem in a two-hop MIMO
relay network where the main goal is to minimize
of the total power consumption of the system while
satisfying different QoS requirements given in
terms of the mean square errors has been observed.
Here, the original nonconvex power allocation
problem is approximated each for linear and
nonlinear architectures separately with a convex
one that can be solved exactly through a multistep
procedure of reduced complexity. When
comparisons are made with existing alternatives
requiring much higher computational burden, it is
seen that the same total power consumption is
required. It has also been observed that the case in
which multihops are used to carry the information
from the source to the destination is not that simple
and hence it has also been investigated.
The optimum relay power allocation problem has
also been investigated for a multiuser two-way
relay network with a variety of two-way relaying
protocols. It is seen that the obtained relay power
allocation solutions maximize an arbitrary
weighted sum of rates in the network, which allows
tracing the boundary of the achievable rate region
for each of the relaying scheme. On comparision of
the performance of different two-way relaying
schemes with optimum power allocation, it has
been observed that for given a relay power budget,
relaying scheme (DXF/CF) can always be chosen
along with the corresponding optimum power
allocation algorithm to obtain the highest rate of
weighted sum.
It has been obtained that the beam-forming weights
through maximizing the receiver SNR subject to
two different types of power constraints, namely
total transmit power constraint and individual relay
power constraints.The total power constraint leads
to a closed-form solution while the individual relay
power constraints result in a quadratic
programming optimization problem.
V.CHALLENGS OF COOPERATIVE
RELAY
Cooperative relay, aside from all its advantages
have some challenges to be faced. Here are some
challenges of cooperative relay based
communication:
5.1. Increased Overhead
For a system to function fully, the major
requirements are handovers, synchronization, extra
security, etc. These factors causes an increased
overhead with respect to a system that does not use
relaying.
5.2. Increased Interference
In case the offered power savings are not used to
decrease the transmission power of the relay nodes
but instead used to boost capacity or coverage, then
relaying will certainly generate extra intra and
inter-cell interference, which is a potential cause
for the system performance to deteriorate.
Therefore, cooperative relaying is much more
suitable for 3G/4G systems due to their higher
tolerance to interference.
5.3.Increased End-To-End Latency
The mere concept of relaying typically involves the
reception and decoding of the entire data packet
before it can be retransmitted. If delay-sensitive
services are supported, such as voice or the popular
multimedia web services, then the latency induced
by the decoding may become Detrimental in this
case. Latency certainly increases with the number
of relays along with the use of inter-leavers, such
as utilized in GSM voice traffic. To circumvent this
latency, either simple transparent relaying (i.e. AF
relaying) or some advanced decoding methods
need to be used.
5.4.More Channel Estimates
The number of wireless channels effectively
increases with the usage of relays. Hence,this
requires more channel coefficients to be estimated
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6. and thus more pilot symbols need to be provided in
case coherent modulation is to be used.
VI.CONCLUSION
In this paper, an overview of cooperative relay is
given along with its different attributes by which it
gains much attention in the field of high-data-rate,
efficient and reliable wireless communication. It is
emerging as an effective technique for reducing the
effects of path loss, shadowing, and multi-path
fading. Cooperative relaying provides diversity
gain, reduces outage probability and improves BER
performance. Various schemes of cooperative
communication, strategies, advantages and the
challenges of cooperative relay technique has been
discussed in this paper with respect to several
algorithms and systems developed based on this
technique. The whole concept of cooperative relay
deserves much more attention as it can solve
enormous problems faced in today’s wireless
communication.
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