A Review on Cooperative Communication Protocols in Wireless World

International Journal of Wireless & Mobile Networks (IJWMN) Vol. 5, No. 2, April 2013
DOI : 10.5121/ijwmn.2013.5209 107
A Review on Cooperative Communication
Protocols in Wireless World
Juhi Garg1
, Priyanka Mehta2
and Kapil Gupta3
1
Department of Electronics and Communication Engineering, FET-MITS University,
Lakshmangarh, Sikar, India
joohigrg@gmail.com
2
primehta04@gmail.com
3
kapil_mbm@yahoo.com
ABSTRACT
Future generations of cellular communications requires higher data rates and a more reliable
transmission link with the growth of multimedia services, while keeping satisfactory quality of service, .
MIMO antenna systems have been considered as an efficient approach to address these demands by
offering significant multiplexing and diversity gains over single antenna systems without increasing
bandwidth and power. Although MIMO systems can unfold their huge benefit in cellular base stations,
but they may face limitations when it comes to their deployment in mobile handsets.
To overcome this drawback, relays (fixed or mobile terminals) can cooperate to improve the overall
system performance in cellular networks. Cooperative communications can efficiently combat the severity
of fading and shadowing through the assistance of relays. It has been found that using relays the capacity
and coverage of cellular networks can be extended without increasing mobile transmit power or
demanding extra bandwidth.
KEYWORDS
Cooperative Communication, Coded Cooperation, MIMO, Amplify and Forward, Decode and Forward
1. INTRODUCTION
The increasing numbers of users demanding service have encouraged intensive research in
wireless communications. The problem with the cooperative communications is the unreliable
medium through which the signal has to travel. To mitigate the effects of wireless channel, the
idea of diversity has been deployed in many wireless systems [1-3]. Diversity is a
communication technique where the transmitted signal travels through various independent
paths and thus the probability that all the wireless paths are in fade is made negligible.
Frequency diversity, time diversity and space diversity are the three basic techniques for
providing diversity to the wireless communication systems.
Multiple-input multiple-output (MIMO) systems, where the transmitters as well as receivers are
equipped with multiple antennas, proved to be a breakthrough in wireless communication
system which offered new degree of freedom, in spatial domain, to wireless communications.
After that, MIMO became part of many modern wireless communications standards like LTE

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Advanced [1], WiMAX [2], [3] and Wireless LAN [4]. However, use of MIMO in small size
nodes, like used in wireless cellular networks proved to be a challenge. To address this
challenge, idea of cooperative communications came into existence to implement the idea of
MIMO in distributed manner. This concept says that transmitting users share each others’
antennas to give a virtual MIMO concept. Though, the idea of cooperative communication was
given in 2003 by Sendonaris et al. [5], [6], it is still considered an extensive research which is
going to exploit its benefits in the next generation communication systems [7][8].
In this article, we discuss a detailed overview of potential benefits offered by this new trend in
communication system.
2. WIRELESS COMMUNICATIONS AND MIMO SYSTEMS
Wireless communication systems have grown successfully over the last few decades and are
expected to continue in the future. There is an increasing demand for high data rates today in
order to support high speed interactive internet services and advanced multimedia applications
such as mobile TV, online gaming etc. This trend is enormously evolving in the 4G systems.
However, transmission over wireless channel of high rate (i.e. bandwidth) faces fundamental
limitations due to impairments inflicted by wireless channel such as, path loss, shadowing and
fading effects. These impairments can be compensated by various ways such as by increasing
transmit power, bandwidth, and/or applying powerful error control coding (ECC). However,
power and bandwidth are very scarce and expensive radio resources whereas ECC yields
reduced transmission rate. Thus, acquiring a high data rate together with reliable transmission
over error-prone wireless channels is a major challenge for wireless system designer.
Another way to cope with the impairments offered by the wireless channel is the use of MIMO
systems. In MIMO systems, multiple antennas are used at the transceiver. This arrangement can
significantly increase data rate and reliability of the wireless link. MIMO systems use either
VBLAST (Vertical Bell Laboratories Layered Space-Time) or DBLAST (Diagonal Bell Labs
Layered Space-Time) algorithm. However, using multiple co-located antennas causes
degradation in the system Quality of service (QoS) due to correlation between them. Also, due
to size, cost, or hardware limitations, small handheld wireless devices may not be able to
support multiple antennas [10].
To overcome the above drawback, an innovative approach known as cooperative
communication has been suggested to exploit MIMO’s benefit in a distributed manner. Such a
technique is also called a virtual MIMO, since it allows single antenna mobile terminals to reap
some of the benefits of MIMO systems. This concept is illustrated in Fig-1 below [9][10].
Figure 1. Illustration of MIMO and virtual MIMO systems [10]
=

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3. WORKING PRINCIPLE
The idea of cooperation was presented by van der Meulen in 1971, which established
foundation of relay channel. Cooperative communication takes advantage of broadcast nature of
the wireless medium where the neighbouring nodes overhear the source’s signals and relay the
information to the destination. Thus, idea of creating a VAA came into existence [11].
Figure 2. Cooperative Communication
4. HISTORICAL BACKGROUND
The scheme of cooperative communications is based on simple three terminal relay channel
introduced by Van der Meulen [12][13]. In this, it was shown that both the transmitter and
receiver nodes can be aided by a relay node to improve the rate region of the transmitter. Later,
idea of cooperative communications was given by Sendonaris [5][6]. The authors prove that
cooperative communications improves the achievable rate for both users, based on two user’s
cooperative communication scenario.
This is further extended by Lane man et al. [14-16]. The authors introduced the idea of amplify-
and-forward, decode-and-forward, and dynamic decode-and-forward protocol. The outage
probability is used as a performance metric to advocate the idea of cooperative communication.
The concept of coded cooperation was given by Hunter [17], [18] which is given as the
integration of cooperative communication and channel coding. The users code their information
into block composed of two parts. The transmitting user transmits the first part of block and
second part is transmitted by another cooperating user if it receives the first part successfully,
otherwise, user itself transmits the second part of the block. In this way, diversity gain is
exploited to efficiently counter the wireless channel impairment.
Later, various channel coding schemes have been applied to this scenario. LDPC [19] was first
applied by Khojastepour et al. [20]. Turbo codes et al. [21] was investigated by various
researchers [22-24]. Extensive work has been implemented by Hunter et al. [17], [18] where
they have utilized convolution codes to cooperative communication.
Thus, in the wireless transmission, the transmission of a node is physically broadcasted. Hence,
even though a node is not the next-hop node of a transmitted data, it can overhear it. In the
conventional transmission, only the next-hop node of the received data accepts it and all other
nodes just ignore it. We call this conventional transmission a direct transmission in this paper.
Independent fading paths

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Figure 3. In Cooperative Communication each mobile is both a relay and a user
However, if we appropriately utilize the broadcasting nature of the wireless transmission, we
can improve the performance of transmission such as its reliability and throughput. The
cooperative transmission uses this broadcasting nature of wireless transmission to improve the
performance of the transmission. In the cooperative transmission, if a node overhears a data
transmission, it may forward it to its next-hop node after performing some processing that
depends on cooperative transmission scheme. We call this node a cooperative node. Hence, the
next-hop node of the data may receive multiple data from the original transmitter node and from
several cooperative nodes and by appropriately combining and decoding them, the performance
of the transmission could be improved compared with that of the direct transmission.
(a) Direct transmission in a frame
(b) Cooperative transmission in a frame
Figure 4. Direct and Cooperative Communication in a frame
User 1
User 2
Destination
Time slot 1 Time slot 2 Time slot 3 Time slot 4
T/4 T/4 T/4 T/4
Time slot 1 Time slot 2 Time slot 3 Time slot 4
T/4 T/4 T/4 T/4

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5. PREVIOUS WORK
Cooperative relaying is an effective technique to combat multipath fading and enhance system
capacity and coverage. This section provides a literature survey on various aspects of
cooperative relaying.
Initially, capacity analyses of Gaussian relay channel was comprehensively studied in [25] .
In [26] , various relaying strategies for wireless networks have been studied. End-to-end error
and outage performance of non-regenerative relay network have been studied in [27] . Here, all
nodes are equipped with single antenna which operates in Nakagami-m fading channel. Outage
probability of multi-hop amplifies and forward relay systems have been analyzed in [28] . In
[29] , closed form expressions of average bit error rate (ABER), amount of fading and outage
probability (OP) have been derived for Rayleigh-fading channel where relay works in non-
regenerative mode and destination performs equal gain combining (EGC). In [30] and [31] ,
closed-form expressions are derived for the moment generating function (MGF), probability
density function (PDF), and cumulative distribution function (CDF) of the statistically
independent Gamma random variables. An amplify-and-forward (AF) relay network has been
studied in [32] where a source communicates with the user having best channel conditions
through an intermediate relay that serves to multiple users. Spatial reuse of relay time-slot in
interference limited channel has been analyzed in [33] for AF cooperative relaying. In [34] , -
Laneman et al. has developed and analyzed distributed space-time coded cooperative diversity
protocols for improving spectral efficiency. Error performance has been analyzed in [35] when
cooperative relay system operates in asymmetric channels. In [36] , outage performance of
MIMO relay channel has been investigated when source and relay use same orthogonal space
time block code. Selection cooperation in network scenario has been discussed in [37] where
multiple sources transmit their message and support each other to forward signals to their
respective destinations. End-to end error performance of selection cooperation has been
presented in [38] . In [39] , optimum power allocation for multi-antenna relay network at the
expense of increased computational complexity has been presented.
An overview of various cooperation schemes related to their implementation has been discussed
in [40] . In [41] , closed form expressions of OP and bit error rate (BER) for binary phase shift
keying (BPSK) are derived for case where communication between source and destination is
supported by multiple-antenna relay and both relay and destination performs MRC of signals in
Rayleigh fading channel. OP and average error rate of two-hop multi-antenna relay based
system for the case when relay performs selection combining (SC) of signals and destination
performs MRC of signals are analyzed in [42] and [43] , respectively. In [44] , closed form
expressions for OP and BER have been derived when multi-antenna relay network operates in
correlated Nakagami-m fading channel and both the relay as well as destination
performs MRC of signal. Closed form expression of outage probability has been derived in
[45] ; here, communication between source and destination is supported by two multi-antenna
relay nodes. A new efficient scheme for cooperative wireless networking based on linear
network codes has been discussed in [46] .
6. BASIC RELAYING PROTOCOLS
In cooperative communications, the transmitting user not only broadcast their own message but
they also relay information, on behalf of each other, to the destination. The strategy, by which
the information is relayed to the destination, is known as protocol. Various protocols have been
introduced so far. Here, we describe some of the basic relaying protocols.

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6.1. Amplify and Forward
This is the simplest protocol. Here, the information received by a user from original transmitter
is amplified and then forwarded to the destination. Based on the principle of amplifying
repeaters [47], amplify-and-forward protocol was formally introduced by Lane man et al. [48]
6.2. Decode and Forward
In this relaying protocol the partner users decodes the message received from original
transmitter, re-encodes and then forwards it to the destination. Thomas M. Cover and Abbas A.
El Gamal are considered as its pioneer [50] and later the idea was further explored by many
authors with the name of Decode-and-Forward [16], [15], [50].
6.3. Compress and Forward
In this relaying protocol, the message is decoded from the transmitter and the partner user
forwards a compressed version of it to the destination, so as to get the diversity benefits [49].
7. COOPERATIVE RELAYING TECHNIQUES
In this section, we will discuss Different Cooperative Protocols or Transmissions Techniques
used in Cooperative Communication. Cooperative communications protocols can be generally
categorized into fixed relaying schemes and adaptive relaying schemes. In this section, we
describe both of these schemes along with both single relay and multi relay scenario.
7.1. Cooperation Protocols
A cooperation strategy is modelled into two orthogonal phases, to avoid interference between
the two phases, either in TDMA or FDMA.
In phase 1, source broadcast information to its destination, and the information is also received
by the relay (due to broadcast) at the same time as shown in figure 5 below.
Figure 5. Phase 1
In phase 2, the relay forwards or retransmits the information to the destination as shown in
figure 6 below.
Figure 6. Phase 2
Source
Relay
Destination
Source
Relay
Destination

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Fig- 7 below depicts a general relay channel, where the source transmits with power P1 and the
relay transmits with power P2. Here, we will consider the special case when both source and
relay transmit with equal power P. Optimal power allocation is a vast topic so can be consider
for future work.
Figure 7. Simplified Cooperation Model [51]
In phase 1, source forwards its information to both the destination and the relay. The received
signals sdY at the destination and srY at the relay, can be written as
sdsdsd nxhPY += (1)
srsrsr nxhPY +=
(2)
where P is the transmitted power at source, x is the transmitted information symbol, and sdn
and srn are additive noise. In (1) and (2), sdh and srh are the channel fades between the source
and destination and the relay, respectively, and are modelled as Rayleigh flat fading channels.
Rayleigh flat fading channel can be mathematically modelled as complex Gaussian random
variable. It is given as z = x + jy, where real and imaginary parts are zero mean independent and
identically distributed (i.i.d) Gaussian random variables. The noise terms sdn and srn are
modelled as zero-mean complex Gaussian random variables with variance No.
In phase 2, relay forwards source’s signal to the destination, and this can be modelled as
rdsrrdrd nYqhY += )( (3)
where the function q (·) depends upon processing which is implemented at the relay node [52].
7.2. Fixed Cooperation Strategies
In fixed relaying, channel resources are divided between source and relay in a fixed
(deterministic) manner. The processing at relay differs according to the employed protocols.
The most common techniques are the fixed AF relaying protocol and the fixed relaying DF
protocol [15][34].
P1
Destination (D)
Source (S)
hs,r hr,d
hs,d
P2

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7.2.1. Fixed Amplify & Forward (Single Relay)
In a fixed AF relaying protocol, or AF protocol, the relay scales the received version and
transmits its amplified version to the destination. The amplify-and-forward scheme is presented
in Fig-8.
Figure 8. Amplify and Forward System Model [51]
The amplify-and-forward relay channel can be modelled as follows. The signal transmitted from
the source x to both the relay and destination can be given as
srsrsr nxhPY += and sdsdsd nxhPY += (4)
where srh and sdh are channel fades between the source and the relay and destination,
respectively. The terms srn and sdn denote the additive white Gaussian noise with zero-mean
and variance N0. Here, the relay amplifies the source signal and forwards it to the destination, to
equalize the effect of the channel fades between the source and the relay. The relay scales the
received signal by a factor that is inversely proportional to the received power, which is denoted
by
osr NhP
P
+
=β
(5)
The signal transmitted from relay is therefore, given by srYβ and has power P equal to the
power of the signal transmitted from the source. In phase 2, the relay amplifies the received
signal from source and forwards it to the destination.
The received signal, in phase 2, at the destination, according to (4) is given as
rdsrrd
osr
rd nYh
NhP
P
Y +
+
=
(6)
Here rdh is the channel coefficient from relay to the destination and sdn is an additive noise.
Destination (D)
Signal
Received Signal
Amplified Signal

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7.2.2. Fixed Amplify & Forward (Multi Relay)
An amplify-and-forward protocol does not suffer from any error propagation problem because
the relay does not need to perform any hard-decision operation on the received signal. First we
discuss the multi-node amplify-and-forward protocol and then analyze its two relaying
strategies. In the first phase, each relay forwards the source’s signal to the destination, while in
the second phase each relay forwards a combined signal from source and previous relays. Fig-9
shows the multi-node Amplify and Forward system model.
Figure 9. Multi Node Amplify and Forward System Model [52]
7.2.3. Fixed Decode and Forward (Single Relay)
Another possibility at the relay node is to decode the received signal at the relay, re-encode it,
and then retransmit it to the receiver. The decode-and-forward scheme is presented in Fig-10.
This kind of relaying is often called as DF scheme. If the decoded signal at the relay is denoted
by x’, the transmitted signal from the relay can be denoted by x’, given that x’ has unit variance.
Figure 10. Decode and Forward System Model [52]
If an incorrect signal is forwarded to the destination, then decoding at the destination is
meaningless. It is clear that the diversity achieved for such a scheme is only one, because
performance of the system is limited by the worst link from the source–relay and source–
destination.
Relay 1
Source
Destination
Relay 2
Orthogonal
Channels
Relay N
Signal
Source (S)
Received Signal
Destination (D)
Re-Encoded
Signal

116
Although fixed DF relaying has the advantage of reducing the effects of additive noise at the
relay over AF relaying, it forwards erroneously detected signals to the destination, causing error
propagation that can diminish the performance of the system. Mutual information between the
source and destination is limited by the mutual information of the weakest link between the
source–relay and the combined channel from the source–destination and relay–destination. The
received signal at the destination in Phase 2 can be given as
rdrdrd nxhY += 2β (7)
With the help of channel coefficients sdh (between source and destination) and rdh (between
relay and destination), the destination detects the transmitted symbols by jointly combining the
received signal sdY from the source in eq. (1) and rdY from the relay in eq. (7).
7.2.4. Fixed Decode and Forward (Multi Relay)
Here, we consider a N-relay (2 Relay For Simulation Purpose) wireless network, where
information is to be transmitted from a source to a destination. Due to the broadcast nature of
the wireless channel, relays overhear the transmitted information and thus cooperate with the
source to send its data. The wireless link between any two nodes is modelled as a Rayleigh
fading channel with AWGN.
The channel fades for different links are assumed to be statistically independent because the
relays are usually spatially separated. The additive noise at receiving terminals is modelled as
zero-mean, complex Gaussian random variables with variance No. The relays are assumed to
transmit over orthogonal channels, thus there is no inter-relay interference.
In DF protocol cooperation strategy, each relay can combine the signal received from the source
along with the signals transmitted by previous relays, decode it and then retransmit it to the
receiver after re-encoding it again. A general cooperation scenario, denoted as C(m) (1 ≤ m ≤ N
− 1), is implemented in which each relay combines the signals received from m previous relays
along with that received from the source.
The multi relay decode and forward scenario is shown in Fig- 11, in which each relay combines
the signals received from previous relays along with that received from the source. In all
considered cooperation scenarios, destination coherently combines the signals received from the
source and relays. Now, we are presenting the system model for a general cooperative scheme
C(m) for any 1 ≤ m ≤ N − 1, where each relay decodes the information after combining the
signals received from the source and previous m relays. We consider 2 relays for simulation
purpose.

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Figure 11. Illustration of Multi relay cooperation [52]
In General Multi Node cooperation protocol has (N+1) phases as stated in AF section but three
in our case. In phase 1, source transmits information to both destination and the ith
(1st) relay,
which can be modelled as,
sdsdosd nxhPY +=
(8)
srisrioris nxhPY +=, Ni ≤≤1 (9)
where oP is the power transmitted at the source, x is the transmitted symbol, sdh and srih are
the fading coefficients between source and destination, and ith
relay, respectively. The terms sdn
and srin denote the AWGN channel noise. In phase 2, the 1st relay decodes the signal it
receives from source, re-encode & send it to other relay & the destination. Second relay
combines the received signals from the 1st relay and source as follow
2,12,12,2,2 rrrrirsrsor YhPYhPY ∗∗
+=
(10)
where 2,1 rrh is the channel fading coefficient between the 1st and the 2nd relay, 2,1 rrY denotes
the signal received at 2nd relay from the 1st relay, which is given as
2,12,12,1 rrrrirr nxhPY +=
(11)
where iP is the power transmitted at relay 1, finally in phase (N + 1), the destination coherently
combines all of the received signals, which are modelled as
dri
N
i
driisddsod YhPYhPY ,
1
,, ∑=
∗∗
+=
(12)
S
R1
R2
Rk
Rk+1
RN
D
Virtual (N+1) *1 MIMO

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7.3. Other Cooperation Strategies
Besides the techniques for fixed relaying, there are other techniques, such as compress-and
forward cooperation and coded cooperation. Here, we discuss an overview of each of them.
7.3.1. Compress and Forward
The main difference between compress-and forward and decode/amplify-and-forward is that in
the later the relay transmits a copy of the received message, while in compress and forward the
relay transmits a quantized and compressed version of the received message. Therefore, the
destination performs the reception function by combining the received message from both
source node and its compressed version from the relay node.
The quantization and compression process at relay node is a process of source encoding, i.e.,
representation of each received message as a sequence of symbols. Let us assume that these
symbols are binary digits (bits). At the destination, an estimate of the compressed message is
obtained by decoding the received sequence of bits. This decoding operation involves mapping
of received bits into a set of values that estimate the transmitted message. This mapping process
normally involves the introduction of distortion, which can be considered as a form of
attenuation and noise [25], [53].
7.3.2. Coded Cooperation
Coded cooperation differs from the previous schemes such that the cooperation is implemented
at the level of the channel coding subsystem. We know in both amplify and forward and
decode-and-forward schemes, the relay repeats the bits sent by the source. In coded cooperation
incremental redundancy at relay, which when combined at the receiver with the codeword sent
by the source, results in a codeword with larger redundancy [54].
7.4. Adaptive Cooperation Strategies
Fixed relaying has advantage of easy implementation and disadvantage of low bandwidth
efficiency. This is because half of the channel resources are allocated to relay for transmission,
which leads to reduced overall rate, because in such a scenario, a high percentage of the packets
transmitted by the source to the destination could be received correctly by the destination and
the relay’s transmissions would be wasted.
To overcome this problem, adaptive relaying protocols are developed to improve the
inefficiency. Here, we will discuss two strategies: selective DF relaying and incremental
relaying [52].
7.4.1. Selective DF Relaying
In this relaying scheme, the relay decodes the received signal and forwards decoded information
to the destination, if the signal-to noise ratio of a signal at the relay exceeds a certain threshold.
On the other hand, if the channel between the source and the relay suffers, such that the signal-
to-noise ratio falls below the threshold, the relay remains idle. Selective relaying shows
improvement upon the performance of fixed DF relaying, as the threshold at the relay can be
used to overcome the inherent problem in fixed DF relaying in which the relay forwards all
decoded signals to the destination although some signals are incorrect. We knew, if the SNR in
source–relay link exceeds the threshold, the relay is able to decode source’s signal correctly. In
this case, SNR of the combined MRC signal at destination is given as sum of the received SNR
from the source and the relay.

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7.4.2. Incremental Relaying
In incremental relaying, there is a feedback channel from the destination to the relay. The
destination sends an acknowledgement to the relay if it was able to receive the source’s message
correctly. This protocol has the best spectral efficiency among the previously described
protocols because the relay does not always need to transmit, and hence second transmission
phase becomes opportunistic depending on the channel state condition of channel between the
source and the destination. Nevertheless, incremental relaying achieves a diversity order of two
as mentioned below:
In incremental relaying, if the source transmission in the first phase was successful, then there is
no second phase and source transmits new information in the next time slot. On the other hand,
if source transmission was not successful in the first phase, then relay can use any of the fixed
relaying protocols to transmit the source signal from the first phase. The transmission rate (R) is
random in incremental relaying. If the first phase was successful, the transmission rate is R,
while if it was in outage, the transmission rate becomes R/2 as in fixed relaying.
8. APPLICATIONS
This section highlights some of the areas where the cooperative relaying strategies can be
applied.
8.1. Virtual antenna array
The field of high-data-rate, spectrally efficient and reliable wireless communication, is currently
receiving much attention. It is a well known fact that the use of MIMO antenna system
improves the diversity gain of wireless systems. However, multi-antenna technique is not
attractive for tiny wireless nodes due to limited hardware and signal processing capability.
Diversity can be achieved through user cooperation, whereby mobile users share their physical
resources to create a virtual array, which thus, removes the burden of multiple antennas on
wireless terminals.
8.2. Wireless ad-hoc network
Ad hoc network is a self organizing network without any centralized infrastructure. In this n/w,
distributed nodes form a temporary functional network and support seamless leaving or joining
of nodes. Such network has been deployed for military communication and civilian applications
including commercial and educational use etc.
8.3. Wireless sensor network
Lifetime of sensor network can be increased by deploying cooperative relaying hence, energy
consumption in sensor nodes got reduced. We knew, communication through weaker channels
requires huge energy as compared to relatively strong channels. So, careful incorporation of
cooperating relay nodes into routing process can select better communication links and precious
battery power can be saved.
8.4. Cooperative sensing for cognitive radio
In cognitive radio system, secondary users can utilize the resources which are employed for
licensed primary users. When primary users want to use their licensed resources, secondary
users have to vacant these resources. Thus, secondary users have to constantly sense the
presence of primary user. Probability of false alarming can be reduced with the help of spatially
distributed nodes, which thus improve the channel sensing reliability by sharing the information
[55].

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9. TRACKS FOR FUTURE WORK
This paper investigated the performance of some of the basic cooperative relaying schemes. For
practical implementation of such schemes in a network environment, it is necessary to
investigate several other issues, some of which are briefly outlined below:
9.1. System modelling taking inference into consideration
In a network scenario, cooperative relay system suffers from co-channel and adjacent channel
interference. Thus, the effect of the interference needs to be analysed.
9.2. Power optimization based on link condition
Wireless nodes generally have limited battery power. Power can be allocated if relay based
systems have some feedback mechanism, based on link condition [34] . Such dynamic
allocation may save battery power or boost the data transfer rate and hence the optimization area
to be investigated.
9.3. Full duplex operation of relays
Relay operating in half-duplex mode creates a wide system bandwidth expansion. Full-duplex
relay operating in single frequency are used to solve this problem. Thus, the effect of full-
duplex relay operation needs to be investigated.
9.4. Complexity performance trade off
Relays can process the signal in non-regenerative or regenerative mode depending on their
functionality. Non-regenerative mode puts less processing burden on the relay as compared to
regenerative mode of operation; hence, it is often preferred when complexity and/ or latency are
needed to be analysed. Scope has been found to exist in future for non-regenerative mode of
relay operation. Noise amplification is a major issue in this operation.
9.5. Modelling of relay link in various environments
Wireless propagation suffers with path loss, shadowing and fading which depends on regional -
geography. Statistical behaviours of various propagation environments are available in
literatures. Relay link can be easily modelled in such propagation environment.
9.6. Relay selection
In the present state of art, wireless relay nodes are half-duplex in nature. Participation of large
number of relay increase the diversity order, but spectrum efficiency of system may suffer.
Therefore, selection of the nodes and optimum number of nodes which should be selected to
optimize the performance in terms of rate and reliability is an interesting field of research.
9.7. Spectrum efficiency
Orthogonal transmission from relay to receiver in TDMA mode can affect the spectrum
efficiency. Relay can interact with the receiver in CDMA mode which avoids bandwidth
expansion. Therefore, orthogonal code design for distributed relay node may be possible area
for research.
9.8. Node cooperation with cross-Layer design
Node cooperation is an efficient technique to improve the performance of WSN’s. Sensor nodes
are powered by small battery that cannot be easily recharged. So reducing energy consumption

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is a wide issue for such type of network. Protocol layering provides modularity that facilitates
standardization and implementation. Unfortunately, layering precludes the benefits of joint
optimization across protocol layers; hence, precious battery power cannot be efficiently utilized.
In this regard, it would be interesting to investigate cross-layer optimization [56] .
9.9. Bidirectional user cooperation
In this work, we are assuming that relay terminals do not have their own data and they are just
forwarding data received from source. In user cooperation, user’s terminal not only transmits its
own data, but also relays other user’s data by sharing some of the resources. In this regard, it
would be interesting to investigate bidirectional user cooperation extension.
9.10. Base station cooperation
In single cellular system, user terminals can communicate with parent base station. Users near
the outskirts of cell can communicate with neighbouring base stations and thus becomes a
source for generating interfering signals. To overcome this, neighbouring base stations can also
cooperate with parent base station and perform joint decoding of received signals. The work
presented for relay cooperation can be extended for base station cooperation.
10. CHALLENGES
Helping out users in a cooperative fashion has its price. Here, we will describe the challenges
that incur in systems with cooperative communication incorporated [57][58].
10.1. Complex Schedulers
Relaying requires more sophisticated schedulers since not only traffic of different users and
applications needs to be scheduled but also the relayed data flows. This function decides how
many resources are scheduled for a single user (or relay node). This function affects the
achieved throughput of the system. Practical implementations of a scheduler also consider
Automatic Repeat-Request (ARQ) protocols and Quality-of-Service (QOS) classes, which
experience different priorities in the scheduling process.
10.2. Increased Overhead
A full system functioning requires handovers, synchronization, extra security, etc. This clearly
induces an increased overhead w.r.t to a system that does not use relaying.
10.3. Increased Interference
If the offered power savings are not used to decrease the transmission power of the relay nodes
but rather to boost capacity or coverage, then relaying will certainly generate extra intra and
inter-cell interference, which potentially causes the system performance to deteriorate. So
cooperative relying is more suitable for 3G/4G systems which are more tolerant to interference.
Many Interference mitigation schemes have been proposed for cooperative communication e.g.,
successive interference cancellation (SIC) scheme in wireless communication network. Zero
forcing (ZF) or minimum mean square error (MMSE) receivers are used to mitigate co-channel
interference (CCI) in the interference cancellation strategy. For efficient utilization of scarce
radio spectrum and codes, a centralized medium access control (MAC) protocol is proposed to
coordinate the code assignment and channel access among the users and relays [59], [60].

122
10.4. Increased End-To-End Latency
Relaying typically involves the reception and decoding of the entire data packet before it can be
retransmitted. If delay-sensitive services are being supported, such as voice or the increasingly
popular multimedia web services, then the latency induced by the decoding may become
detrimental. Latency increases with the number of relays and also with the use of interleavers,
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.
10.5. More Channel Estimates
The use of relays effectively increases the number of wireless channels. This requires the
estimation of more channel coefficients and hence more pilot symbols need to be provided if
coherent modulation was to be used.
11. CONCLUSIONS
As stated at the outset, the field of high-data-rate, efficient and reliable wireless communication,
is currently receiving much attention. Cooperative transmission is emerging as an effective
technique for combating effects of path loss, shadowing, and multi-path fading. This tutorial
elaborates wireless cooperative communication, a technique that both allow single antenna
mobiles to share their antennas and reap the benefits of multiple antenna systems. Cooperative
relaying provides diversity gain, reduces outage probability and improves BER performance.
Various types of relays, mode of operation, applications, and tracks for future work have been
discussed here. This paper will be helpful for incorporating relay based system in real scenario.
Throughout this paper we focused on only two Protocols viz AF & DF but there are many other
protocols as well that deserve attention. We also didn’t include Power Allocation i.e. at what
power; source/relay should transmit without causing interference for others.
REFERENCES
[1] 3GPP TR 36.814 V1.2.1, “Further advancements for EUTRA: Physical layer aspects,”
Technical Specification Group Radio Access n/w, June 2009.
[2] I. P802.16j/D9, “Draft amendment to IEEE standard for local and metropolitan area network part
16: Air interface for fixed and mobile broadband wireless access systems: Multihop relay
specification,” May 2009.
[3] Yang Yang; Honglin Hu; Jing Xu; Guoqiang Mao, “Relay technologies for WiMAX and LTE-
Advanced mobile systems,” IEEE Comm. Magazine, vol. 47, no. 10, pp. 100–105, October 2009.
[4] “IEEE draft standard for local and metropolitan area networks; part 11: Wireless LAN medium
access control (MAC) and physical layer (PHY) specification: amendment: enhancements for
higher throughput, IEEE Draft Std.802.11n (d2),” 2007.
[5] A. Sendonaris, E. Erkip and B. Aazhang, “User cooperation diversity- Part I: System
description,” IEEE Transaction on Communications, vol. 51, no. 11, pp. 1927–1938, Nov. 2003.
[6] A. Sendonaris, E. Erkip and B. Aazhang, “User cooperation diversity-Part II: Implementation
aspects and performance analysis,” IEEE Trans. on Commun., vol. 51, no. 11, pp. 1939–1948,
Nov. 2003.
[7] L. Sankar, G. Kramer and N. B. Mandayam, “Dedicated-relay vs. user cooperation in time-
duplexed multi-access networks,” Journal of Communications, vol. 6, no. 9, pp. 330–339, July
2011.
[8] Hongzheng Wang; Shaodan Ma; T. S. Ng , “On performance of cooperative communication
systems with spatial random relays,” IEEE Trans. on Commun., vol. 59, no. 4, pp. 1190–1199,
2011.

123
[9] Birsen, Sirkeci, “Distributed Distributed Cooperative Communication in Large-Scale Wireless
Networks,” Cornell University 2006.
[10] Quang Trung Duong, “On Cooperative Communications and Its Application to Mobile
Multimedia,” Blekinge Institute of Technology, ISBN: 978-91-7295-167-9, 2010.
[11] Y.W. Peter Hong, Wan-Jen Huang & C.C. Jay Kuo, “Cooperative communications and
Networking: Technologies and System Design,” Springer, (2010) ISBN: 1441971939.
[12] E. C. Van Der Meulen, “Transmission of information in a T-terminal discrete memory less
channel,” Ph.D. Disser., Dept. of Statistics, University of California, Berkeley, 1968.
[13] Edward C. Van Der Meulen, “Three terminal communication channels,” Adv. Appl. Prob., vol.
3, pp. 120–154, 1971.
[14] J. N. Laneman and G. W. Worn ell, “Energy-efficient antenna sharing and relaying for wireless
networks,” in IEEE Wireless Commun. and Networking Conference (WCNC-2000), vol. 1, pp.
7–12, Sep 2000.
[15] J. N. Laneman, D. N. C. Tse and G. W. Wornell, “Cooperative diversity in wireless networks:
efficient protocols and outage behaviour,” IEEE Trans. on Information Theory, vol. 50, no. 12,
pp. 3062–3080, Dec. 2004.
[16] J. N. Laneman, “Cooperative diversity in wireless networks: Algorithms and architectures,”
Ph.D. dissertation, Massachusetts Institute of Technology, Cambridge, MA, Aug 2002.
[17] T. E. Hunter and A. Nosratinia, “Co-operation diversity through coding,” IEEE International
Symposium on Information Theory, pp. 220, July 2002.
[18] T. E. Hunter and A. Nosratinia, “Diversity through coded co-operation,” IEEE Transactions
on Wireless Commun., vol. 5, no. 2, pp. 283–289, Feb. 2006.
[19] R. G. Gallager, “Low density parity-check code,” Ph.D. Dissertation, Massachusetts Institute of
Technology, Cambridge, MA, 1963.
[20] M. A. Khojastepour, N. Ahmed and B. Aazhang, “Code design for the relay channel and
factor graph decoding,” Conference Record of the Thirty-Eighth Asilomar Conf. On Signals,
Systems and Computers, vol. 2, pp. 2000–2004, 2004.
[21] C. Berrou, A. Glavieux and P. Thitimajshima, “Near Shannon limit error-correcting coding and
decoding: Turbo-codes,” IEEE International Conference on Communications, vol. 2, pp. 1064–
1070, 1993.
[22] Z. Zhang and T. M. Duman, “Capacity-approaching turbo coding and iterative decoding for
relay channels,” IEEE Trans. on Commun., vol. 53, no. 11, pp. 1895–1905, Nov. 2005.
[23] B. Zhao and M. C. Valenti, “Distributed turbo-coded diversity for the relay channel,” IEEE
Electronics Letters, vol. 39, no. 10, pp. 786–787, May 2003.
[24] Bin Zhao and Matthew C. Valenti, “Cooperative diversity using distributed turbo codes,”
Virginia Technical Symposium on Wireless Personal Communications, (Blacksburg, VA), June
2003.
[25] T. Cover and A. E. Gamal, “Capacity theorems for the relay channel,” IEEE Trans. on
Information Theory, vol. 25, no. 5, pp. 572-84, Sep. 1979.
[26] P. Herhold, E. Zimmer-mann and G. Fettweis, “Cooperative multi-hop transmission in wireless
networks,” Computer N/w, Vol. 49, no. 3, pp. 299-324, 2005. Selected Paper from the European
Wireless 2004 Conference.
[27] M. S. Alouini and M. O. Hasna, “End-to-end performance of transmission systems with relays
over Rayleigh-fading channels”, IEEE Trans. on Wireless Commun., vol. 2, no. 6, pp. 1126-31,
Nov. 2003.
[28] C. Conne and Il-Min Kim, “Outage probability of multi-hop amplify-and-forward relay
systems,” IEEE Trans. on Wireless Communications, vol. 9, no. 3, pp. 1139-49, Mar. 2010.

124
[29] S. Ikki and M. H. Ahmed, “Performance analysis of cooperative diversity using equal gain
combining (EGC) technique over Rayleigh fading channels,” IEEE International Conf. on
Commun., pp. 5336-41, Jun. 2007.
[30] G. K. Karagiannidis, T. A. Tsiftsis, R. K. Mallik, N. C. Sagias and S. A. Kotsopoulos, “Closed-
form bounds for multi-hop relayed communications in Nakagami-m fading”, IEEE International
Conf. on Communications, vol. 4, pp. 2362-6, May 2005.
[31] G. K. Karagiannidis, T. A. Tsiftsis and R. K. Mallik, “Bounds for multi-hop relayed
communications in Nakagami-m fading,” IEEE Trans. on Communications, vol. 54, no.1, pp.
18-22, Jan. 2006.
[32] J. B. Kim and D. Kim, “Comparison of two SNR-based feedback schemes in multi-user dual-
hop amplify and forward relaying networks”, IEEE Commun. Letters, vol. 12, no.8, pp. 557- 9,
Aug. 2008.
[33] A. Agustin and J. Vidal, “Amplify-and-forward cooperation under interference-limited spatial
reuse of the relay slot”, IEEE Trans. on Wireless Commun., vol. 7, no. 5, pp. 1952-62, May
2008.
[34] J. N. Laneman and G. W. Wornell, “Distributed space-time-coded protocols for exploiting
cooperative diversity in wireless networks”, IEEE Trans. on Information Theory, vol. 49, no. 10,
pp. 2415-25, Oct. 2003.
[35] A. Adinoyi and H. Yanikomeroglu, “On the performance of co-operative wireless fixed relay in
asymmetric channels,” IEEE Global Telecommun. Conf., pp. 1-5, Dec. 2006.
[36] L. Vandendorpe and B. K. Chalise, “Outage probability analysis of a MIMO relay channel with
orthogonal space-time block codes,” IEEE Commun. Letters, vol. 12, no. 4, pp. 280-2, Apr.
2008.
[37] E. Beres and R. Adve, “Selection cooperation in multi-source co-operative networks”, IEEE
Trans. on Wireless Communications, vol. 7, no. 1, pp. 118-27, Jan. 2008.
[38] A. Adinoyi, Y. Fan, H. Yanikomeroglu and H. V. Poor, “On the performance of selection
relaying,” IEEE Vehicular Technology Conference, pp. 1-5, Sep. 2008.
[39] A. Talebi and A. W. A. Krzymien, “Optimized power allocation for multiple-antenna multi-relay
cooperative communication system,” IEEE International Conf. on Spread Spectrum Techniques
and Applications, pp. 222-226, Aug. 2008.
[40] H. Katiyar, R. Bhattacharjee and B. S. Paul, “User cooperation in TDMA wireless system,”
IETE Technical Review Journal, vol. 25, pp. 270-6, Sep. 2008.
[41] H. Katiyar and R. Bhattacharjee, “Performance of MRC combining multi-antenna co-operative
relay network,” AEU - International Journal of Electronics and Communications (Elsevier), vol.
64, no. 10, pp. 988-91, 2010.
[42] R. Bhattacharjee and H. Katiyar, “Outage performance of two-hop multi-antenna co-operative
relaying in Rayleigh fading channel,” IEEE Electronics Letters, vol. 45, no.17, pp. 881-3, Aug.
2009.
[43] H. Katiyar and R. Bhattacharjee, “Average error rate of multi-antenna decode and forward
cooperative relay network,” IEEE INDICON, DAIICT Ahmadabad, pp. 18-20, 2009.
[44] R. Bhattacharjee and H. Katiyar, “Performance of two-hop regenerative relay network under
correlated Nakagami-m fading at multi-antenna relay,” IEEE Commun. Letters, vol. 13, no. 11,
pp. 820-2, Nov. 2009.
[45] H. Katiyar and R. Bhattacharjee, “Outage performance of multi-antenna relay co-operation in the
absence of direct link,” IEEE Commun. Letters, vol. 15, no. 4, pp. 398-400, Apr. 2011.
[46] M. Xiao and M. Skoglund, “Multiple-user cooperative communications based on linear network
coding,” IEEE Trans. on Commun., vol. 58, no. 12, pp. 3345-51, Dec 2010.
[47] B. Schein and R. Gallager, “The Gaussian parallel relay network,” pp. 22, June 2000.

125
[48] J. N. Laneman, G. W. Wornell, and D. N. C. Tse, “An efficient protocol for realizing
cooperative diversity in wireless networks,” IEEE Intern. Symposium Information Theory, pp.
294, June 2001.
[49] A. E. Gamal and T. Cover, “Capacity theorems for the relay channel,” IEEE Trans. on
Information Theory, vol. IT-25, no. 5, pp. 572–584, Sep. 1979.
[50] G. D. Menghwar and C. F. Mecklenbräuker, “Cooperative versus non-cooperative
communications,” in 2nd International Conference on Computer, Control and Communication,
2009 (IC4 2009), Karachi, Pakistan, Feb. 2009.
[51] K. Alexopoulos, “Performance Analysis of Decode-and-Forward with Cooperative Diversity and
Alamouti Cooperative Space-Time Coding in Clustered Multihop Wireless Networks,” N.P.S
Monterey California, 2008.
[52] K. J. Rayliu, A. K. Sadek, Weifengsu, and Andres Kwasinski, “Cooperative Communications
and Networking,” Cambridge University Press, ISBN-13 978-0-511-46548-2, 2009.
[53] G. Kramer, M. Gastpar and P. Gupta, “Co-operative strategies and capacity theorems for relay
networks,” IEEE Trans. on Information Theory, 51(9):3037–306, pp. 3037-3063, Sept. 2005.
[54] M. Janani, A. Hedayat, T. E. Hunter and A. Nosratinia, “Coded cooperation in wireless
communications: space-time transmission and iterative decoding,” IEEE Trans. on Signal
Processing, 52:362–370, February 2004. pp. 362-371.
[55] E. Peh and Y. C. Liang, “Optimization for co-operative sensing in cognitive radio networks”,
IEEE Wireless Commun. and Networking Conference, pp. 27-32, Mar. 2007.
[56] Y. Q. Zhang, “Cross-layer design for QoS support in multi-hop wireless networks”, IEEE Trans.
on Signal Processing, vol. 96, no. 1, pp. 64-76, Jan. 2008.
[57] A. Nosratinia, T. E. Hunter and A. Hedayat, “Cooperative Communication in Wireless
Networks,” IEEE Commun. Magazine, vol. 42, no. 10, pp. 74-80, 2004.
[58] Mischa Dohler, Yonghui Li, “Cooperative Communications Hardware, Channel & Phy,” John
Wiley & Sons, 2010 ISBN 978-0-470-99768-0
[59] Eun Cheol Kim and Jae Sang Cha, “Successive interference cancellation for cooperative
communication systems,” International Conference on Hybrid Information Technology, 2009,
pp. 652-656.
[60] Kuang-Hao Liu, Hsiang-Yi Shin and Hsiao-Hwa Chen, “Interference-resistant cooperative
wireless networks based on complementary codes,” John Wiley & Sons, 2009.
Authors
Juhi Garg was born in India on July 12, 1989. She received her B. Tech. Degree
in Electronics and Communication Engineering from A.C.E.I.T., Jaipur
(University RTU, KOTA), Rajasthan, India in 2011 and currently is a M. Tech.
(Signal Processing) student in Mody Institute of Technology and Science (MITS,
Deemed University), Rajasthan, India.
Priyanka Mehta was born in India on December 4, 1989. She received her B.
Tech. Degree in Electronics and Communication Engineering from Marudhar
Engineering College, Bikaner (University RTU), Rajasthan, India in 2010 and
currently is a M. Tech. (Signal Processing) student in Mody Institute of
Technology and Science (MITS, Deemed University), Rajasthan, India.

126
Kapil Gupta was born in Kota (Rajasthan), India in 1980. He received his B.E.
(Hons.) degree in Electronics & Communication Engineering in 2003 from RU
and M.E. (Hons.) degree in Digital Communication from JNV University,
Jodhpur, Rajasthan in 2008. He is an Assistant Professor of Mody Institute of
Technology and Science (Deemed University), Lakshmangarh and has 7 years
of experience in teaching. His research interests are in Digital Communication
over fading channel and Error correction codes.

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