In this paper an ad-hoc network having source, a destination and a third station which is a relay is analyzed. The channels used here are modeled having thermal noise, Rayleigh fading and path loss. Different methods for combining and diversity protocols are compared.

1. www.ijcsit-apm.com International Journal of Computer Science &Information Technology 1
IJCSIT, Vol. 1, Issue 1 (Jan-Feb 2014) e-ISSN: 1694-2329 | p-ISSN: 1694-2345
Improved Ad-Hoc Networks Using
Cooperative Diversity
Omkar Singh
Infosys Technologies, Chandigarh, India
omkar.technocrat@gmail.com
Abstract: In this paper an ad-hoc network having source, a
destination and a third station which is a relay is analyzed.
The channels used here are modeled having thermal noise,
Rayleigh fading and path loss. Different methods for
combining and diversity protocols are compared. Amplify
and forward protocol shows a better performance than
decode and forward protocol, unless an error correcting code
is simulated. To combine the incoming signals the channel
quality should be estimated as well as possible. Information
about the average quality shows nice benefits, and a rough
approximation about the variation of the channel quality
increases the performance even more. Whatever combination
of diversity protocol and combining method is used second
level diversity is observed. The relative distances between
the relay and the stations have a large effect on the
performance.
Keywords: Rayleigh fading, cooperative diversity, relay,
diversity protocols, combining methods, path loss.
I. INTRODUCTION
“The increasing demand for wireless multimedia and
interactive Internet services, along with rapid proliferation of
a multitude of communications and computational gadgets,
are fuelling intensive research efforts on the design of novel
wireless communication systems architectu1res for high
speed, reliable and cost effective transmission solutions” [2].
The introduction and rapid development of MIMO (multiple-
input and multiple-output) systems has promised significant
improvements in reliability and throughput for Ad hoc
networks; by utilizing multiple antennas at both the
transmitter and the receive side. However, this technique is
clearly advantageous for cellular base stations, but not
feasible for mobile devices, due to their sizes and power
constraints [1] [2]. An alternate to this is a newly developed
technique known as multi-user cooperative diversity that
allows a single antenna user to achieve transmit diversity
benefits by sharing their physical resources through a virtual
transmit and receive antenna array. The major benefit of this
technique includes the diversity – because different paths are
likely to fade independently, beam forming gain and
interference mitigation [1] [3].
II. FUNDAMENTALS
A. Introduction to Cooperative Relaying
We consider scenarios as depicted in Figure 1, which include
a single relay and where all nodes feature only a single
antenna. As is true for all relaying protocols, cooperative
relaying schemes suffer from the “orthogonality
constraint”2, calling for the assignment of orthogonal
resources for reception and transmission at the relay.
Without loss of generality, we focus on the time division
case and divide the available channel into two orthogonal
sub channels in the time domain. Note that in order to
achieve the same end-to-end spectral efficiency, we then
need to double the spectral efficiency on each of the
individual links in this case.
Fig. 1. Illustration of a cooperative relaying scenario.
The source sends a broadcast message to destination and
relay. The relay then forwards additional information about
the source message to the destination, which appropriately
Cooperative relaying protocols[5] can be classified
according to their forwarding strategy as:
1) Amplify-and-Forward: The relay acts as an analog
repeater, resulting in noise enhancement in the relay path.
2) Decode-and-Forward: The relay fully decodes, again
encodes and retransmits the received message, possibly
propagating decoding errors that may lead to a wrong
decision at the destination.
3) Decode-and-Reencode: The relay fully decodes the
received message, but constructs a codeword differing from
the source codeword – thus enabling parallel channel coding.
This approach can be seen as an distributed incremental
redundancy technique. The main problem is again error
propagation.
Protocols that require the relay to decode the received
message are clearly favorable for implementation purposes
since amplify-and-forward style protocols require either the
storage of large amounts of analog data (time division) or
complicated and expensive transceiver structures (frequency
division). The reader is referred to [4] for a detailed
discussion of advantages and disadvantages. We may further
categorize the transmission schemes based on the protocol
nature:
1) Fixed Protocols where the relay always forwards (a
processed version of) its received message,2) Adaptive
Protocols where the relay uses a threshold rule to decide
autonomously whether to forward or not, and
3) Feedback Protocols where the relay only assists the
transmission when explicitly required by the destination. A
combination of these options yields 9 different cooperative
relaying protocols. Static Amplify-and-Forward networks
have been extensively discussed in [6], a number of Amplify
and Decode-and-Forward protocols have been thoroughly

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investigated in [11] and Decode-and-Reencode protocols
have been the subject of evaluation in [9], [15].
B. Combining Type[6]
1. Equal Ratio Combining (ERC) : If computing time is a
crucial point, or the channel quality could not be estimated,
all the received signals can just be added up.
2. Fixed Ratio Combining (FRC): A much better
performance can be achieved, when fixed ratio combining is
used. Instead of just adding up the incoming signals, they are
weighted with a constant ratio, which will not change a lot
during the whole communication. The ratio should represent
the average channel quality.
3. Signal to Noise Ratio Combining (SNRC) A much
better performance can be achieved, if the incoming signals
are weighted on an intelligent way. An often used value to
characterize the quality of a link is the SNR, which can be
used to weight the received signals.
4. Maximum Ratio Combining (MRC) The Maximum
Ratio Combiner (MRC) achieves the best possible
performance by multiplying each input signal with its
corresponding conjugated channel gain. This assumes that
the channels' phase shift and attenuation is perfectly known
by the receiver
5. Enhanced Signal to Noise Combining (ESNRC):
Another combining method is to ignore an incoming signal
when the data from the other incoming channels have a
much better quality. If the channels have more or less the
same channel quality the incoming signals are rationed
equally.
III. RESULTS AND DISCUSSIONS
The performance of different combinations of the methods
are analyzed to illustrate their potential benefits. In this part,
it is assumed that the three stations (sender, relay and
destination) have an equal distance from each other and
therefore the same path loss and average signal-to-noise ratio
is assumed. With this equidistant arrangement the different
combining and amplifying types are compared to see their
advantages and disadvantages.
A. Equidistant Arrangement: In this section it is assumed,
that the three stations are arranged at the edges of a triangle
with a length of one. This means that all the channels will
have the same path loss and therefore the same average
signal-to-noise ratio
Amplify and Forward
To compare the benefits of the different combining method,
the optimal ratio for the FRC needs to be evaluated first. Fig.
3.1 illustrates the effects of the different weighting. In Fig.
3.2 the effect on the performance of the different combining
types using a AAF protocol can be seen. The first pleasant
result is that whatever combining type is used, the AAF
diversity protocol achieves a benefit compared to the direct
link. Even the equal ratio combining shows advantages. But
compared to the fixed ratio combining, the performance
looks quite poor. Otherwise you should call to mind that the
equal ratio combining does not need any channel
information, except the phase shift, to perform the
combining. The fixed ratio combining on the other hand,
needs some channel information to calculate the appropriate
weighting. The signal-to-noise ratio combining (SNRC) and
the enhanced signal-to-noise ratio combining (ESNRC)
show roughly the same performance, which is much better
then the one using FRC/ERC.Using the AAF protocol, there
is no point in wasting a lot of computing power and
bandwidth to get some exact channel information. And even
if the channel quality could not be estimated at all (and
therefore ERC is used), there is still a benefit using diversity.
Decode and Forward
The FRC is simulated with different weighting to estimate
the ratio that results in the best performance. The
simulations, illustrated in Fig. 3.3, show the best
performance when a ratio of 3:1 is used. It is quite surprising
that this ratio differs that much from the ratio using AAF.
Figure 3.1: To estimate the best ratio for FRC different ratios are
plotted.The ratio 2:1 gives a good result
Figure 3.2: The different combining types are compared with each
other. The best performance results when using SNRC/ESNRC.
The FRC with a ratio of 3:1 can now be used to compare
with the other combining methods. The different combining
methods using the DAF protocol are illustrated in Fig. 3.4
In contrast to the AAF protocol, a big benefit results using
one of the block analyzing combining methods
(SNRC/ESNRC). Using the DAF protocol shows now the
benefit estimating every single block separately and hence
using more computing power. There is now an additional
benefit, to estimate every block precisely when using SNRC,
instead of just approximating the channel quality combining
the signals with ESNRC. But considering that the achievable
benefit is about half a decibel it might not be worth wasting
the additional computing power and bandwidth which is

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required to get precise channel estimation. If AAF is used,
there is no benefit at all, using the SNRC instead of ESNRC.
Figure 3.3: To estimate the best ratio for FRC Different ratios are
plotted. The ratio 3:1 results in the best performance.
Figure 3.4: The different combining types are compared with each
other. The best performance results when using SNRC.
IV CONCLUSION
The AAF protocol has shown a better performance than the
DAF protocol whatever combining method was used at the
receiver. But it must be considered that no error correcting
code was added to the transferred signal. Therefore it was
not possible to take full advantage of the DAF protocol. To
get an idea of the potential of the DAF protocol the magic
genie was introduced to simulate an error correcting code.
The performance of a system using the DAF protocol in
combination with a magic genie was much
better than one using the AAF protocol.
REFERENCES
1. A. Nosratinia, T. E. Hunter, A. Hedayat, “Cooperative
Communications in Wireless Networks”, IEEE Communications
Magazine, 2004, pp. 74-80.
2. M. Uysal, “Cooperative Communications for Improved Wireless
Network Transmission”, Information Science Reference, July 2009.
3. G. K. Karagiannidis, C. Tellambura, S. Mukherjee, A. O.
Fapojuwo, “Editorial - Multi-user Cooperative Diversity for
Wireless Networks”, EURASIP Journal on Wireless
Communications and Networking.
4. E. Zimmermann. “On the cooperative exploitation of spatial
diversity in wireless networks”, Dresden University of
Technology, Vodafone Chair Mobile Communications Systems,
April 2003.
5. Ernesto Zimmermann, et al “On the Performance of Cooperative
Relaying Protocols in Wireless Networks”, Dresden University of
Technology, Vodafone Chair Mobile communications Systems,
Germany
6. Dr John Thompson et al “Cooperative Diversity in Wireless
Networks” in March 2004.