HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION
FACULTY OF HIGH-QUALITY TRAINING

REPORT
cooperative network

COOPERATIVE NETWORK

Name of Students

Student ID

Nguyễn Phúc Tiến

19161030

HO

CHI MINH
CITY

UNIVERSITY OF TECHNOLOGY AND EDUCATION


FACULTY OF HIGH QUALITY TRAINING

REPORT

COOPERATIVE NETWORK

Name of Students

Student ID

Nguyễn Phúc Tiến

19161030

Ho Chi Minh City, 12th, December, 2021


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TABLE OF CONTENTS


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LIST OF FIGURES
Chapter 1

Chapter 2

LIST OF ABBREVIATION
Multiple-input, multiple-output (MIMO)
Frequency modulation (FM)
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Two-wave with diffused power (TWDP)
Amplify-and-Forward (AF).
Decode-and-Forward (DF).
Compress-and-Forward (CF)
Signal-to-noise ratio (SNR)
Multi-hop Decode-and-Forward (MDF)

Orthogonal frequency-division multiplexing (OFDM)
single frequency networks (SFNs)
Diversity DF (DDF)
adaptive relaying protocol (ARP)
fractional incremental relaying (FIR)
negative acknowledgment (NACK)
acknowledgment (ACK)
Maximal Ratio Combining (MRC)
carrier-to-noise ratio (CNR)
Equal-gain Combining (EGC)
wireless ad hoc network (WANET)
Wireless sensor networks (WSNs)
Multi-hop Amplify-and-Forward (MAF)
Switched Combining (SWC)

Selection Combining (SC)
Very high frequency (VHF)
Ultra high frequency (UHF)

INTRODUCTION
Data communication over wireless networks is a field that is gradually advancing
in both directions. magic and applicability. This is the spearhead in the information
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and communication industry now and in the future. However, the transmission of
information through radio channels is not guaranteed for many reasons such as
weather and terrain. In practice, the signal is transmitted from the transmitter to the

receiver along many different paths, causing random fluctuations in the amplitude,
phase, and angle of incidence of the received signal, a phenomenon known as
multipath fading. The influence of multipath fading on signal transmission quality is
very large. This problem has received a lot of research attention and various methods
have been proposed to limit the effect of this fading such as using diversity
techniques. MIMO... However, with each method there are disadvantages. This report
will present another method to reduce the effects of fading, which is Multi-hop
Communication, which is a relatively new technique. The main idea of this technique
is to split the transmission path between the source node and the destination node by
using intermediate nodes in the middle (relay) to relay the signal. Node relay in
addition to signal transmission is also responsible for amplifying and transmitting,
decoding, and transmitting to expand the coverage area. improve the quality of the
system. This is also an issue worthy of attention and research.

CHAPTER I: WIRELESS CHANNEL MODEL
1.1 Path Loss

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1.1.1 Theory
The decline in power density (attenuation) of an electromagnetic wave as it
propagates over space is known as path loss or path attenuation. Path loss is an
important factor to consider while analyzing and designing a telecommunication
system's link budget.
In wireless communications and signal propagation, this word is frequently used.
Free-space loss, refraction, diffraction, reflection, aperture-medium coupling loss, and
absorption are all possible causes of path loss. Terrain contours, environment (urban

or rural, flora and foliage), propagation medium (dry or wet air), distance between
transmitter and receiver, and antenna height and position are all factors that affect path
loss.

1.1.2 Cause
Path loss typically includes propagation losses due to the natural expansion of the
radio wave front in free space (which usually takes the shape of an ever-increasing
sphere), absorption losses (also known as penetration losses) when the signal passes
through media that are not transparent to electromagnetic waves, diffraction losses
when part of the radiowave front is obstructed by an opaque obstacle, and losses due
to other phenomena.
Path loss typically includes propagation losses due to the natural expansion of the
radio wave front in free space (which usually takes the shape of an ever-increasing
sphere), absorption losses (also known as penetration losses) when the signal passes
through media that are not transparent to electromagnetic waves, diffraction losses
when part of the radio wave front is obstructed by an opaque obstacle, and losses due
to other phenomena.

1.2 Shadowing
The route loss model discussed in the preceding section seeks to calculate the
path loss in a deterministic manner for a given transmitter and receiver position. In
actuality, the position of a receiver includes the topography as well as the objects that
surround the transmission line. Measurements were taken under a variety of
situations, with statistical variances noted. Different levels of the received signal
power were measured at a certain frequency and distance. As a result, the received
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signal power is not predictable for a given fixed distance, frequency, and transmission
power, but fluctuates according to objects in and surrounding the signal path.
Shadowing is the name for these stochastic, location-dependent changes. It's worth
noting that these stochastic fluctuations are constant in time as long as the receiver
and his surroundings remain stationary. The term "shadowing" refers to the disparity
between the observed received signal strength and the theoretical value estimated
using route loss calculations. However, averaging numerous received signal power
levels for the same distance produces the precise route loss value.
The fluctuations of the recorded signal level compared to the average anticipated
route loss were determined using path loss measurements for a variety of settings and
distances. It has a normal distribution with a 0 mean in decibels, implying a lognormal distribution of received power around the path loss mean value.
The Kolmogrov-Smirnov test was used to verify this hypothesis, and it was
confirmed to be valid with large confidence intervals. The theoretical underpinning
for the log-normal distribution is that in an environment with surrounding objects,
different signals travel across the propagation medium with random re ections and
diractions. The additional loss in each path, expressed in decibels, is equal to
subtracting a random loss from the path loss value. The total of all the dB losses for a
large number of propagation pathways converges to a normally distributed random
variable (central limit theorem) since the different propagation paths are independent.
This becomes a log-normal distribution in natural units.
The path loss shadowing fluctuations may thus be computed from the distribution.

where is the signal's variability and all variables are measured in decibels. To obtain
the variations, the value of the variation due to shadowing is added to the path loss
value.

1.3. Fading
Fading is the fluctuation of a signal's attenuation with numerous factors in
wireless communications. Time, geographic location, and radio frequency are among
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the factors. Fading is frequently shown as a chaotic process. A communication
channel that fades is known as a fading channel. Fading in wireless networks can be
caused by multipath propagation (also known as multipath-induced fading), weather
(especially rain), or shadowing from barriers impacting wave propagation (also
known as shadow fading).
Fading is the fluctuation of a signal's attenuation with numerous factors in
wireless communications. Time, geographic location, and radio frequency are among
the factors. Fading is frequently shown as a chaotic process. A communication
channel that fades is known as a fading channel. Fading in wireless networks can be
caused by multipath propagation (also known as multipath-induced fading), weather
(especially rain), or shadowing from barriers impacting wave propagation (also
known as shadow fading).
Stopping at a traffic light and hearing an FM broadcast degrade into static is a
classic example of deep fade, as the signal is re-acquired if the car drives only a
fraction of a meter. The truck came to a halt at a spot where the signal was subjected
to strong destructive interference, resulting in the loss of the transmission. Similar
brief fades can also be seen on cellular phones.
In cellular networks and broadcast communication, fading channel models are
frequently used to simulate the effects of electromagnetic transmission of information
over the air. Fading channel models are often used to mimic the distortion induced by
the water in underwater audio communications.

1.3.1 Models of fading:
1.3.1.1 Nakagami distribution:
The Nakagami distribution, also known as the Nakagami-m distribution, is a
gamma-like probability distribution. There are two parameters in the Nakagami

distribution family: a shape parameter a second parameter that controls spread

The Nakagami distribution is a relatively recent concept, having been suggested
for the first time in 1960. It has been used to analyze the influence of fading channels
on wireless communications and to model attenuation of wireless signals travelling
numerous pathways
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1.3.1.2 Rayleigh fading:
Rayleigh fading is thought to be a good model for tropospheric and ionospheric
signal propagation, as well as the influence of densely populated metropolitan settings
on radio transmissions. When there is no dominating propagation along a line of sight
between the transmitter and receiver, Rayleigh fading is most useful. Rician fading
may be more appropriate if there is a dominant line of sight. Two-wave with diffused
power (TWDP) fading is a specific instance of Rayleigh fading.
This random variable, R, will have the following probability density function:

A complex number is frequently used to indicate the gain and phase aspects of a
channel's distortion. The assumption that the tangible and intangible sections of the
response are described by independent and identically distributed zero-mean Gaussian
processes, with the amplitude of the response being the sum of two such processes,
results in Rayleigh fading in this situation.
Rayleigh fading can be a helpful model in strongly built-up city centers when
there is no line of sight between the transmitter and the receiver and numerous
buildings and other things attenuate, reflect, refract, and diffract the signal due to the
demand for multiple scatterers. Near-Rayleigh fading has been discovered in
Manhattan as a result of experimental study. [3] Many particles in the atmospheric

layers operate as scatterers in tropospheric and ionospheric signals transmission, and
this type of environment may also resemble Rayleigh fading. If the environment is
such that there is a substantially dominant signal visible at the receiver in addition to
the scattering, which is commonly induced by a line of sight, the mean of the random
process will no longer be zero, but will instead fluctuate about the power-level of the
dominant path. Rician fading is a better term for this circumstance.
Rayleigh fading is a small-scale phenomenon. The fading will be placed on the
environment's bulk qualities, such as path loss and shadowing.
The speed with which the receiver and/or transmitter move will determine how
quickly the channel fades. The received signal components undergo a Doppler shift as
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a result of motion. The figures depict a constant signal's power change over one
second after travelling via a single-path Rayleigh fading channel with a maximum
Doppler shift of 10 Hz and 100 Hz. At 1800 MHz, one of the operational frequencies
for GSM mobile phones, these Doppler shifts correspond to velocities of roughly 6
km/h (4 mph) and 60 km/h (40 mph). This is the classic Rayleigh fading form. 'Deep
fades,' where signal strength might drop by a factor of thousands, or 30–40 dB.

1.3.1.3 Rician fading:
Rician fading, also known as Ricean fading, is a stochastic model for radio
propagation anomalies induced by partial cancellation of a radio signal by itself – the
signal arrives to the receiver through many routes (thus multipath interference), at
least one of which is changing (lengthening or shortening). When one of the
pathways, usually a line of sight signal or some powerful reflection signals, is
substantially stronger than the others, Rician fading develops. The amplitude gain in
Rician fading is defined by a Rician distribution.

When there is no line of sight signal, Rayleigh fading is sometimes considered a
specific example of Rician fading. The Rician distribution, which characterizes the
amplitude gain in Rician fading, becomes a Rayleigh distribution in this situation.
Two-wave with diffuse power (TWDP) fading is a specific instance of Rician fading.

1.3.2 Mitigation
Fading can degrade the performance of a communication system by causing a
decrease in signal power without lowering the noise power. This signal loss might
occur throughout a portion or the entirety of the signal bandwidth. Communication
systems are frequently built to adjust to such deficiencies, although fading can change
quicker than improvements can be implemented. In such instances, the likelihood of a
fade (and the associated bit errors as the signal-to-noise ratio lowers) on the channel
becomes the link's performance limiting factor.
Fading can be mitigated by transmitting the signal across numerous channels,
each of which experiences separate fading, and then coherently merging them at the
receiver. The likelihood of seeing a fade in this composite channel is thus proportional
to the probability of seeing a fade in all of the component channels at the same time,
which is a far more rare scenario.

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1.3.2.1 MIMO
Multiple-input, multiple-output, or MIMO, is a method for doubling the capacity
of a radio connection by using multipath propagation by using multiple transmitting
and receiving antennas. MIMO has become a key component of wireless
communication technologies such as IEEE 802.11n (Wi-Fi 4), IEEE 802.11ac (Wi-Fi
5), HSPA+ (3G), WiMAX, and LTE (LTE). As part of the ITU G.hn standard and the

HomePlug AV2 specification, MIMO has recently been used to power-line
communication for three-wire setups.
The term "MIMO" used to refer to the usage of multiple antennas at the
transmitter and receiver in wireless communications. In current usage, "MIMO" refers
to a viable technology for sending and receiving multiple data signals over the same
radio channel at the same time by taking advantage of multipath propagation.
Although the "multipath" phenomena is intriguing, the increase in data capacity is due
to the use of orthogonal frequency division multiplexing to encode the channels.
MIMO is fundamentally distinct from smart antenna methods like beamforming and
diversity, which were designed to improve the performance of a single data
transmission.

Figure 1. 1: MIMO system

1.3.2.2 OFDM
Orthogonal frequency-division multiplexing (OFDM) is a sort of digital
transmission and a way of encoding digital data on multiple carrier frequencies that is
used in telecommunications. OFDM is a widely used wideband digital
communication technique, with applications including digital television and audio

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broadcasting, DSL internet access, wireless networks, power line networks, and
4G/5G telecommunications equipment.
OFDM is a frequency-division multiplexing (FDM) method developed by Bell
Labs' Robert W. Chang in 1966. In OFDM, data is carried in parallel by many closely
spaced orthogonal subcarrier signals with overlapping spectra. Fast Fourier transform

methods are used in demodulation. Weinstein and Ebert enhanced OFDM in 1971 by
introducing a guard interval, which increased orthogonality in multipath propagationaffected transmission channels. At a low symbol rate, each subcarrier (signal) is
modulated using a traditional modulation strategy (such as quadrature amplitude
modulation or phase-shift keying). In the same bandwidth, this keeps overall data
speeds comparable to standard single-carrier modulation techniques.
The capacity of OFDM to cope with harsh channel circumstances without the use
of sophisticated equalization filters is its major benefit over single-carrier systems.
Because OFDM uses numerous slowly modulated narrowband signals rather than a
single rapidly modulated wideband signal, channel equalization is simpler. The low
symbol rate allows for the use of a guard interval between symbols, allowing for the
elimination of due to interference (ISI) and the use of reverberations and timespreading (visible as ghosting and blurring in digital audio television, respectively) to
achieve diversity order, or a transmission ratio improved performance. This
mechanism also makes it easier to create single frequency networks (SFNs), in which
two or more adjacent transmissions send the same signal at the same frequency at the
same time, because the signals from multiple faraway transmitters can be
cooperatively recombined, avoiding the interference that a traditional single-carrier
system would cause.

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CHAPTER II: COOPERATIVE COMMUNICATION
2.1. Cooperative Communication Protocol
Consider the three-node network in Figure, where the source is connected to a
relay and a destination, and the channels between the nodes are hsr, hsd, and hrd,
respectively. The relay can now assist in the transmission of information in a variety
of ways.


Figure 2. 1: The fundamental relay channel

The relay amplifies the received signal by a specific factor and retransmits it in
Amplify-and-Forward (AF). The relay decodes the packet and then re-encodes and
retransmits it in Decode-and-Forward (DF). In Compress-and-Forward (CF), the relay
makes a quantized (compressed) version of the signal it receives from the source and
sends it to the destination, where it is combined with the directly transmitted signal
from the source. In the following, we'll assume that all relaying nodes work in halfduplex mode, which means they can't send and receive in the same frequency range at
the same time. This is understandable because wireless signal transmit and receive
levels are sufficiently dissimilar that the sent signal would "swamp" the RX, making it
difficult to identify the receive signal.
These relay processing methods may now be paired with a variety of transmission
protocols that specify when and from which nodes certain information blocks are
transferred. We've arranged them in ascending order of performance (and at the same
time of increasing complexity).

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2.1.1 Decode-and-Forward
DF is the most essential of all the relaying techniques. Before re-encoding and retransmitting a packet, the relay receives it and decodes it, removing the impacts of
noise. Following that, we'll look at the capacity of a few of the implementations.
Multi-hop Decode-and-Forward is the most straightforward strategy to examine
(MDF). If we assume constant transmit power and equal time splitting between the
two phases, the overall data rate per unit bandwidth is

Ps and Pr are the source and relay powers, respectively, while Pn is the noise
power. In other words, the link with the lowest Signal-to-Noise Ratio SNR becomes

the "bottleneck" that decides total capacity; the half-duplex limitation is responsible
for the factor 1/2. The capabilities of the source-relay and relay-destination links are
terminology used inside the min operation. A data packet must travel through both
lines for a transmission to be successful; the link with the lower capacity is thus the
bottleneck that determines the possible trans- mission rate.
The values of Ps and Pr can be fixed or can be optimized given the power
constraints and the values of the channel coefficients hsr and hrd. In the latter case the
powers should be adjusted in such a way that the capacity of the source-relay link is
the same as the one for the relay-destination link, i.e.,

Further improvements to this approach (as well as the ones discussed below) can
be made by separating a data transmission time slot into unequal portions and
optimizing the length of those two sections.
The destination listens throughout both phases of Diversity-Decode-and-Forward
(DDF), allowing it to sum up the signals received from the source (phase 1) and the
relay (in phase 2). Then there are two significant examples to consider:
1. Repetition coding transmission from the relay: in this situation, the relay
employs the same encoder as the source. As a consequence, the source can add up the
received signals before decoding, improving the SNR. Assume that the subsequent
restriction transmission is successful only if the message from both the source and the

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relay is received successfully by the destination. In that situation, the greatest pace
that may be achieved is

and its best power distribution is


A smarter protocol would only use the relay if it can genuinely aid, otherwise it
would be idle. Adaptive DDF is the name of such a protocol. "Incremental relaying,"
in which the relay does not send if the destination can already decode the packet after
the first transmission phase, achieves even greater performance.
2. Transmission from the relay using incremental-redundancy encoding: the relay
decodes the packet and re-encodes it using a different coder in this scenario.
Intuitively, the RX can sum the mutual information from the two transmission phases
– in other words, it perceives a low-rate code in which certain information bits and
parity-check bits come in the first phase and some in the second. Such a protocol's
capability is

We define the entire system as being in outage if the attainable rate falls below
the required threshold Rth, using the idea of outage capacity. In the case of
nonadaptive DDF, the likelihood of such an outage is

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The first term on the right-hand side corresponds to the case where the sourcerelay connection is too weak (since the protocol requires the relay to transmit in the
second phase anyway, this causes an outage), and the second term corresponds to the
case where the source-relay connection is strong enough, but the relay-destination and
source-destination connections are too weak to sustain sufficient information flow to
the destination. Because the system's numerous linkages are independent, the
probabilities add up. If all of the connections are Rayleigh fading, the first component
dominates in the limit of large SNRs since it only gives diversity order 1; the second
term vanishes if either the source-relay or the relay-destination link is of sufficient
quality. The overall diversity order 1 is due to the protocol's requirement that the

source-relay link be of sufficient strength. Diversity order 2 may be accomplished
using adaptive DDF: two independent pathways (source-destination or source-relaydestination) are available, and transmission is successful if any of those paths delivers
sufficient quality.

2.1.2 Amplify-and-Forward
The essential premise of AF is that the relay amplifies the (noisy) signal yr that it
receives with a gain; yr is not manipulated in any other way (like decoding,
demodulating, etc.). The AF processing at the relay is thought to cause a half-time slot
delay. 5 Thus, the signal received at the destination in the first phase is just the
(attenuated) signal from the source plus noise (additional words exist for Intersymbol
interference Amplify-and-Forward (IAF), which we will not discuss further). The
signal in the second phase is the sum of the source's direct signal and the relay's
signal, which is the amplified source word from the previous phase. that position:

where xs and x2 signify the source and relay transmit signals, respectively, superscript
(1) and (2) denote the first and second transmission phases, respectively, and nr and
nd imply noise at the relay and destination, respectively (xs(2) can be zero, depending
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on the protocols given above). Power limits limit the amplification factor. We demand
that if there is an immediate power limitation,

The limitation must be averaged across the fading realizations in the case of an
instantaneous power constraint. 5 The delay of a completely analog repeater is
actually considerably lower in practice.
Despite the scheme's apparent simplicity, there are a variety of alternative protocol
implementations, as seen in the categorization above. Let's look into Multi-hop

Amplify-and-Forward (MAF) performance with Pr = Ps = P first. During the first
phase, the signal arriving at the RX is just the source signal multiplied by the channel
coefficient hsd, and the noise has variance Pn. The signal arriving at the destination in
the second phase is the source signal multiplied by hsrhrd, and the noise has variance.

As a result, the SNR is simply = P|hsrhsd|2 /P’ However, in MAF, the optimal power
allocation is provided by

We want to combine the signals from the two phases in Diversity-Amplify-andForward (DAF) to maximize the SNR, i.e., we want to do maximum-ratio combining.
As a result, the first phase's signal must be increased by

i.e., phase-adjusted and multiplied by the square root of the receive SNR at that time.
The signal from the second phase must be amplified by using a similar motive.
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The equivalent SNRs for the two phases, assuming Ps = Pr = P, are

And

As always with Maximum Ratio Combining (MRC), the total SNR = 1 + 2. The
capacity as a result is log2(1 + ), where the factor 1/2 comes from the relay's halfduplex limitation. The method also exhibits diversity order 2 since the signal might
reach the target through two separate paths: directly or through the relay. However,
the direct approach is not particularly beneficial for coverage extension relays with
reasonable SNRs (as opposed to the infinite SNRs used for diversity order
calculations) — if we could get good reception with the direct way, we wouldn't need
the relay in the first place.


2.1.3 Compress-and-Forward
CF and AF are similar in that the relay does not decipher messages but instead passes
everything it gets (including noise). The forwarded signal is a quantized, compressed
version of the signal received at the relay, which is the major distinction from AF. The
quantization and compression process may be viewed as a source encoding issue, in
which the received signal is a (analog) source whose information should be encoded
into a digital signal with as few distortions as feasible – but the rate at which that
signal can be delivered is restricted (and depends on the relay-destination channel).
This signal is combined with the signal received directly from the source node at the
destination to rebuild the original signal.
For some channel configurations, CF has been demonstrated to provide more capacity
than DF or AF. It is, however, far more involved than any of those forms, and as a
result, it will not be discussed further in this essay. The sources listed at the
conclusion of the chapter provide more information.
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2.3 Cooperative Relaying Protocols:
2.3.1 Adaptive Relaying Protocols:
A simple adaptive relaying protocol (ARP) that combines the benefits of both the
DF and AF protocols while minimizing their drawbacks. All relays in the proposed
scheme are assigned to one of two relay groups: the DF relay group or the AF relay
group. The DF relay group contains all relays that can successfully decode the signals
delivered from the source, whereas the AF relay group contains all relays that cannot
decode the signals correctly. The AF relay group's relays all amplify and transmit the
received signals from the source, whereas the DF relay group's relays decode, reencode, and forward the received signals to the destination. The ARP is processed in
the same way as the AF and DF at the destination. All signals sent from the relays in
both the AF and DF groups arrive at the destination and are merged into one signal.

The source data can then be recovered using a Viterbi decoding technique. The
suggested ARP's performance is evaluated and compared to that of other relaying
protocols. It is demonstrated that the suggested ARP method outperforms the AF
scheme and avoids error propagation caused by faulty decoding at relays in a DF
protocol, therefore outperforming both the AF and DF protocols. At high signal to
noise ratios, this performance benefit improves as the number of relays increases, and
eventually approaches perfect DTC (SNR).

2.3.2 Incremental Relaying
Feedback from the destination concerning the success or failure of direct
transmission is utilized in incremental relaying. Only when direct transmission fails is
the relay allowed to send the signal; otherwise, the source proceeds with the next
message, decreasing the total time for transmission from two to one time slot. The
spectral efficiency of incremental relaying improves. Incremental relaying protocols,
also known as hybrid automatic-repeat-request protocols, are extensions of
incremental redundancy techniques (ARQ). By re-transmitting partial information
from relays, the fractional incremental relaying (FIR) protocol enhances spectral
efficiency even more. If the destination is unable to decode the packet correctly, as
signaled by a negative acknowledgment (NACK) from the destination, the relay
breaks the received packet into fractions and transmits a fraction. The relay continues

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to deliver the next fraction until it receives an acknowledgement (ACK) from the
destination or reaches the maximum number of relay transmissions.

2.4 Combining Strategies

There are two types of combining techniques used to integrate several diversity
branches in the reception: post-detection combining and pre-detection combining. In
pre-detection combining, the signals from diversity branches are merged coherently
before detection. Signals, on the other hand, are detected independently before being
combined in post-detection. For both combining strategies for coherent detection, the
communication system's performance is same. However, employing pre-detection
combining for non-coherent detection improves the performance of the
communication system. In the case of coherent modulation, this means that the kind
of combining technique has no influence on performance. In non-coherent detection,
post-detection combining is not difficult, and the findings are widely used.

2.4.1 Maximal Ratio Combining (MRC):
To fight channel fading, this is a highly helpful combining technique. In
comparison to other ways, this is the best combining procedure for achieving the best
performance improvement. The MRC is a widely used combining method for
improving performance in noise-limited communication systems in which the AWGN
and fading are independent among the diversity branches. The MRC, on the other
hand, requires summing circuits, weighting, and co-phasing. Before summing or
combining, the signals from separate diversity branches are co-phased and weighted
in the MRC combining process. To maximize the overall carrier-to-noise ratio, the
weights must be proportionate to the separate signal levels (CNR). The weighting
used to the diversity branches must be changed based on the SNR.
It is possible to use MRC in the transmit diversity transmission method. However,
in this instance, the transmitter should get accurate feedback on the condition of the
sub-channels between a single receive antenna and numerous transmit antennas. In a
mixed transmit-receive diversity channel, however, it is not possible to weight
broadcasts from many antennas appropriately for each receiving antenna.
Furthermore, if a communication system's interference is minimal, a method that
mixes the diversity branches in order to optimize the signal-to-interference-plus-noise
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ratio may give significantly greater performance than MRC. If we can see noise
power at the receiver where only thermal noise is accounted for, the assumption holds
true for spatially white Gaussian noise. The thermal noise power is uncorrelated and
equal for each branch if we utilize the same type of antenna components.

Figure 2. 2: Maximal Ratio Combining

2.4.2 Equal-gain Combining (EGC):
The most optimal diversity combining strategy is MRC, however it necessitates a
highly costly receiver circuit design to adjust the gain in each branch. For the
sophisticated fading, it requires adequate tracking, which is extremely difficult to
perform realistically. It is, nevertheless, relatively simple to achieve equal gain
combining using a simple phase lock summing circuit. The EGC is identical to the
MRC except that it does not have the weighing circuits. Because there is an
opportunity to blend signals with interference and noise with high quality signals that
are interference and noise free, the performance improvement in EGC is slightly
smaller than in MRC.
In the reception of diversity, the EGC can use coherent modulation. In EGC,
diversity channels' envelope gains are ignored, and the diversity branches are
concatenated with equal weights but conjugate phase. Because the channel's envelope
gain is not estimated, the structure of equal-gain combining (EGC) is as follows.

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Figure 2. 3: Equal-gain Combining

2.4.3 Selection Combining (SC):
Very high frequency (VHF), ultra high frequency (UHF), and mobile radio
applications are not suited for MRC or EGC. In a constantly changing, multipath
fading, and random-phase environment, realizing a co-phasing circuit with accurate
and consistent tracking performance is difficult. Because of its ease of
implementation, SC is a better choice for mobile radio applications than MRC and
EGC. In SC, the signal level of the diversity branch with the highest signal level must
be chosen. As a result, the fundamental algorithm of this approach is based on the
notion of selecting the best signal from all the signals at the receiver end. Even in the
presence of a rapid multipath fading environment, steady operation is simple to
establish. It has been demonstrated experimentally that the performance advantage
realized by selection combining is only marginally higher than that provided by a
perfect MRC. As a result, the SC is the most widely utilized wireless communication
diversity approach.
The most common method of selection combining is to keep track of all the
diversity branches and choose the best one for detection (the one with the greatest
SNR). As a result, we may argue that SC is a selection technique at the available
diversity rather than a combining approach. SNR measurement, on the other hand, is
tough since the system must pick it in a short amount of time. When the average noise
power on each branch is the same, picking the branch with the greatest SNR is
comparable to selecting the branch with the highest received power. As a result,
choosing the branch with the most signal composition, noise, and interference is

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realistic. Selection combining can also be employed in transmission if feedback
information about the channel status of the diversity branch is available.

Figure 2. 4: Selection Combining

2.4.4 Switched Combining (SWC):
In selection combining, monitoring all diversity branches is impractical.
Furthermore, if we want to continually monitor the signals, we'll need the same
number of receivers and branches. As a result, selection combining is implemented
using the switched combining method. The best switching threshold in SWC must be
determined. When the threshold is set to a very high value, the rate of unwanted
switching transients rises. If the threshold is set too low, however, the variety benefit
will be minimal. In the case of frequency hopping systems, the switching of switch
combinations can be done on a regular basis.
The value of threshold selection, the time delay that results from the loop of
feedback of monitoring estimation, switching, and decision, and the performance
increase gained by the switching technique are all dependent on the value of threshold
selection. Furthermore, phase transients and a carrier's envelope might limit
performance increase. The phase transient is responsible for creating mistakes in the
detection stream of data in an angle modulation system, such as GSM. To eliminate
envelope transients in this scenario, a pre-detection band pass filter might be utilized.

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