diversity techniques for wireless communication

International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 –

6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 2, March – April (2013), © IAEME

144

DIVERSITY TECHNIQUES FOR WIRELESS COMMUNICATION

Pravin W. Raut1, Dr. S.L. Badjate

2

L 1

Research Scholar, HOD ET Dept, Shri Datta Meghe Polytechnic, Nagpur

L 2 Vice Principal & Professor, S. B. Jain Institute of Technology, Management. & Research,

Nagpur

ABSTRACT

The users of the wireless communication demands for higher data rates, good voice

quality and higher network capacity restricted due to limited availability of radio frequency

spectrum, Bandwidth, Channel Capacity, physical areas and transmission problems caused by

various factors like fading and multipath distortion.

The wireless communication channel suffers from much impairment which leads

degradation of the overall system performance. There are many performance degradation

factors in wireless communication channels but FADING problem is the major impairment

problem.

This paper addresses the Diversity techniques which are the useful methods to reduce

fading problem in wireless communications. In diversity technique, the receiver is supplied

multiple replicas of transmitting signals instead of one signal that have passed over different

fading channels. As a result, the probability that all replicas of signals will fade

simultaneously is reduced considerably. The uncorrelated faded signals are collected from

diversity branches and combine in such manner that can improve the performance of

communication systems, called as diversity combining method to increase overall received

SNR. The best diversity techniques can be selected by analyzing and comparing the different

types of diversity techniques. Moreover, different diversity techniques can be combined and

used in wireless communication systems to get the best result to mitigate fading problems.

Keywords: Signal to Noise Ratio (SNR), Transmitter, Receiver, Fading, Diversity, multiple

Antenna, MIMO, Channel estimation.

INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN

ENGINEERING AND TECHNOLOGY (IJARET)

ISSN 0976 - 6480 (Print)

ISSN 0976 - 6499 (Online)

Volume 4, Issue 2 March – April 2013, pp. 144-160

© IAEME: www.iaeme.com/ijaret.asp

Journal Impact Factor (2013): 5.8376 (Calculated by GISI) www.jifactor.com

IJARET

© I A E M E



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I. INTRODUCTION

There are two types of communication systems such as wired communication and

wireless communication. The wired communication almost out of market and / or limited

use due to its various limitations. Wireless communication is divided into mobile

communications and fixed wireless communications. Each type of communication has

huge demand according to customers need in the market. Wireless data transmission

gives us every opportunity to get all feasible necessary access to the world wherever we

are and wherever we need from. The exceptional growth of the telecommunication

industry in recent years fueled by the widespread popularity of mobile phones, wireless

computer networking and continues to expand everyday with new technology invention.

This growth of wireless communication is restricted due to the limitations of

available frequency resources, bandwidth, channel capacity, complexity, reliability,

transmission data rate, physical areas and communication channel between transmitter

and receiver.

The transmission data rates can be increase by increasing the transmission

bandwidth or using higher transmitter power. But, from a practical point of view,

increasing the transmission bandwidth or the transmitter power is not always feasible due

to high system deployment costs. Moreover, increasing the transmit power results in an

increased interference to other transmissions and also reduces the battery life-time of

mobile transmitters.

The uncertainty or randomness is the main characteristic of wireless

communication which appears in user’s transmission channel and user’s location.

Wireless communication channels suffer from various factors but FADING problem is

the major impairment problem which leads the degradation of overall system

performance.

Fading means the loss of propagation experienced by the radio signal on forward

and reverse links. The signals which is received by mobile terminals come from several

propagation paths those are called multi-path propagation.

To improve the performance of those fading channels, diversity techniques are

used. In diversity technique, communication channel is supplied with multiple

Transmitting and Receiving antennas. The signal is transmitted and received through

multiple paths. As a result, the probability that all replicas of signals will fade

simultaneously is reduced considerably.

For getting full benefit, uncorrelated faded signals are collected from diversity

branches and combine in such manner that can improve the performance of

communication systems. This is called diversity combining method and also used to

optimize received signal power or signal-to-noise ratio (SNR). This combining method

can be used in receiver mainly.

The diversity techniques are classified under three domains namely, Temporal

diversity, frequency diversity and spatial diversity. Among these, due to its efficiency in

terms of system resource usage (no extra power and bandwidth utilization necessary)

spatial diversity with multiple transmitting and receiving antennas are most popular.

Spatial diversity provides a more robust and reliable communication, and by introducing

additional degrees of freedom to the system, it provides a higher system capacity without

requiring any additional power or bandwidth.



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II. PERFORMANCE DEGRADATION FACTORS IN WIRELESS COMMUNICATION

Following are the major performance degradation factors of wireless communication.

A. Characteristics of Wireless Communication Channel

The main characteristic of wireless communication is Uncertainty or randomness

which is of two types: randomness in user’s transmission channels and randomness in user’s

geographical locations causes random signal attenuation.

The behavior of the wireless communication channel is a function of the electromagnetic

(Radio) waves propagation effect in an environment. The information suffers attenuation

effects by several reasons which are called fading of radio waves. These attenuation effects

can vary with time and variations depends on user mobility, which makes wireless channel a

challenging medium of communication.

Also it is impossible to get proper Line Of Sight (LOS) or proper communicating nodes

because of some natural or constructive obstacles to establish a wireless communication link.

To overcome this problem, a transmission path is modeled randomly which has varying

propagation path in such an environment in which signal propagation over multipath made us

need to model wireless channels as wireless multi-path channels.

B. Factors Affecting the Wireless Communication Channel Wireless communication system sends the signal information through radio

propagation environment. The different copies of signal undergo different attenuation,

distortion, phase shift and delays during transmission.

The following impairments are responsible to the suffering of radio wave propagation and

hence the overall performance of wireless communication system.

� Path loss � Shadowing loss �Noise

� Interference � Channel spreading �Channel fading

(a) Path loss: The loss of power on the way of radio wave propagation in space is called as

Path Loss which attenuates the signal and depends on the distance between the

communicating nodes of the system and hence limits the coverage of a transmitter. In any

real channel, signals attenuate as they propagate. The path loss is given by

where ‘λλλλ’ is the wavelength of the signal and ‘d’ is the distance between the source and

the receiver (Communicating nodes). The power of the signal decays as the square of the

distance.

In land mobile wireless communication environments, similar situations are observed.

The mean power of a signal decays as the nth

power of the distance : L = c dn

where ‘c’ is a constant and the exponent ‘n’ typically ranges from 2 to 5. The exact

values of c and n depend on the particular environment.



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(b) Shadowing loss: The loss due to the presence of large-scale obstacles in the propagation

path of the radio signal is called as Shadowing loss. Due to the relatively large obstacles,

movements of the mobile units do not affect the short term characteristics of the shadowing

effect. Instead, the nature of the terrain surrounding the base station and the mobile units as

well as the antenna heights determines the shadowing behavior.

Usually, shadowing is modeled as a slowly time-varying multiplicative random process.

Neglecting all other channel impairments, the received signal r(t) ) is given by:

r(t)= g(t) s(t) where s(t) is the transmitted signal and g(t) is the random process which models the

shadowing effect.

For a given observation interval, we assume g(t) is a constant g, which is usually

modeled as a lognormal random variable whose density function is given by

Notice that ln g is a Gaussian random variable with mean µ and variance σ

2. This

translates to the physical interpretation that µ and σ2 are the mean and variance of the loss

measured in decibels due to shadowing.

(c) Noise : In radio wave propagation there are two types of noise, Natural noise and man-

made noise. The Main source of natural noise is the ignition systems of vehicles. However,

natural noise source such as galactic noise, solar, atmospheric noise, has less effect in land-

mobile communication systems but lots in radio channel. The noise generated in the

components in the communication systems also corrupt the received signals besides the

natural and man-made noise.

The characteristics of different noise sources are simply different but the noise process

most commonly and frequently modeled with Additive White Gaussian Noise (AWGN).

(d) Interference:

In radio system the source of interference can be originated at the system itself or located

at external source. The self-centered interference can be divided into two types: inter-cell and

intra-cell interface. The inter-cell interference comes from other mobile stations and it

normally approximately 60% of total interference in a radio system. In the uplink case, the

intra-cell interface comes from other mobile station cells.

There are two types of interference, such as: Inter-symbol-interference (ISI) and Co-

channel-interference (CCI)

Inter-Symbol-Interference (ISI):

When transmit, a small part of symbol overlap on the next symbol. It spreads more than

its normal extension and smeared into the next symbol and make the noise called as Inter

symbol interference (ISI) which is an unavoidable consequence introduced by the delay

spread in a propagating channel as shown in fig-1 (a) and 1 (b).

The original time of pulse is called is called Symbol time shown in fig 1-(a). ISI can be

controlled by slowing down the transmit data and also by using a maximum likelihood

sequence detector.



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Fig.1 (a)- The Transmitter symbols

Fig.1 (b)- The Received symbols

The next information pulse should send when the received signal damps down. The time

it takes to damp is called delay spread. To suppressed ISI, one can select a space-time filter

that equalizes the channel.

Co-Channel Interference (CCI): When the neighboring cells operate at the same frequencies then CCI occurs. This

scenario is shown in following fig 2. Some other factors responsible for CCI are insufficient

cross-polarization isolation, non-linearity of power amplifier, poor radiation from antenna

side lobs, faulty filtering etc.

The CCI can be suppressed by using an orthogonal space time filter to the interference

channels. Another method to solve this problem is the estimation of Time of Arrival (TOA)

which uses the synchronized time difference between original signal and the CCI signal. An

un-synchronized base station is used to suppressed the CCI signal and the signal without CCI

is received which has good voice quality and data quality.

Fig.2: Co-channel Interference scenario for neighboring base station



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(e) Channel Spreading: When information carrying signal energy spreads in space or concerning time or

frequency axis then such spreading of the signal is called as Channel Spreading.

The reason of spreading of signal energy in the space dimension, time or in the frequency

axis is due to Propagation of a radio wave from a user or to a user in multipath channel. The

design of receiver is affected by the characteristics of channel spreading.

There are two types of channel spreading such as : Doppler spread and Delay spread

Doppler Spread: Due to movement of the communicating device or other components in a multipath

propagation environment the information carrying radio signal experience a shift in

frequency domain. The shift in frequency domain is also called Doppler shift. The amplitude

of the Doppler shift is depends on the path direction of the signal arrival. Doppler shift is

much smaller than the carrier frequency and it is bounded to positive and negative amplitude.

For example, it can be seen that component waves arriving from ahead of the vehicle

experience a positive Doppler shift, while those arriving from behind the vehicle have a

negative Doppler shift .

The result of Doppler spread in the channel characteristics is that it change the channel

characteristics sharply in time, it gives rise to the so called time selectivity. The fading

channel can be considered as constant during the coherent time and the coherent time is

inversely proportional to the Doppler spread.

Delay Spread:

Sometimes, multipath propagation is characterized by different version of transmitted

signal arriving at the receiver attenuation factors and delays. When spreading in time domain

then it called delay spread and this is responsible for the selectivity of the channel in

frequency domain. The coherence bandwidth is inversely proportional to the delay spread.

The significant delay spread causes strong inter-symbol interference.

(f) Channel Fading : Fading in a channel is the propagation losses by radio signal on both forward and reverse

links. This impairment is a major problem of wireless communication channel. Fading

introduce for the combined effect of multiple propagation paths, high speed of mobile units

and reflectors.

In a typical wireless communication environment, multiple propagation paths often exist

from a transmitter to a receiver due to scattering by different objects. Signal copies following

different paths can undergo different attenuation, distortions, delays and phase shifts.

Constructive and destructive interference can occur at the receiver. When destructive

interference occurs, the signal power can be significantly diminished. This phenomenon is

called fading. The performance of a system (in terms of probability of error) can be severely

degraded by fading. The result is a time-varying fading channel. Communication through

these channels can be difficult. Special techniques may be required to achieve satisfactory

performance.

III. PARAMETERS OF FADING CHANNEL

The performance analysis of general time varying channel for wireless

communication channel is too complex to understand. Many practical wireless channels can



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be adequately approximated by the Wide-Sense Stationary Uncorrelated scattering (WSSUS)

model. In this model, the time varying fading is seems to be wide-sense stationary random

process and the signal copies from the scattering by different objects are assumed to be

independent. The following parameters are often used to characterize a WSSUS fading

channel.

1.Multi-path Spread, Tm This finds the maximum delay between paths of significant power in the channel. When

we send a very narrow pulse in a fading channel, the received power can be measured as a

function of time delay (fig 3.1).The average received power P(r) is called multi-path intensity

profile or delay power spectrum when � is a function of excess time delay. Sometimes, P(r)

is essentially non-zero over a range of values of a function of excess time delay �. Then it’s

called multipath spread of the channel, Tm.

Fig 3.1: Multipath delay profile

2. Coherent Bandwidth, (∆f)C Coherent bandwidth in channel gives us an idea how far signals should be separated in

frequency. In a fading channel, signals with different frequencies can undergo different

degrees of fading. If two frequency signals are separated by more than coherent bandwidth

then the signals may undergo different degrees of fading. The relationship between (∆f)C and

Tm is

3. Coherent Time (∆T)C

The coherent time identify the time duration over which the channel impulse is invariant

or highly correlated which is vary with time in a time varying channel. If the time duration is

smaller than the coherent time then the channel considerably invariant during the reception of

symbol.

4 Doppler Spread Bd A signal propagating in a channel may undergo frequency shift or Doppler shift due to its

time varying nature. If a bunch of frequency is transmitted through a channel, the received

power spectrum can be plotted against the Doppler shift according to figure3.2. called as

Doppler power spectrum. The Doppler spread is the range of the values where the Doppler

power spectrum is non-zero. Coherent bandwidth and Doppler spread is related by the

following equation:



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Fig 3.2 : Doppler Power Spectrum

5. Mean path loss The mean path loss describes the attenuation of a radio wave in a free space propagation

environment due to isotropic power spreading which is given by the inverse square law,

Where Pr and Pt are received and transmitted powers, λ is wavelength of the radio wave,

d is the range, Gt.Gr are gains of transmitter and receiver respectively.

The main path is accompanied sometimes by a surface reflected path which may

destructively interfere with the primary path. There is a model called path loss model is

developed to handle this effect.

Where ht and hr are the effective heights of transmitter and receiver respectively. This

path loss model built in according to an inverse fourth power law and the path loss exponent

may vary from 2.5 to 5 depending on the environment.

IV. CLASSIFICATION OF FADING CHANNEL

Based on the parameters of the channels and the characteristics of the signals to be

transmitted, time varying fading channels can be classified as:

Frequency non-selective versus frequency selective

While on comparing with Coherence Bandwidth (∆ƒ)c, all frequency components of the

signal would undergo fading of almost same amount if it is found that the transmitted

bandwidth of the signal is small. The channel is then classified as frequency non-selective

which is also called flat fading.

On the other hand, if the transmitted bandwidth of the signal is large in comparison to

Coherence Bandwidth (∆ƒ)c, then different frequency components of the signal (that differ

by more than Coherence Bandwidth (∆ƒ)c) would undergo fading of different degrees. The

channel is then classified as frequency selective.

Slow fading versus fast fading

If the symbol duration is small compared with Coherence Time (∆t)c, then the channel is

classified as slow fading. Slow fading channels are very often modeled as time-invariant

channels over a number of symbol intervals. The channel parameter of these varying, may be

estimated with different estimation techniques.

On the other hand, if (∆t)c is close to or smaller than the symbol duration, the channel is

considered to be fast fading (also known as time selective fading). In general, it is difficult to



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estimate the channel parameters in a fast fading channel. The fig4.1 and 4.2 shows the

comparison of slow and fast fading channel.

The above classification of a fading channel depends on the properties of the transmitted

signal. The above two ways of classification give rise to following four different types of

fading channel:

� Frequency non-selective slow fading

� Frequency selective slow fading

� Frequency non-selective fast fading

� Frequency selective fast fading

Fig 4.1: Slow fading Vs fast fading

Fig 4.2: Slow fading Vs fast fading

V. DIVERSITY TECHNIQUES

Diversity technique is used to decreased the fading effect and improve system

performance in fading channels. Instead of transmitting and receiving the desired signal

through one channel, we obtain L copies of the desired signal through M different channels.

The idea is that while some copies may undergo deep fades, others may not. We might still

be able to obtain enough energy to make the correct decision on the transmitted symbol.

Following are the types of diversity techniques.



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� Multipath/frequency diversity

� Temporal/time diversity

� Spatial/space diversity

� Polarization diversity

� Angle diversity

� Antenna diversity

Frequency / Multipath diversity: The diversity can be achieved by modulating information signal through L different

carrier frequencies (refer fig 5.1). Each carrier should be separated from the others by at least

the coherence bandwidth (∆f)c so that different copies of the signal undergo independent

fading.

This L independently faded copies are “optimally” combined at the receiver to construct the

original signal. The optimal combiner is the maximum ratio combiner, which will be

introduced later. Frequency diversity can be used to combat frequency selective fading.

Fig.5.1 : frequency Diversity

Time / Temporal diversity: Another approach to achieve diversity is to transmit the desired signal in L different

periods of time, i.e., each symbol is transmitted L times (refer fig 5.2). The intervals between

transmission of the same symbol should be at least the coherence time (∆T)c. so that different

copies of the same symbol undergo independent fading. Optimal combining can also be

obtained with the maximum ratio combiner. Notice that sending the same symbol L times is

applying the (L,1) repetition code. Actually, non-trivial coding can also be used. Error control

coding, together with interleaving, can be an effective way to combat time selective (fast)

fading.

Fig.5.2 : Time Diversity



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Spatial / Space diversity: This diversity techniques uses multiple antennas at the transmitting and Reception side

(refer fig 5.3). So L antennas to receive L copies of the transmitted signal. The antennas

should be spaced far enough apart so that different received copies of the signal undergo

independent fading. This is Different from frequency diversity and temporal diversity, no

additional work is required on the transmission end and no additional bandwidth or

transmission time is required. However, physical constraints may limit its applications.

Spatial diversity can be employed to combat both frequency selective fading and time

selective fading. The spatial diversity increased the SNR.

Fig.5.3: Spatial / Space Diversity

Polarization Diversity: In polarization diversity, the electric and magnetic fields of the signal carrying the

information are modified and many such signals are used to send the same information. Thus

orthogonal type of Polarization is obtained.

Angle Diversity/ Pattern Diversity / Direction Diversity: This diversity system needs a number of directional antennas those responds

independently to wave propagation. An antenna response to a wave propagates at a specific

angle and receives a faded signal which is uncorrelated with other signals.

The procedure to obtain angle diversity is to fix antennas with narrow beam widths

different sector in the system. Then the arriving multi-paths from the different beam

directions are resolved and combined advantageously. This procedure not only creates

diversity but also increases the antenna gain and reduces interference by providing angular

discrimination.

Antenna Diversity: Antenna diversity is a popular and extensively used technique to improve performance in

wireless communication systems. The technique reduces fast fading and inter-channel

interference effects in the wireless network system. In an antenna diversity system, two or

more antennas are used and fixed in positions which will provide uncorrelated signals with

the same power level. Then the signals are combined and created an improved signal. The

basic method of antenna diversity is that the antennas experiences different kind of signals

because of individual channel conditions and the signals are correlated partially. Then we can

expect that if one signal from one antenna is highly faded, other signals from other antennas

are not faded such way and these signals are our expected quality signals.



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VI. DIVERSITY COMBINING TECHNIQUES

It is important to combine the uncorrelated faded signals which were obtained from

the diversity branches to get proper diversity benefit. The combing system should be in such

a manner that improves the performance of the communication system like the signal-to-

noise ratio (SNR) or the power of received signal. Mainly, the combining should be applied

in reception; however it is also possible to apply in transmission. Following are the various

diversity combining methods available, out of these MRC,EGC and SC are mainly used.

� Maximal ratio combining (MRC)

� Equal gain combining (EGC)

� Selection combining (SC)

� Switched Combining (SWC)

� Periodic Switching Method

� Phase Sweeping Method

� Maximal Ratio Combining (MRC):

Fig 6.1 : Maximal-Ratio Combining (MRC)

In the MRC combining technique needs summing circuits, weighting and co-phasing.

The signals from different diversity branches are co-phased and weighted before summing or

combining. The weights have to be chosen as proportional to the respective signals level for

maximizing the combined carrier-to-noise ratio (CNR). The applied weighting to the

diversity branches has to be adjusted according to the SNR. For maximizing the SNR and

minimizing the probability of error at the output combiner, signal of dth

diversity branch is

weighted before making sum with others by a factor, cd*

/σ2

n,d . Here σ2n,d is noise variance of

diversity branch dth

and cd* complex conjugate of channel gain.

As a result the phase-shifts are compensated in the diversity channels and the signals

coming from strong diversity branches which has low level noise are weighted more

comparing to the signals from the weak branches with high level of noise. The term σ2n,d in

weighting can be neglected conditioning that σ2

n,d has equal value for all d. Then the

realization of the combiner needs the estimation of gains in complex channel and it does not

need any estimation of the power of noise.

This is a very useful combining process to combat channel fading. This is the best

combining process which achieves the best performance improvement comparing to other

methods. The MRC is a commonly used combining method to improve performance in a

noise limited communication systems where the AWGN and the fading are independent

amongst the diversity branches.



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� Equal-gain Combining (EGC): The EGC is similar to MRC with an exception to omit the weighting circuits. The

performance improvement is little bit lower in EGC than MRC because there is a chance to

combine the signals with interference and noise, with the signals in high quality which are

interference and noise free. EGC’s normal procedure is coherently combined the individual

signal branch but it non-coherently combine some noise components according to following

figure 6.2.

MRC is the most ideal diversity combining but the scheme requires very expensive

design at receiver circuit to adjust the gain in every branch. It needs an appropriate tracking

for the complex fading, which very difficult to achieve practically. However, by using a

simple phase lock summing circuit, it is very easy to implement an equal gain combining.

The EGC can employ in the reception of diversity with coherent modulation. The envelope

gains of diversity channels are neglected in EGC and the diversity branches are combined

here with equal weights but conjugate phase. The structure of equal-gain combining (EGC) is

as following since there is no envelope gain estimation of the channel.

Fig,6.2 Equal Gain Combining



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� Selection Combining (SC):

Fig,6.3- Selection Combining

The techniques MRC and EGC are not suitable for very high frequency (VHF), ultra

high frequency (UHF) or mobile radio applications because realization of a co-phasing circuit

with precise and stable tracking performance is not easy in a frequently changing, multipath

fading and random-phase environment. SC uses simple implementation procedure and is

more suitable comparing to MRC and EGC in mobile radio application.

In SC, the diversity branch which has the highest signal level has to be selected.

Therefore, the main algorithm of this method is on the base of principle to select the signal

amongst the all signals at the receiver end. Refer the fig 6.3, the general form of selection

combining is to monitor all the diversity branches and select the best one (the one which has

the highest SNR) for detection. Therefore we can say that SC is not a combining method but a

selection procedure at the available diversity. However, measuring SNR is quite difficult

because the system has to select it in a very short time. But selecting the branch with the

highest SNR is similar to select the branch with highest received power when average power

of noise is the same on each branch. Therefore, it is practical to select the branch which has

the largest signal composition, noise and interference.

It is experimentally proved that the performance improvement achieved by the

selection combining is just little lower than performance improved achieved by an ideal MRC

refer to fig 6.4,As a result the SC is the most used diversity technique in wireless

communication. If there is an availability of feedback information about the channel state of

the diversity branch the selection combining also can be used in transmission.

Fig 6.4 : SC and MRC comparison



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� Switched Combining (SWC): It is impractical to monitor the all diversity branches in selection combining. In

addition, if we want to monitor the signals continuously then we need the same number of

receivers and branches. Therefore, the form of switched combining is used to implement

selection combining. According to the figure 6.5 (a), switching from branch to branch occurs

when the signal level falls under threshold.

The value of threshold is fixed under a small area but the value is not the best

necessarily over the total service area. As a result the threshold needs to be set frequently

according to the movement of vehicle fig 6.5 (b). It is very important to determine the

optimal switching threshold in SWC. If the value of threshold is very high, then the rate of

undesirable switching transient increases. However, if the threshold is very low then the

diversity gain is also very low. The switching of switch combining can be performed

periodically in the case of frequency hopping systems.

Fig. 6.5(a): Switching combining methods with fixed threshold (a) and variable threshold (b)

� Periodic Switching Method: In a simple switching method, the diversity branches are selected periodically by a

conventional, free-running oscillator. This procedure is useful in comparably large

deviational and low-speed frequency modulation systems which includes phase transients

creates by switching can be diminished. The only selectable parameter switching rate can be

chosen as twice the height of the bit rate of signal. As a result the signal of the better branch

can select per signaling period. However, performance improvement may reduce in adjust-

channel area because this channel spectrum may be folded into desired channel band by

periodic switching in the pre-detection radio frequency stage (refer fig 6.6). So we can see an

overlap here which can be solved by rising selectivity of the adjust-channel at the receiver.



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Fig. 6.6: Periodic switching method

� Phase Sweeping Method: Phase sweeping method is another version of switching method which uses a single

receiver. In phase sweeping method sweeping rate is more than twice the highest frequency

of modulation signal. But we can gain the same diversity improvement which we achieve by

the periodic switching method. The phase sweeping method is as like mode-averaging

method where spaced antennas are used with electrically scanned directional patterns (refer

fig 6.7)..

Fig. 6.7: Phase Sweeping method

VI. CONCLUSION

The diversity techniques is used to provide the receiver with several replicas of the

transmitted signal, used to overcome the fading problem and to improve the performance of

the radio channel without increasing the transmitted power and improves the SNR. Among

the various diversity techniques spatial diversity is best suitable for the wireless

communication. Multi-input-multi-output (MIMO) wireless communication uses spatial

diversity techniques.

Among the various Diversity Combining methods: MRC outperforms the Selection

Combining; Equal gain combining (EGC) performs very close to the MRC. Unlike the MRC,

the estimate of the channel gain is not required in EGC. Among different combining

techniques MRC has the best performance and the highest complexity, SC has the lowest

performance and the least complexity. Alamouti suggested new transmit diversity techniques

to provide the same diversity order as that of MRC by using two transmit antenna and one

receive antenna.

Thus by employing multiple transmit and receive antenna the diversity can be

achieved to improve the performance of radio wireless communication channel.



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