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. Badjate2
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
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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 σ2
. 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 σ2
n,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 σ2
n,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.

159
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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