 Open Access
 Total Downloads : 245
 Authors : Rupender Kour , Manasvi Mannan
 Paper ID : IJERTV6IS080086
 Volume & Issue : Volume 06, Issue 08 (August 2017)
 DOI : http://dx.doi.org/10.17577/IJERTV6IS080086
 Published (First Online): 09082017
 ISSN (Online) : 22780181
 Publisher Name : IJERT
 License: This work is licensed under a Creative Commons Attribution 4.0 International License
MRC Receiver in Correlated Hoyt Fading Channel with Multiple Modulation Technique
Rupender Kour

ech Scholar, Department of EC Panjab College of Engineering & Technology
Manasvi Mannan
Assistant Professor, Department of EC Panjab College of Engineering & Technology
Abstract In this paper the performance of diversity receivers and Mary modulation over hoyt fading channels is analysed. Mary modulation scheme has been tested on hoyt fading channel as it is more realistic representation of fading in satellite link. We have tested it for 16PSk, 4PSK and 32 PSK scheme for various fading and correlation coefficient parameters of hoyt channel. Hoyt channel is derived form nakagamim channel and also known as nakagamiq channel. The classical PDF based approach has been followed to derive the performance measures of basic diversity combiner namely Maximal ratio combining (MRC) receiver over Hoyt. The analysis is carried out for both independent and correlated fading channels for various coherent and noncoherent modulation schemes. For independent diversity receivers the analysis has been carried out for arbitrary number of input branches. The effect of diversity order and fading parameters on performance measures is studied with the help of the numerical evaluation of the obtained expressions. For dual correlated receivers the analysis is carried out for arbitrary correlation, whereas for L diversity receivers it is for most important practical correlation models exponential correlation. Exponential correlation is used to model the system when the receiving antennas are placed in a linear array. The effect of correlation on the receiver performance is studied for all the systems. To validate the derived expressions Monte carlo simulation is performed.
KeywordsMArray Modulation; Diversity; Nakagamim fading channel.

INTRODUCTION
In past few years, wireless communication has played an important role in information technology as information can be transmitted without the need of dedicated link between transmitter and receiver unlike wired communication, where a dedicated link/channel exist between transmitter and receiver. Compared to wired communication systems, wireless systems introduce a very interesting feature mobility. In any kind of communication, wired or wireless, there are some parameters like bandwidth, transmitted power, data rate etc. which decide the reliability of a system. The one which optimizes all of them is said to be a perfect system. In recent years, lots of research has been done on both kinds of communication so that a reliable system can be designed with high bandwidth, low transmitted power, high data rates and low bit or symbol error probability.
A. Wireless Communication System
In a wireless communication system, data is transmitted in the form of electromagnetic waves using antennas. When signal propagates through the wireless media, phenomena such as reflection and scattering through buildings, trees etc. and refraction through the edges causes the signal to follow multiple paths having different path loss factors and different delays. Thus, at the receiver, the received signal consists of multiple copies of same information bearing signal having different amplitudes and different phases arising due to different path lengths. Figure 1 shows a typical urban/suburban mobile radio environment. In the figure the direct path between the transmitter and the receiver is called lineofsight (LOS) path,
Figure 1 Paths between transmitter and receiver
Whereas, the path corresponding to reflected signal is called on lineofsight (NLOS) path. These multipaths have different phases corresponding to different pathdelays, so that they interfere at the receiver either constructively or destructively resulting in variation in signaltonoise ratio. In addition, mobility introduces time variation in channel response, i.e. if a very short pulse is transmitted; the received signal appears as a train of pulses due to presence of multipath. Secondly, as a result of time varying response, if same procedure is followed multiple times, a change is observed in the received pulse train over time, which will include changes in the sizes of individual pulses, changes in relative delays among the pulses and often, changes in the number of pulses observed. Hence, the equivalent lowpass time varying impulse response of the channel can be modelled as [1]:
(; ) = ()2()[ ()]
Where, () and () are time varying attenuation factor and path delay for ith path respectively. For a transmitted signal s(t) = 1 the received signal for the case of discrete multipath is given by [1]:
() = ()()
The () and () associated with different signals vary at different rates and in random manner. So, received signal () can be modelled as a random process. For large number of paths, central limit theorem can be applied and ()can be modeled as complexvalued Gaussian random process i.e. c( ;t) is also a complexvalued random process in t variable [1].

DIVERSITY COMBINING TECHNIQUES
There are different types of diversity combining techniques used in practice [2], which are as follows:
A. Maximal Ratio Combining
In maximal ratio combining technique, the received multiple faded copies of the transmitted signal are cophased. The co phased signal copies are weighted individually in proportion to their strength to maximize SNR at the output of the combiner. Assuming the received signal SNR at the input of the combiner is i , i = 1, 2, ..N, the output SNR can be shown to be [5]:

Selection Combining
In selection combining (SC), the system chooses the received signal having maximum SNR out of all copies of signals received. In this scheme the output SNR can be given as [2]:
SC = max{1, 2, …, N }

Switch and Stay Combining
The switch and stay combining (SSC) technique discussed here is presented in [2] and also shown in Figure 4. In this system, there are only two copies of fading signals are used. The combiner has only two antennas to receive fading signals. The received signal is fed as shown in Figure 4. In this scheme the received SNR 1 at antenna L1 is compared with a predefined threshold T . Switching occurs to the input branch L2 if 1 < T . And it again switches to first branch if 1 > T . It may happen that after switching the input SNR 2 at L2 is less than T or even less than 1, in such case the switch will still be connected to L2 until the SNR of first branch becomes greater than T . Switching from branch L2 to branch L1 is done in similar manner.
=
=1
The MRC operation requires estimation of phase and
amplitude of each received input branch signal. Hence, the complexity of implementation is high.
B. Equal Gain Combining
Different weights for each branch may not be convenient as it may increase the complexity of the receiver as in the case of MRC. So it is convenient to set all the gains to unity, while co phasing all signals before combining [2]. This technique of combining is called Equal Gain Combining.
Figure 2: Block diagram of Equal Gain Combiner [2]
Figure 3: Block diagram of Selection Combiner
Figure 4: Block diagram of Dual branch Switch and Stay Combiner
The SSC output SNR, SSC can be given as:
For EGC, the output SNR is given as [2]:
= { 1 1
2
( 2)
E. Switch and Examine Combining
= =0
=0
Unlike SSC combining scheme, switch and examine combining (SEC) adds the benefit of having multiple branches
where, i is the fading amplitude for ith copy of the transmitted signal.
at the receiver, especially when they are independent and identically distributed (i.i.d.) or equicorrelated and identically distributed. In SSC scheme, receiver switches between the
best two paths, adding a path does not improve the performance unless the added path is better than at least one of the best two ones. In SEC combining scheme, the receiver starts examining from the first path. If first path is acceptable, it continues to receiver from it, else, it switches and examines the next available path. This process continues until an acceptable path is found or all paths have been examined. In the latter case, the receiver stays on the last examined path [6] or selects the best path for reception [7].


PROPOSED WORK
with =0 and 2 = 0.
2
The noise on each receive antenna is independent from the noise on the other receive antennas.

At each receive antenna, the channel hi is known at the receiver.

In the presence of channel hi, the instantaneous bit energy to noise ratio at ith receive antenna is 2. For notational
convenience, let us define,
 2
In our work we have tested the hoyt fading channel performance in two different systems. One is Mary PSK simulation and other is MRC diversity scheme in montecarlo
=
simulation for correlated hoyt fading channel. The motivation behind MPSK is to increase the bandwidth efficiency of the PSK modulation schemes. In BPSK, a data bit is represented by a symbol. In MPSK, n = log2 M data bits are represented by a symbol, thus the bandwidth efficiency is increased to n times. Among all MPSK schemes, QPSK is the mostoften used scheme since it does not suffer from BER degradation while the bandwidth efficiency is increased. Since the description about Mary PSK modulation scheme is not so important to inherit in this chapter. So we have put that detail in appendix below.
Correlation among received fading signals cannot be avoided due to reasons discussed in [1, 2]. Analysis of diversity receivers for correlated channels is relatively more

Maximal Ratio combining diversity scheme
A signal transmitted at a particular carrier frequency and at a particular instant of time may be received in a multipath null. Diversity reception reduces the probability of occurrence of communication failures (outages) caused by fades by combining several copies of the same message received over different channels. In general, the efficiency of the diversity techniques reduces if the signal fading is correlated at different branches. The most common and efficient diversity scheme is maximal ratio combining (MRC). In Maximum Ratio combining each signal branch is multiplied by a weight factor that is proportional to the signal amplitude. That is, branches with strong signal are further amplified, while weak signals are attenuated as shown in figure 5.
complicated compared to the independent fading case. In this
section, performance of dual MRC, receivers are analyzed for correlated Hoyt fading channels. For MRC receiver an analysis for unequal fading parameters is also presented in addition to the equal fading parameter case. Unequal channel fading parameters may be observed in urban fading environments where diversity channels may have different characteristics. In the analysis presented here the PDF based approach is used. Some conditions are followed for MRC simulation which are:

We have N receive antennas and one transmit antenna.

The channel is flat fading In simple terms, it means that the multipath channel has only one tap. So, the convolution
r1 a1
r2
rn an
Adder
Receiver
operation reduces to a simple multiplication.

The channel experienced by each receive antenna is randomly varying in time. For the ith receive antenna, each transmitted symbol gets multiplied by a randomly varying complex number hi. As the channel under consideration is a
hoyt channel, the real and imaginary parts of hi are Gaussian distributed having mean and variance 2 = 1/2.
Figure 5: Lbranch antenna diversity receiver (L = 5). With
MRC, the attenuation/amplification factor is proportional to the signal amplitude ai = ri for each channel i.
On the ith receive antenna, the received signal is,
= +
Where the received symbol on the ith is receive antenna,
is the channel on the ith receive antenna, x is the transmitted

The channel experience by each receive antenna is
independent from the channel experienced by other receive antennas.

On each receive antenna, the noise has the Gaussian probability density function with
symbol and is the noise on ith receive antenna.
Expressing it in matrix form, the received signal is, Y=hx+n, where
= [1, 2, . ] is the received symbol from all the receive antenna
() = 1
22
()2 22
= [1, 2, . ] is the channel on all the receive antenna
x is the transmitted symbol and
= [1, 2, . ] is the noise on all the receive antenna.
Vol. 6 Issue 08, August – 2017
=1
The term, =
2
i.e sum of the channel powers
1 1
22 (1, 1, . , ) =
across all the receive antennas.


Complex Gaussian Model of Hoyt Random Variables
1
(22 )/2
=1 ( 1 + )
2 2
The complex Gaussian model of Hoyt RV l = Zl  for lth (l =
Hence, the joint CF in Equation can be obtained as
22 (1, 1, . , ) = 22
1, 2, . . . , L) branch can be given as
Zl = Xl + jYl, l = 1, 2, . . . , L
1
(22 2 )
1
1
1
In this representation, the Hoyt RV l = Zl has the PDF given in Equation. For the convenience of presentation but without
= /2
=1 ( 1 + )( 1 + )
loss of generality, we assume xl = 1, this result yl = q. Assuming 2 = 2 and 2 = 2 l, from above equation,
22
22
we can obtain = [2] = 1 + 2. Substituting this value of
l in Equation and expressing I0(Â·) in terms of confluent hyper geometric function, Equation 1.1.2.3 can be rewritten as
1 2
D. Probability Distribution Analysis
Receiver In this analysis correlation between the fading envelopes ls (l = 1,2) is assumed. A general expression for
() =
22
1
1(
; 1;
1 2
2)
the combined output SNR
is given in below Equation. It
2
22
can be expressed for the dual diversity case as
For equal branch average power i.e. 1 = 2 = . . . = L =
= (2 + 2)
(equivalently, for 1 = 2 = 3 . . = ), Eb/N0 can be expressed in terms of the fading parameter q as
= 2 (
) = (1 + ) ( )
1 2
An expression for the PDF of mrc i.e. fmrc (mrc), when 1
and 2 are correlated with correlation coefficient can be
0
0
obtained using the complex Gaussian model of Hoyt RV in
[13]. Using the PDF fmrc (mrc), performance measuresC. Characteristic Function of Sum of Hoyt Square RVs
In the mathematical model of Hoyt RVs i.e. 2 = 2 + 2 is
such as average output SNR, outage probability and ABER for binary, coherent and noncoherent modulations are derived. PDF of Combiner Output SignaltoNoise Ratio From above
independent. So the joint CF of 2l can e given as
2,2 (1, 2)
Equation , it can be observed that an expression for the PDF of
mrc can be obtained from the PDF of the RV 2 + 2. Using
1 2 1 2
(2 1) (2 1)
the complex Gaussian model for Hoyt distribution , an
1 +1 2 2
= 2 2
! ! [( 1 + 1) ( 1 + 2)] 2
expression for the joint CF of RVs 1 and 2 is reproduced
(1 )(2) =0
=0
2(1 2)2
2(1 2)2
below.
22 (1, 1, . , )
1
Ã— [ ]2(+) 1
= 22 (1, 1, . , )22 (1, 1, . , )
82(12)
+1
1
1
[( 1 +1)( 1 +1)] 2An expression for 22 (1, 1, . , ) can be derived
2(12)2
2(12)2
1
as
An expression for the PDF of 2 = 2 + 2 can be obtained
shown below: 1 2
From the PDF of Xl, performing transformation of random variable operation, PDF of a Xl2 can be obtained as
22
1
2 (2) =
by substituting 1 = 2 = in above Equation and subsequently taking the inverse Fourier transform to the resulting expression. This can be given as
2 (2 )
22
2
(2 1) (2 1)
From above equation can be obtained as
1
=
2 (1) = [ ]
8(1 2)( 2
=0
! !
)
=0
1 1 ( 1 +)
2(+)
=
22
Ã— [ 2 2 ]
2+1
2+1
(22 )1/2
0
8 (1 )
( 1 +)
2(12)2
( 1 +)
2(12)2
Performing the integration we obtain
2 ( ) = 1
The combined output SNR can be given as = () 2 .
1
22 (
1 22
+ )
0
Thus, the PDF of mrc can be obtained by scaling equation
corresponding to the multiplying factor Eb/N0, applying the
Since Xls are independent their joint CF is the product of
concept of transformation of RVs. For identical branch
individual CFs, hence
(
) 1 1
average power i.e. 1 = 2 = (equivalently, 1 = 2 =
3 . . = ), it can be shown that Eb/N0 = /(1 + 2).
22 1, 1, . , = /2
1
(22 )
=1 ( 1 + )
2 2
Substituting this relation, subsequent to the transformation of RV, an expression for fmrc(mrc) can be obtained as
Similarly the joint CF of RVs 2 2 can be obtained as
1
()
(1 + 2)
(2 1) (2 1)
(1 + 2)
2(+)
Input Message Random Symbols (Decimal)
Integer Value —>
Amplitude —>
20 1
Modulated Signal
= ( )2
! ! (2( + + 1)) Ã— [
]
8(1 2)
2(1 2)
=0
=0
10 0
E. Outage Probability
Outage probability is an important performance measure of any communication receiver. For the output SNR, it is defined as the probability that the output SNR , falls below a certain threshold value th. Mathematically, it can be given as
() = ()
0
0 5 10
Symbol Index —>
Amplitude —>
Original Message Sequence (Binary) 1
0.5
0
0 5 10
n —>
1
0 5 10
n —>
Amplitude —>
Demodulated Message Sequence (Decimal) 20
10
0
0 5 10
n —>
Putting fmrc(mrc) from previous equation into this equation,
an expression for the outage probability for correlated dual MRC receiver can be expressed as
( )
Demodulated Message Sequence (Binary) 1
Amplitude —>
0.5
0
(1 + 2)
(2 1) (2 1)
(1 + 2)
2(+)
0 5 10
= ( )2
! ! (2( + + 1)) Ã— [
]
8(1 2)
n —>
2(1 2)
Ã—
=0
=0
Figure 6: 16PSk modulated input symbol
(1+2)
2(12)2
2+2+11{2
Constellation diagram provides a graphical representation of
1 4
22
+ 1; 2( + + 1); } 2 (1 )
where th is the threshold value of the combined output SNR. The integral in Equation cannot be solved in the given form. By expressing the hyper geometric function in infinite series, above equation can rewritten as
( )
the complex envelope of each possible Symbol state. The x axis of the constellation diagram represents the inphase component of the complex envelope and the yaxis represents the quadrature component of the complex envelope. The distance between the signals on the constellation diagram relates to how different the modulation waveform are, and how well a receiver can differentiate between all possible
(1 + 2)
(2 1) (2 1)
(1 + 2)
2(+)
symbols when random noise is present.
= ( )2
! ! (2( + + 1)) Ã— [
]
8(1 2)
2(1 2)
=0
=0
Signal Constellation
2
1+2
Ã—
2+2++1 22(12) }
1.5
1
0101 0100 0011


RESULT
We have earlier noticed that nakagamiq channel or hoyt fading channel is the mathematical formulation of fading in satellite link or other fading which is more similar to actual
0.5
Quadrature
0
0.5
0110
0111
1000
1001
1010
0010
0001
0000
1111
1110
signal losses. In previous chapter we have described mathematically the hoyt fading channel and its derivation for outage probability for correlated hoyt fading channels. Results
1
1.5
2
1011 1100 1101
have been analysed by outage probability and bit error rate. We have observed the performance of hoyt fading channel considering Mary modulation and MRC.
MATLAB R2013a has been used as a simulation tool as it provides a wide range of designed mathematical functions which proved to be useful in calculation of channel response. For example the complex calculation of outage probability for MRC is made easier by MATLABs hypergeometric function, zeroth order Bessel function and gamma function.
CASE I MARY MODULATION IN HOYT FADING CHANNEL
We have tested the performance of nakagamiq channel for 16PSK modulation. The input data for a short interval is shown in figure 5. The constellation diagram for it is shown in figure 6.
2 1 0 1 2
InPhase
Figure 7: constellation diagram of 16ary PSK modulation
In teh previous chapter the channel response of hoyt fading channel depends upon the hoyt fading parameter. Variation in this value results in change in pdf of channel. Fading parameter (q) is the ratio of uneqal variances and . A channel response for hoyt channel is shown in figure 8. As per central limit theorem if there is sufficiently much scatter, the channel impulse response will be wellmodelled as a Gaussian process irrespective of the distribution of the individual components. If there is no dominant component to the scatter, then such a process will have zero mean and phase evenly distributed between 0 and 2 radians. The envelope of the channel response will therefore be Hoyt distributed. In this case for q=0.2 is more similar to Gaussian distribution. The
response curve is not ideal which is in case when random variable alpha is 1. We have tested this on different value of alpha which are:
0 Outage probability curve for16ary modulation in Hoyat fading channel
10
50
10
0.247921068062695
0.053990966533
6576
RV alpha
0.342198280312217
100
Outage Probability
10
q=0.2
q=0.5
q=1
1
0.9
0.8
0.7
0.6
pdf
0.5
0.4
Hoyt channel PDF
150
10
200
10
250
10
300
10
q=0.4,ro=0 q=0.5,ro=0 q=1,ro=0 q=0.4,ro=0.8 q=0.5,ro=0.8 q=1,ro=0.8
0 2 4 6 8 10 12 14 16 18
Eb/No, dB
0.3
0.2
0.1
0
0 0.5 1 1.5 2 2.5 3
Figure 9: outage probability curve for 16ary simulation of Hoyt fading channel
q=0.4
q=0.5
q=1
BER for16ary modulation in Hoyat Fading channel
1
Hoyt fading channel amplitude 10
Figure 8: channel response of nakagami q channel
2
Bit Error Rate
10
The outage probability curve for 16 ary PSK modulation is
3
2
–
a r y
4
–
a r y
shown in figure 9. the outage occurs if signal drops below the noise power level. From the figure it is clear that with variation of correlation coefficient , higher values provides less outage probability which means less loss of signal whereas for it is highest for combination of fading coefficient value 1 and correlation coeff =0. From this simulation curve 16 ary PSK modulation it is proved that if fading coeff (q) has range in between 0.40.5 and correlation coefficient is 1 then outage in signal will be least. A bit error rate curve for this case is shown in figure 10. it must be kept in consideration here that the Mary simulation has been checked for single transmitter and receiver antenna. The bit error rate curve in 4.5 shows that minimum value is for q0.5, which is in accordance with outage probability. To validate the simulation results we have tested the Mary results for 4 and 32 PSK as shown in table 4.1. These simulation curves of outage probability also proves that for q=1 and = 0, outage probability is highest in hoyt fading channel. Here = 0 represents the uncorrelation case as it is correlation coefficient. So in other words for uncorrelated case the hoyt fading channel performs least.
Case II: MRC monte carlo simulation
The next case considered is MRC scheme with monte carlo simulation. In this case we have considered 2 receivers with BPSK modulation. Results have been shown in figure 11 and
3
10
4
10
5
10
0 5 10 15 20 25 30 35
Eb/No, dB
10
150
10
100
10
50
q=0.5,ro=0
10
0
2
1.5
1
0.5
0
0.5
1
1.5
2
2
Signal Constellation
00
10
01
Quadrature
Outage Probability
Figure 10: BER curve for 16ary simulation of Hoyt fading channel
Outage probability curve for4ary modulation in Hoyat fading channel
q=0.4,ro=0
q=1,ro=0
q=0.4,ro=0.8
q=0.5,ro=0.8 q=1,ro=0.8
0
1
2
3
4
5
6
Signal Constellation
10
300
10
250
10
200
2
1
0
InPhase
1
11
0 Outage probability curve for32ary modulation in Hoyat fading channel
2
1.5
1
0.5
0
0.5
1
1.5
2
2
10
50
10
00101
010100011000001010110
01011
100
00100
00011
00010
00001
00000
11111
11110
11101
01100
01101
01110
01111
10000
10001
10010
10011
Quadrature
Outage Probability
10
1.7 for outage probability and bit error rate. These are checked for different values of L, q and . for now only 2 receivers case is being analysed, but the script developed is dynamic
150
10
200
10100111110101001011010
10
10101 11011
q=0.4,ro=0
10100 11100
q=0.5,ro=0 q=1,ro=0
and can be used for more number of receivers.
250
10 q=0.4,ro=0.8
q=0.5,ro=0.8
300
10
q=1,ro=0.8
0 5 10 15 20 2
Eb/No, dB
1
0
InPhase
1
2
Figure 11: MRC with monte carlo
The effect of branch correlation on the outage can be observed by comparing the outage values for =0.8 against the values for =0 (uncorrelated case). Clearly, with the increase in the receiver suffers more outage, for a fixed value of q and L. Again as expected, increase in input branches reduces the probability of outage. The least outage probability is observed at q=0.5, = 0.8 and L=2 & maximum outage probability is at q=0.4, = 0 nd L=1. Similar is the case with BER, for q=0.4 and L=1, it is highest and q=1 and L=2, it is lowest as shown in figure 12. So increasing the number of receivers lower the effect of fading in hoyt channel which fulfil the MRC purpose since MRC is used to reduce the noise effect in transmitted signal.
Outage probability curve BPSK modulation with Maximal Ratio Combining in Hoyat fading channel
0
10
50
10
100
q=0.4,ro=0,L=1 q=0.5,ro=0,L=1 q=1,ro=0,L=1 q=0.4,ro=0.8,L=1 q=0.5,ro=0.8,L=1 q=1,ro=0.8,L=1 q=0.4,ro=0,L=2 q=0.5,ro=0,L=2 q=1,ro=0,L=2 q=0.4,ro=0.8,L=2 q=0.5,ro=0.8,L=2 q=1,ro=0.8,L=2
Outage Probability
10
150
10
200
10
are encountered frequently in the field deployment of diversity receivers. Results are compared with various correlation coefficients value of hoyt fading channel and different number of receiver antennas and different set of fading coefficients. It has been observed that in case of Mary simulation with M=16, fading coeff (q) has range in between 0.40.5 and correlation coefficient is 1for least outage probability. These values are validated by checking on 4ary and 32ary simulation too.
In case of MRC scheme, 2 receivers are compared for different values of q and . it is observed that with increase in number of antennas, outage probability and BER decreases. The least outage probability is observed at q=0.5, = 0.8 and L=2 & maximum outage probability is at q=0.4, = 0 and L=1. These results are successfully simulated using MATLABs communication toolbox.
REFERENCES
[1]. Rupaban Subadar and P. R. Sahu, Performance of LMRC Receiver over Equally Correlated Hoyt Fading Channels, IETE JOURNAL OF RESEARCH, VOL 57, ISSUE 3, MAYJUN 2011 [2]. Vladeta Milentijevi1, Dragan Deni1, Mihajlo Stefanovi1,StefanR. Pani2, Dragan Radenkovi, Relative Measurement Error Analysis in the Process of the Nakagami m Fading Parameter Estimation, SERBIAN JOURNAL OF ELECTRICAL
250
10
300
10
0 5 10 15 20 25 30 35
ENGINEERING Vol. 8, No. 3, November 2011, 341349
[3]. Suvarna P. Jadhav, Vaibhav S. Hendre, Performance of Maximum ratio combining (MRC) MIMO Systems for Rayleigh Fading Channel, International Journal of Scientific and Research Publications, Volume 3, Issue 2, February 2013Figure 12: outage probability curve for MRC in hoyt fading channel
BER for BPSK modulation with Maximal Ratio Combining in Hoyat Fading channel
1
10
2
Bit Error Rate
10
3
10
q=0.4,L=1 q=0.5,L=1
4
10 q=1,L=1
q=0.4,L=2 q=0.5,L=2
5 q=1,L=2
10
0 5 10 15 20 25 30 35
Eb/No, dB
Figure 13: BER for MRC in hoyt fading channel

CONCLUSSION

Hoyt fading channel is more realistic satellite link channel. In this work, Performance of Mary modulation scheme and MRC diversity receivers are analyzed over Hoyt fading channels. Focusing on the analytical approach, mathematical expressions for various performance measures such as outage probability and BER of diversity receivers have been obtained. The PDF based analytical approach has been preferred in all analyses for these performance measures, wherever possible. It is stressed to analyze diversity receivers with arbitrary order of diversity with correlated fading channels since these cases
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