INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN ENGINEERING AND TECHNOLOGY (IJARET)

Transcription

1 INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN ENGINEERING AND TECHNOLOGY (IJARET) International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 ISSN (Print) ISSN (Online) Volume 4, Issue 2 March April 2013, pp IAEME: Journal Impact Factor (2013): (Calculated by GISI) IJARET I A E M E DIVERSITY TECHNIQUES FOR WIRELESS COMMUNICATION Pravin W. Raut 1, 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. 144

2 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. 145

3 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 λ 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 n th power of the distance : L = c d n 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. 146

4 (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 σ 2 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 manmade 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 landmobile 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 Cochannel-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. 147

5 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 148

6 (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 149

7 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: 150

8 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 151

9 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. 152

10 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 153

11 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. 154

12 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-tonoise 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 d th diversity branch is weighted before making sum with others by a factor, c d * /σ 2 n,d. Here σ 2 n,d is noise variance of diversity branch d th and c d * 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 σ 2 n,d in weighting can be neglected conditioning that σ 2 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. 155

13 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 156

14 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 157

15 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 adjustchannel 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. 158

16 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. 159

17 REFERENCES [1] Siavash M. Alamouti. A Simple Transmit Diversity Technique for Wireless Communications. IEEE Journal on Select Areas in Communcations, 16(8): ,October [2] MIMO: The next revolution in wireless data communications By Babak Daneshrad [3] Bit Error Rate Performance of MIMO Channels for various Modulation Schemes using Maximum Likelihood Detection Technique, IP Multimedia Communications A Special Issue from IJCA [4] Maximum-Likelihood Equalisation for STBC-MIMO on Test-Bed,Ashu Taneja Assistant Professor,Department of Electronics & Communication Engineering Chitkara University, Baddi. International Journal of Computer App ( ) Volume 46 No.22, May 2012 [5] G. J. Foschini and M. J. Gans, On limits of wireless communications in a fading environment when using multiple antennas, Wireless Pers. Commun., vol. 6, pp , Mar [6] G. J. Foschini, Layered space time architecture for wireless communication in a fading environment when using multielement antennas, Bell Labs Tech. J., pp , Autumn [7] D. Gesbert, M. Shafi, D.-S. Smith, and Naguib, From theory to practice: an overview of MIMO space-time coded wireless systems, IEEE Sel. Areas in Comm.Journal, vol. 21, 3, pp ,Apr [8] Diversity in Spread Spectrum-Tan F.Wong: Spread Spectrum cdma [9] Transmit Diversity vs. Spatial Multiplexing in Modern MIMO Systems -Angel Lozano, Nihar Jindal, IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 9, NO. 1, JANUARY 2010 [10] An Overview of Diversity Techniques in Wireless Communication Systems, Hafeth Hourani, Helsinki Univ. of Techn. Communications Lab [11] Physical Diversity and Virtual Diversity for Wireless Comm. Networks-A ReviewAli and Saleh A. Alshebieli,(PSATRI), Saudi Arabia, [12] C. N. Chuah, Tse, J M.Kahn, and R.Valenzuela, Capacity scaling in MIMO wireless systems under correlated fading, IEEE Trans. Inform. Theory, vol. 48, pp , Mar [13] L. Hanlen and M. Fu, Multiple antenna wireless communication systems: Capacity limits for sparse scattering, in Proc. 3rd Australian Communication Theory Workshop, Aus CTW 2002, [14] Jack Winters "Optimum Combining in Digital Mobile Radio with Cochannel Interference," Special Issue on Mobile Radio Communications IEEE Journal on Selected Areas in Communications, July 1984, [15] Raleigh, G. G. and Jones, V. K. "Multivariate modulation and coding for wireless communication", IEEE J. Selected Areas in Communication, vol. 17, no. 5, pp , May 1999 [16] Gerard. J. Foschini "Layered Space-Time Architecture for Wireless Communication in a Fading Environment When Using Multi-Element Antennas". Bell Laboratories Technical Journal, pp: October 1996 [17] L. Zheng and D. N. C. Tse (May 2003). "Diversity and multiplexing: A fundamental tradeoff in multiple-antenna channels". IEEE Trans. Inf. Th.49 (5): doi: /TIT [18] Sudha.P.N and Dr U.Eranna, Source and Adaptive Channel Coding Techniques for Wireless Communication, International Journal of Electronics and Communication Engineering & Technology (IJECET), Volume 3, Issue 3, 2012, pp , ISSN Print: , ISSN Online: [19] T.Regu and Dr.G.Kalivarathan, Prediction of Wireless Communication Systems in the Context of Modeling, International Journal of Electronics and Communication Engineering & Technology (IJECET), Volume 4, Issue 1, 2013, pp , ISSN Print: , ISSN Online: [19] Haritha.Thotakura, Dr. Sri Gowri.Sajja and Dr. Elizabeth Rani.D, Performance of Coherent OFDM Systems Against Frequency offset Estimation under Different Fading Channels, International Journal of Electronics and Communication Engineering & Technology (IJECET), Volume 3, Issue 1, 2012, pp , ISSN Print: , ISSN Online: