3.IJAEST-Vol-No-8-Issue-No-1-Performance-Analysis-of-Wireless-MIMO-System-by-Using-Alamouti’s-Sche

Muhammad Sana Ullah* et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 8, Issue No. 1, 019 - 024

Performance Analysis of Wireless MIMO System by Using Alamouti’s Scheme and Maximum Ratio Combining Technique Muhammad Sana Ullah

rapidly increasing worldwide. On the other hand available radio spectrum is limited and the Communication capacity needs cannot be met without a significant increase in communication spectral efficiency. Advances in coding, such as Turbo codes, Low density parity check codes and Space time codes [1],[6],[9],[15-16] made it feasible to approach the Shannon capacity limit in system with a single antenna link.

Significant further advances in spectral efficiency are available though increasing the number of antennas at both transmitter and the receiver which is as MIMO technology. It is one of several forms of smart antenna technology. In fact, the MIMO concept is much more general and embraces many other scenarios such as wireline digital subscriber line (DSL) systems [13] and single-antenna frequency-selective channels [1, 2, 14]. MIMO technology has attracted attention in wireless communications, because it offers significant increases in data throughput and link range without additional bandwidth or transmit power. It is achieved by higher spectral efficiency (more bits per second per hertz of bandwidth) and link reliability or diversity (reduced fading). Because of these properties, MIMO is an important part of modern wireless communication standards such as IEEE 802.11n(Wifi), 4G, 3GPP Long Term Evolution, WiMAX and HSPA+. The aim of this paper is to approach AWGN channel performance from Rayleigh fading channel performance by using Alamouti diversity and Maximum ratio combining technique with increasing the number of transmitting and receiving antennas at low SNR 2×2 and/or 1×4 MIMO wireless communication system.

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Abstract—With the integration of Internet and multimedia applications in next generation wireless communications, the demand for wide-band high data rate communication services is growing. As the available radio spectrum is limited, higher data rates can be achieved only by designing more efficient signaling techniques. Recent research in information theory has shown that large gains in capacity of communication over wireless channels are feasible in multiple input multiple output (MIMO) systems as well as significantly enhances the system performance compared to conventional systems in fading multipath channel environment. The MIMO channel is constructed with multiple element array antennas at both ends of the wireless link. All these MIMO techniques are based on proper handling of (Alamouti scheme and maximum ratio combining method) signals transmitted and received by an array of antennas. Simulation results show very high performance in terms of bit error rate, even for low signal-to-noise ratios.

Mohammed Jashim Uddin

Dept. of Electronic and Telecommunications Engineering International Islamic University Chittagong Chittagong-4203, Bangladesh jashimcuet@yahoo.com

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Dept. of Electrical and Electronic Engineering Chittagong University of Engineering and Technology Chittagong4349, Bangladesh hi.sanam@yahoo.com

Keywords-AWGN channel, Diversity technique, BER, MIMO, SISO, SNR, Rayleigh fading channel.

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I. INTRODUCTION In broad sense, the term communications refers to the sending, receiving and processing of information by electronic means. It is the technique of transmitting a message, from one point to another, knowing how much information, if any, is likely to be lost in the process [1]. Hence, the term "communication” is covered all forms of distance communications including radio, telegraphy, television, telephony, data communication and computer networking.

Communications started with wire telegraphy in the eighteen forties, developing with telephony some decades later and radio at the beginning of this century. More recently, the use of satellites and fiber optics has made communications even more widespread, with an increasing emphasis on computer and other data communications [1-2]. A modern communications system is first concerned with the sorting, processing and sometimes storing of information before its transmission. The actual transmission then follows, with further processing and filtering of noise. Finally it come reception, which may include processing steps such as decoding, storage and interpretation [4]. Demands for capacity in wireless Communications, driven

by Cellular mobile, Internet and Multimedia services have been

ISSN: 2230-7818

This paper is organized as follows. Besides MIMO system model, the mathematical view of total received signal power is described in Section II. In section III provided the degradation effect of fading. Explanation of diversity technique including Alamouti scheme and Maximum ratio combining technique are given in Section IV whereas Section V viewed the simulation results, followed by conclusion in Section VI. II.

THE MIMO SYSTEM MODEL

When a transmitter and a receiver, with an appropriate channel coding/decoding scheme, are equipped with multiple antennas, the presence of multipath fading can improve by

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Muhammad Sana Ullah* et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 8, Issue No. 1, 019 - 024

Fig. 2. Multipath fading Phenomenon.

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Fig. 1. MIMO system model The transmitted signals in each symbol period are represented by a column matrix , where the th component of , refers to the transmitted signal from antenna . A Gaussian channel has been considered, for which, according to information theory, the optimum distribution of transmitted signals is also Gaussian. Thus, the elements of are considered to be zero mean independent and identically distributed (i.i.d.) Gaussian variables. In [1], the covariance matrix of the transmitted signal is given by

III. DEGRADATION EFFECTS OF FADING The mobile radio channel is a time-varying multipath channel and is subject to physical propagation path loss [17].

The time-variations are caused by the medium changes as the vehicles moves. The propagation losses are related to both the atmospheric propagation and the terrain configuration [12]. In [7], Sklar viewed that the multipath aspect is caused by different scatterers and reflectors such as building or trees that surround the mobile unit which is shown in Fig. 2.

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achievable transmission rates [3]. For such MIMO channels, several optimum space-time codes have been designed. Now, let us consider a single point-to-point MIMO system with arrays of transmit and receive antennas. In this case focus on a complex base band linear system model described in discrete time. The general modeling of a channel as an abstract MIMO channel allows for a unified treatment using a compact convenient vector-matrix notation. The system block diagram is shown in Fig. 1.

denoted the Hermitian of matrix , which means the transpose

As a result of these propagation phenomena in a narrow-band transmission, where narrow-band is defined with respect to the coherence bandwidth of the channel [4], [11], the receive signal affect the performance of the receiver which results in an increase of bit error rate (BER). The channel performance is shown in Fig. 3 which viewed the three major performance categories in terms of error probability versus signal to

and component-wise complex conjugate of . According to

noise ratio ( â „

{ where

}

{ } denoted the expectation and the operator

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Vucetic et al in [1], the total transmitted power is constrained to

regardless of the number of transmit antennas

be represented as

where is the channel matrix. Now, the received signal }, by using Eq. (3), is covariance matrix, defined as { given by

BER Comparison

0

10

. It can

-1

10 Error Probability (Pb)

where denoted the trace of matrix , obtained as the sum of the diagonal elements of . By using the linear model, the received vector can be represented as

).

-2

10

-3

10

-4

10

-5

10

-6

10

0

2

4

6

8 10 Eb/No in (dB)

12

14

16

Fig. 3. Error Performance: The good, the bad, and the awful.

While the total received signal power can be expressed as .

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The left most exponentially shape curve shown that at a reasonable signal to noise ratio level, good performance can

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signal distortion has been mitigated, the versus ( ⁄ ) curve can transition from awful category to the bad Rayleigh limit curve. Next approach is to further strive towards AWGN system performance by using some sort of diversity and powerful error correction code.

1) Alamouti space time encoding: In Fig. 4 has shown the block diagram of the Alamouti’s space-time encoder. Let us assume that an M-ary modulation scheme is used. In the Alamouti’s space-time encoder [5], each group of m information bits is first modulated, where . Then, the encoder takes a block of two modulated symbols and in each encoding operation and maps them to the transmit antennas according to a code matrix given by

[

]

Information Source

x1

Encoder

x2 

Modulator



  x2     x2 x1 

x1 x2    x1

Fig. 4. A Block diagram of the Alamouti space-time encoder.

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IV. DEGRADATION EFFECTS OF FADING Diversity is a technique of transmitting multiple copies of the same signal. This technique requires a number of signal transmission paths known as diversity branches and each branch carries the same information with approximately uncorrelated or dissimilar multipath fading characteristics. The diversity technique also requires combining circuit so as to combine signals from each diversity branch or select only best signal out of different received signals [1].

Alamouti’s transmit diversity technique; including encoding and decoding algorithms have being represented.

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be expected in a AWGN interference. The middle curve known as Rayleigh limit, shown a performance degradation resulting from a loss in signal to noise ratio which is the consequence of flat fading or slow fading [7]. The remaining curve that reached an irreducible error-rate level, sometimes called an error-floor, where the bit-error-probability can level off at values nearly equal to . This shows the severe degradation in performance due to fast fading or frequency selective fading. In such cases zero amount of signal to noise ratio will help to achieve the desired level of bit-error probability . In that situation only approach available for improving performance is to use some form of mitigation techniques to remove or reduce the signal distortion. The mitigation method depends on whether the distortion is caused by frequency selective fading or fast fading [7]. Once the

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In wireless mobile communications, diversity techniques are widely used to reduce the effects of multipath fading and improve the reliability of transmission without increasing the transmitted power or sacrificing the bandwidth. The diversity technique requires multiple replicas of the transmitted signals at the receiver, all carrying the same information but with small correlation in fading statistics. The basic idea of diversity is that, if two or more independent samples of a signal are taken, these samples will fade in an uncorrelated manner, e.g., some samples are severely faded while others are less attenuated.

This means that the probability of all the samples being simultaneously below a given level is much lower than the probability of any individual sample being below that level.

Thus, a proper combination of the various samples results in greatly reduced severity of fading, and correspondingly, improved reliability of transmission.

A. Alamouti’s scheme The Alamouti’s scheme is historically the first space-time block code to provide full transmit diversity for systems with two transmit antennas [1]. It is worthwhile to mention that delay diversity schemes can also achieve a full diversity, but they introduce interference between symbols and complex detectors are required at the receiver. In this section,

ISSN: 2230-7818

The encoder outputs are transmitted in two consecutive transmission periods from two transmit antennas. During the first transmission period, two signals and are transmitted simultaneously from antenna one and antenna two, respectively. In the second transmission period, signal is transmitted from transmit antenna one and signal from transmit antenna two, where is the complex conjugate of . It is clear that the encoding is done in both the space and time domains. Let us denote the transmit sequence from antennas one and two by and , respectively. [

]

[

]

The key feature of the Alamouti’s scheme is that the transmit sequences from the two transmit antennas are orthogonal, since the inner product of the sequences and is zero, i.e.

The code matrix has the following property

[ | | where

| |

| | | |

| |

]

| | is a 2 × 2 identity matrix.

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Muhammad Sana Ullah* et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 8, Issue No. 1, 019 - 024

| | | | where | | and are the amplitude gain and phase shift for the path from transmit antenna i to the receive antenna, and T is the symbol duration. 

x1

h1

Transmit Antenna 1



h2

Transmit Antenna 2

+

Noise

B. Maximum Ratio Combining Maximum ratio combining is a linear combining method.

In a general linear combining process, various signal inputs are individually weighted and added together to get an output signal. The weighting factors can be chosen in several ways. A block diagram of a maximum ratio combining diversity is shown in Fig. 6. The output signal is a linear combination of a weighted replica of all of the received signals. It is given by ∑ where is the received signal at receive antenna i, and the weighting factor for receive antenna i.

IJ A hˆ1

hˆ 2

Rx 2

Rx 1

Signal Combiner

Channel Estimator

are independent complex variables with zero

⁄ per dimension, mean and power spectral density representing additive white Gaussian noise samples at time t and t + T, respectively.

Receive antenna

n1 , n 2

and

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 x2

where

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2) Receiver of Alamouti scheme: Let us assume that one receive antenna is used at the receiver. The block diagram of the receiver for the Alamouti’s scheme [1] is shown in Fig. 5.

The fading channel coefficients from the first and second transmit antennas to the receive antenna at time t are denoted by and , respectively. Assuming that the fading coefficients are constant across two consecutive symbol transmission periods, they can be expressed as follows

x2

x1

1

…..

r1

RF Front End

RF Front End

RF Front End







rn R

n

2

R

+ Detector

xˆ 2

Fig. 5. Receiver for the Alamouti scheme.

At the receiver antenna, the received signals over two consecutive symbol periods, denoted by and for time t and t+T, respectively, can be expressed as

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Rx

nR

r2

Maximum Likelihood Decoder

xˆ1

is

Output Fig. 6. Block diagram of maximum ratio combining diversity.

In maximum ratio combining, the weighting factor of each receive antenna is chosen to be in proportion to its own signal voltage to noise power ratio. Let and be the amplitude and phase of the received signal , respectively. Assuming that each receive antenna has the same average noise power, the weighting factor can be represented as

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Performance of Diversity Technique and Other Comparisons

0

10

No Diversity (1Tx, 1Rx), BPSK Alamouti (2Tx, 2Rx), BPSK Maximal-Ratio Combining (1Tx, 4Rx), BPSK

-1

10

-2

10

BER

This method is called optimum combining since it can maximize the output SNR. It is shown that the maximum output SNR is equal to the sum of the instantaneous SNRs of the individual signals. In this scheme, each individual signal must be co-phased, weighted with its corresponding amplitude and then summed. This scheme requires the knowledge of channel fading amplitude and signal phases. So, it can be used in conjunction with coherent detection, but it is not practical for non coherent detection.

-3

10

V.

SIMULATION RESULT -4

10

0

10

6

8 10 12 Eb/No (in dB)

14

16

18

20

Following Table I gives the comparison result among no diversity, Alamouti’s scheme and Maximum ratio combining method for a particular SNR.

No Diversity (1Tx, 1Rx) Alamouti (2Tx, 1Rx) Maximal-Ratio Combining (1Tx, 2Rx)

-1

4

Fig. 8. Performance analysis of SISO (No diversity (1T x, 1Rx)) and MIMO (Alamouti (2Tx, 2Rx) and Maximum ratio combining (1Tx, 4Rx)) system.

Performance Analysis using Diversity Technique

0

2

T

In this work, MATLAB is used to test the channel performance using diversity technique based on BPSK modulation scheme. By applying Alamouti’s diversity and/or Maximum ratio combining technique, it is possible to make channel response from Rayleigh fading channel to AWGN channel.

10

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TABLE I

COMPARISON BETWEEN SISO ( NO DIVERSITY) AND MIMO (ALAMOUTI AND MAXIMUM RATIO COMBINING TECHNIQUE) SYSTEM

-2

BER

10

SNR in dB

-3

10

-4

10

10

2

4

6

8

10 12 Eb/No(in dB)

14

16

18

20

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0

Fig. 7. Performance analysis of SISO (No diversity (1T x, 1Rx)) and MIMO (Alamouti (2Tx, 1Rx) and Maximum ratio combining (1Tx, 2Rx)) system.

From Fig. 7 it is seen that channel performance is improved but does not seem like AWGN channel for 2×1 or 1×2 MIMO configuration. When the number of transmitting and receiving antenna is increased like Alamouti (2Tx, 2Rx) or Maximum ratio combining (1Tx, 4Rx), the channel performance just like AWGN channel with constant SNR. The result is shown in Fig. 8.

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Diversity technique

No diversity (1Tx,1Rx) Alamouti (2Tx,1Rx)

Bit Error Rate (BER) 0.02314 0.005665

Alamouti (2Tx, 2Rx) Maximum ratio combining (1Tx, 2Rx)

0.0001161 0.001722

Maximum ratio Combining (1Tx, 4Rx)

0.00001058

VI.

CONCLUSION

A noble method diversity technique for estimating the channel performance of mobile communication signals affected by Rayleigh multipath fading phenomena is discussed. The performance of Alamouti scheme and Maximum ratio combining technique are evaluated under the assumption of BPSK signals affected by reflection, defraction and scattering environment. It is shown that in wireless MIMO system based on Alamouti diversity technique and Maximum ratio combining technique can help to combat and mitigate against Rayleigh fading channel and approach AWGN channel performance with constant transmit power. For this reason, multi-antenna MIMO channels have recently become an attractive scheme means to increase quality of wireless communications by the use of spatial diversity at both sides of the link and occupies a considerable part of today’s academic research.

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REFERENCES

Mohammed Jashim Uddin was born in 1979 in Chittagong, Bangladesh. He received the B.Sc. degree in Electrical and Electronic Engineering from Chittagong University of Engineering & Technology (CUET), Chittagong, Bangladesh and the M.Sc. degree in Electronic and Communication Engineering from University of Greenwich, Medway, UK in 2004 and 2009, respectively.

Since 2004, he has been involved at PHP Float Glass Industry, Chittagong, Bangladesh as an Assistant Engineer, where he was engaged with the 10MW power plant for Gas and Diesel generator. In 2006, he joined at MARS Textile Limited, Chittagong, Bangladesh as a Senior Engineer. In 2008, he worked for Texcel Technology plc, Dartford, UK as a Test Technician, where his responsibility was involved with PCB Testing, Inspection and Assembly.

His Research interests are Renewable and Sustainable Energy, Solar cell, RF and Microwave Power Amplifier and Antenna & Wave Propagation and signal processing. He is currently serving as a Lecturer in International Islamic University Chittagong under the Electronic and Telecommunication Engineering Department.

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[1] B. Vucetic and J. Yuan, Space-Time Coding, England, Wiley, 2003.

[2] D. Tse and P. Viswanath, Fundamentals of Wireless Communication, Cambridge University Press, USA, 2005.

[3] G. G. Raleigh and J. M. Cioffi, “Spatio-Temporal Coding for Wireless communication”, IEEE Transaction on Communication, Vol. 46, No. 3, pp. 357-366, March 1998.

[4] W. H. Tranter, K. S. Shanmugan, T. S. Rappaport and K. L. Kosber, Principles of Communication Systems Simulation with Wireless Applications, Prentice Hall, USA, 2003.

[5] S. M. Alamouti, "A simple transmit diversity technique for wireless communications", IEEE(R) Journal on Selected Areas in Communications, Vol. 16, No. 8, pp. 1451-1458, October 1998.

[6] V. Tarokh, H. Jafarkhami, and A.R. Calderbank, “Space-time block codes from orthogonal designs”, IEEE Transactions on Information Theory, Vol. 45, No. 5, pp. 1456-1467, July 1999.

[7] B. Sklar, Digital Communications Fundamentals and Applications, Second Edition, Pearson Education, India, 2003.

[8] --------, “Communications Toolbox for Use with MATLAB”, The MathWorks, Version 3.4, 2006.

[9] G. J. Foschini, “Layered space-time architecture for wireless communication in a fading environment when using multi element antennas”, Bells lab technical journal, Vol. 1, No. 2, pp. 41-59, Autumn 1996.

[10] I. E. Telatar, “Capacity of multi-antenna Gaussian channel”, European Transaction telecommunication, Vol. 10, No. 6, pp. 585-595, Nov.-Dec. 1999.

[11] T. S. Rappaport, Wireless Communications, Second Edition, Pearson Education, India, 2002.

[12] G. Foschini and M. Gans, “On limits of wireless communications in a fading environment when using multiple antennas”, Wireless Personal Communication, Vol. 6, pp. 311-335, 1998.

[13] M. L. Honig, K. Steiglitz and B. Gopinath, “Multichannel Signal processing for data communications in the presence of crosstalk”, IEEE Transactions on communication, Vol. 38, No. 4, pp. 551-558, April 1990.

[14] A. Scaglione, G. B. Giannakis, S. Barbarossa, “Redundant filterbank precoders and equalizers Part I: Unification and optimal designs”, IEEE Transcation on Signal Processing, Vol. 47, No. 7, pp. 1988-2006, July 1999.

[15] V. Tarokh, H. Jafarkhami, and A.R. Calderbank, "Space-time block codes for wireless communications: Performance results", IEEE Journal on Selected Areas in Communications, Vol. 17, No. 3, pp. 451-460, March 1999.

[16] A.F. Naguib, V. Tarokh, N. Seshadri, and A.R. Calderbank, "Space-time codes for high data rate wireless communication: Mismatch analysis", Proceedings of IEEE International Conf. on Communications, pp. 309313, June 1997.

[17] W. Jakes, “Microwave Mobile Communication”, John Wiley and Sons, 2003.

Engineering & Technology. His research interests include digital signal processing and wireless communication and biomedical engineering.

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ACKNOWLEDGMENT The author’s wishes to express his gratitude to computer simulation lab for interest and support throughout the course of the simulation result described in this paper. The author’s also gratefully acknowledge the contributions of S. M. Alamouti, V. Tarokh, H. Jafarkhami and A.R. Calderbank for their work on Space time block codes and diversity technique of this document.

BIBLOOGRAPHY

Muhammad Sana Ullah (B.Sc.’08- ) was born in Kishoreganj, Bangladesh. He received Bachelor of Science in Electrical & Electronic Engineering degree from Chittagong University of Engineering & Technology in 2008. He is currently a Lecturer in the Department of Electrical & Electronic Engineering of Chittagong University of

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