Performance Analysis of MIMO-OFDM by Spatial Diversity with STBC4

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International Journal of Computer Applications (0975 – 888) Volume 48– No.20, June 2012 Performance Analysis of MIMO-OFDM by Spatial Diversity with STBC4

Bhanu Lavish Kansal 1Department of Electronics and Assistant Professor Telecommunication, Department of Electronics and Telecommunication Lovely Professional University, Punjab Lovely Professional University, Punjab

ABSTRACT analysis its performance under different channels having The main aim of OFDM-MIMO systems is to combine more number of antennas. OFDM technology with the techniques of MIMO systems. The growing demand of multimedia services and the growth 2. OFDM TECHNOLOGY of Internet related contents lead to increasing interest to high In this section, the physical layer of OFDM is implemented. speed communications. OFDM is a type of multichannel Figure 1 shows the block diagram of an OFDM system with modulation that divides a given channel into many parallel SISO configuration. Different blocks are implemented. sub channels or subcarriers, so that multiple symbols are sent 2.1 Source Coding in parallel. In this paper, a simulation model of OFDM- Source coding entails the efficient representation of MIMO system based on STBC4 is built. BER performance information sources. For both discrete and continuous of the system with different number of transceiver antennas sources, the correlations between samples are exploited to like 4X1, 4X2, 4X3, 4X4 with OFDM are analyzed and produce an efficient representation of the information. The simulated under different channels considering different aim of source coding is either to improve the SNR for a modulation modes such as PSK and QAM. The spatial given bit rate or to reduce the bit rate for a given SNR. An diversity is increased by employing OFDM-MIMO with obvious benefit of the latter is a reduction in the necessary STBC. system resource of bandwidth and/or energy per bit to

transmit the information source. A discussion on source Keywords coding requires the definition of a quantity, which measures OFDM, MIMO, STBC, Spatial diversity, BER. the average self information in each discrete alphabet, termed source entropy [4]. 1. INTRODUCTION 2.2 Channel Encoding and Decoding Wireless communication is one of the most vibrant areas in Error control coding, or channel coding, is a method of the communication field today. While it has been a topic of adding redundancy to the sent information so that it can be study since the 1960s, the past decade has seen a surge of transmitted over a noisy channel, and subsequently be research activities in the area. OFDM is one of the promising checked and corrected for errors that occurred in the modulation candidates for a fourth generation broadband transmission. Convolutional codes are commonly specified mobile communication system because of its robustness by three parameters n, k and m, where n is the number of against inter-symbol interference (IS1) [1]. Orthogonal output bits, k is the number of input bits and m is the number frequency division multiplexing (OFDM) technique transfers of memory registers. [5]. The convolutional encoder is used the frequency selective multi path fading channel to flat to correct random error. The coding rate is 1/2 and the channel, so it can reduce the influence of fading [2]. constraint length is 7. Since different data rates are supported Multiple antenna elements are placed both in transmitter and in 802.11a OFDM PHY, puncture is needed after receiver of MIMO system [2]. Its core idea is space-time Convolutional coding. Puncturing is a very useful technique signal processing, which Use multiple antennas to increase to generate additional rates from a single convolutional code. the spatial dimension based on the equal time dimension. So The basic idea behind puncturing is to not transmit some of it can achieve a multi-dimensional signal processing, and it the output bits from the convolutional encoder, thus obtain spatial multiplexing gain and spatial diversity gain. increasing the rate of the code. This increase in rate Multiple input multiple output (MIMO) system could decreases the free distance of the code, but usually the increase capacity linearly with the number of transmitting resulting free distance is very close to the optimum one that receiving antennas without additional power or bandwidth is achieved by specifically designing a convolutional code [3]. for the punctured rate. The paper is organized as follows: At the beginning, the paper introduces the basic principles of MIMO and OFDM, and then further it gives space time block coding scheme of MIMO- OFDM to achieve the spatial diversity, and

16 International Journal of Computer Applications (0975 – 888) Volume 48– No.20, June 2012

Source Channel S I P Interleaving Modulation Data Coding / F /

P F S T

Cyclic Channel Prefix Remove Cyclic S F P De- Channel Prefix Demodulation / F / interleaving Decoding P T S

Receive Data

Figure 1 OFDM Block Diagram

2.3 Interleaving and Deinterleaving of the cyclic properties of the multipliers Fast Fourier Interleaving aims to distribute transmitted bits in time or Transform (FFT) techniques reduce the number of frequency or both to achieve desirable bit error distribution computations to the order of N log N. The FFT is most after demodulation. All encoded data bits shall be interleaved efficient when N is a power of two. Several variations of the by a block interleaver with a block size corresponding to the FFT exist, with different ordering of the inputs and outputs, number of bits in a single OFDM symbol. The interleaver is and different use of temporary memory. FFT can be defined by a two-step permutation. The first permutation implemented in two ways i.e. DIT and DIF. for DIT, the input ensures that adjacent coded bits are mapped onto nonadjacent is bit-reversed and output is in natural order, while in DIF, the subcarriers. The second ensures that adjacent coded bits are reverse is true [8]. FFT can be implemented in two ways i.e. mapped alternately onto less and more significant bits of the DIT and DIF. Two main differences between decimation in constellation and, thereby, long runs of low reliability (LSB) time and decimation in frequency. First, for DIT, the input is bits are avoided.[6] Deinterleaving is the opposite operation of bit-reversed and output is in natural order, while in DIF, the interleaving; i.e., the bits are put back into the original order. reverse is true. Secondly, for DIT complex multiplication is performed before the add-subtract operation, while in DIF the 2.4. Modulation and Demodulation order is reversed. Secondly, for DIT complex multiplication is In telecommunications, modulation is the process of performed before the add-subtract operation, while in DIF conveying a message signal. Digital modulation is the the order is reversed. While complexity of the two structures mapping of data bits to signal waveforms that can be is similar in typical DFT, this is not the case for partial FFT transmitted over an analog channel. The data that we want to transmit over the wireless propogation channel are-digital – 2.6 Cyclic Prefix Insertion and Removal either because we really want to transmit data files or because One way to prevent IS1 is to create a cyclically extended the source coder has rendered the source information into guard interval, where each OFDM symbol is preceded by a digital format. On the other hand, the wireless propogation periodic extension of the signal itself. At the receiver, channel is an analog medium, over which analog waveforms removing the guard interval becomes equivalent to removing have to be sent [7]. For this reason, modulator is used at the the cyclic prefix. transmitter side to convert the digital source data to analog waveforms and at the receiver side; demodulator is used to N L recover the bits from the received waveform.

2.5. IFFT and FFT Cyclic Prefix Data IFFT is useful for OFDM because it generates samples of a waveform with frequency component satisfying orthogonality condition. It also removes the need of oscillator However, by calculating the outputs simultaneously and taking advantage Figure 2. Cyclic Prefix in OFDM Transmission

17 International Journal of Computer Applications (0975 – 888) Volume 48– No.20, June 2012

When the guard interval is longer than the channel impulse bandwidth. MIMO is performing better in terms of channel response, or the multipath delay, the IS1 can be eliminated [9]. capacity in a rich scatter multipath environment than in case However, the ICI, or in-band fading, still exists. The ratio of of environment with LOS. This fact was spectacularly shown in [11]. the guard interval to useful symbol duration is application dependent. Since the insertion of guard interval will reduce In MIMO systems, a transmitter sends multiple streams by data throughput L is usually less than N/4. multiple transmit antennas as shown in figure above. The transmit streams go through a matrix channel which consists 2.7 Channel of all MTMR paths between the MT transmit antennas at the Channel, refers either to a physical transmission medium such transmitter and MR receive antennas at the receiver. Then, the receiver gets the received signal vectors by the multiple as a wire, or to a logical connection over a multiplexed receive antennas and decodes the received signal vectors into medium such as a radio channel. A channel is used to convey an information signal, for example a digital bit stream, from the original information. one or several senders (or transmitters) to one or several Because of these properties, MIMO is an important part of receivers. A channel has a certain capacity for transmitting modern wireless communication standards such as IEEE information, often measured by its bandwidth in Hz or its data 802.11n (Wi-Fi), 4G, 3GPP Long Term Evolution, rate in bits per second. It is not so smooth as received signal is WiMAX and HSPA+. MIMO systems may be implemented in not coming directly from the transmitter, but the combination a number of different ways to obtain either a diversity gain to of reflection, diffraction and scattered copies of the combat signal fading or to obtain a capacity gain. Spatial transmitted signals. Reflection occurs when the signal hits a Diversity is one of the methodology. surface where partial energy is reflected and the remaining is transmitted into the surface. Radio signals may also undergo 3.1 Spatial Diversity diffraction. It is found that when signals encounter an obstacle Diversity is one of the ways to combat this multipath fading. they tend to travel around them. This can mean that a signal The main idea behind diversity is to provide different replicas may be received from a transmitter even though it may be of the transmitted signal to the receiver. If these different "shaded" by a large object between them. This is particularly replicas fade independently, it is less probable to have all noticeable on some long wave broadcast transmissions. copies of the transmitted signal in deep fade simultaneously Scattering occurs when the signal impinges upon rough [12]. MIMO take advantage of the spatial diversity obtained surfaces, or small objects [10]. Types of Channels:- by placing separate antennas in a dense multipath scattering environment. These systems can be implemented in a number 2.7.1. AWGN Channel of different ways to obtain either a diversity gain to combat 2.7.2. Fading Channels signal fading or a capacity improvement. Therefore, the 2.7.2.1 Rayleigh Fading Chanel receiver can reliably decode the transmitted signal using these received signals. This technique involves Space Time Block 2.7.2.2 Rician Fading Channel Coding (STBC) and Space Time Trellis Coding (STTC). 2.7.2.3 Nakagami Fading Channel Diversity techniques can be implemented into different ways. 3.2 Spatial Multiplexing 3. MIMO TECHNOLOGY The first MIMO spatial multiplexing system is proposed in MIMO technology has been developed over many years. [13], known as D-BLAST (Diagonal Bell Labs Layered Space-Time). To reduce complexity, a V-BLAST system is In radio, multiple-input and multiple-output, or MIMO, is the introduced [14]. The key for spatial multiplexing is how to use of multiple antennas at both the transmitter and receiver to recover the original transmitted data stream. The received improve communication performance. It is one of several signals from different antennas interfere with each other. forms of smart antenna technology. The terms input Theoretically, to get rid of the mutual interference, the number and output refer to the radio channel carrying the signal, not to of receiver antennas has to be equal to or larger than the the devices having antennas. number of transmitter antennas. The receiver signal processing algorithm can be based on zero forcing, minimum mean squared error (MMSE), or maximum likelihood (ML). TX1 RX1 Multi - user detection algorithms initially designed for CDMA systems [15] can also be used for spatial multiplexing MIMO receive processing. 3.3 Beam Forming TX2 RX2 A nonli near interpolation and a modified clustering based transmit beam forming schemes are investigated by J. Huang TX3 RX3 et.al to reduce the feedback information and improve performance for a MIMO-OFDM system [16]. It exploits the knowledge of channel at the transmitter. It decomposes the channel coefficient matrix using SVD and uses these decomposed unitary matrices as pre- and post-filters at the Figure 3. Diagram of MIMO system with M Transmitters transmitter and the receiver to achieve near capacity. and N Receivers 3.4. Interference Reduction and Avoidance MIMO has attracted a great attention Interference in wireless networks results from multiple users in wireless communications, because it offers significant sharing time and frequency resources. Interference may be increases in data throughput and link range without additional mitigated in MIMO systems by exploiting the spatial

18 International Journal of Computer Applications (0975 – 888) Volume 48– No.20, June 2012 dimension to increase the separation between users. For discussed above has been designed using the STBC4 code instance, in the presence of interference, array gain increases structure for MIMO-OFDM system. Results are shown in the the tolerance to noise as well as the interference power, hence form of SNR vs BER plot for different modulations and improving the signal-to-noise- plus-interference ratio (SINR). different channels. The performance of MIMO-OFDM system Additionally, the spatial dimension may be leveraged for the purposes of interference avoidance, i.e., directing signal is analyzed using BER analysis. energy towards the intended user and minimizing interference to other users. Interference reduction and avoidance improve 5.1 BER Analysis of MIMO-OFDM System the coverage and range of a wireless network. In this section BER analysis of MIMO-OFDM system using 4. STBC IN OFDM-MIMO STBC4 code structure is done for higher order Modulations over Nakagami and Rician channel. First, M-PSK is OFDM PHY. Layer as well as MIMO systems have been presented over Nakagami fading channel. implemented till now. Further work on OFDM-MIMO has been done for low modulations and low antenna 5.1.1 M-PSK over Nakagami Fading Channel configurations. In MIMO systems, Alamouti scheme has been implemented till now. The transmit diversity technique Over code rate 1/2 proposed by Alamouti was the first STBC .Firstly we implement block diagram of OFDM. After that we will combine OFDM with MIMO systems with the help of STBC Bit error rate for 32psk modulation for different channels 1/2 0 encoder and decoder at the transmitter and receiver side. 10 STBC4 4X1 STBC4 4X2 INPUT STBC4 4X3 -1 STBC4 4X4 10 OFDM STBC OFDM Transmitter Encoder

-2

10 bit error rate bit error

Channel -3 10

-4 10 0 20 40 60 80 100 120 signal to noise ratio(dB) OUTPUT OFDM STBC Decoder Receiver (a) 32-PSK

Bit error rate for 64psk modulation for different channels 1/2 0 Figure 4. STBC IN MIMO-OFDM 10 STBC4 4X1 The data is encoded by a channel code and the encoded data is STBC4 4X2 split into multiple streams that are simultaneously transmitted STBC4 4X3

-1 STBC4 4X4 using multiple transmit antennas [17]. The received signal at 10 each receive antenna is a linear superposition of the different OFDM transmitted signals. The performance criteria for designing channel codes under the assumption that the fading is slow -2 and frequency non-selective is also derived. Performance is 10 shown to be determined by diversity gain quantified by ranks and coding gain quantified by determinants of certain matrices rate bit error that are constructed from the code sequences. A detailed -3 analytical behavior and BER performance of the system with 10 different number of transceiver antennas is given [17], [18].

5. RESULTS & DISCUSSIONS -4 10 In this report behaviour of the MIMO-OFDM under different 0 20 40 60 80 100 120 modulation environments is studied and the effects of signal to noise ratio(dB) increasing the order of the modulation on the BER performance of the system are presented. The system (b) 64-PSK

19 International Journal of Computer Applications (0975 – 888) Volume 48– No.20, June 2012

Bit error rate for 128psk modulation for different channels 1/2 0 Bit error rate for 1024psk modulation for different channels 1/2 10 0 10 STBC4 4X1 STBC4 4X1 STBC4 4X2 STBC4 4X2 STBC4 4X3 STBC4 4X3 -1 STBC4 4X4 10 -1 STBC4 4X4 OFDM 10 OFDM

-2 10 -2

bit error rate bit error bit error rate bit error

-3 -3 10 10

-4 -4 10 10 0 20 40 60 80 100 120 0 20 40 60 80 100 120 signal to noise ratio(dB) signal to noise ratio(dB)

Bit error rate for 256psk modulation for different channels 1/2 0 Figure 5.4: (a)-(f) SNR vs. BER plots for M-PSK over 10 STBC4 4X1 Nakagami channel with code rate 1/2 STBC4 4X2 STBC4 4X3 a) 32-PSK b) 64-PSK c) 128-PSK d) 256-PSK

-1 STBC4 4X4 10 e) 512 -PSK (f) 1024-PSK OFDM

For MIMO-OFDM system SNR vs. BER plots for M-PSK over Nakagami channel with different code rates 1/2 have -2 10 been presented in fig5.4 (a) – (f) employing different antenna configurations. These graphs depicts as we increasing the bit error rate bit error number of transmitting and receiver antennas , the BER keeps on decreasing due to spatial diversity and provide -3 10 better BER performance as compared to OFDM. Table 5.4: SNR improvement for M-PSK in Nakagami channel with 1/2 -4 10 0 20 40 60 80 100 120 Different Modulation Levels SNR improvement signal to noise ratio(dB) for AWGN Channel (d) 256-PSK (db) 32-PSK 5 dB

Bit error rate for 512psk modulation for different channels 1/2 0 10 STBC4 4X1 64-PSK 5 dB STBC4 4X2 STBC4 4X3

-1 STBC4 4X4 10 OFDM 128-PSK 5 dB

-2 256-PSK 5 dB 10 bit error rate bit error 512-PSK 5 dB

-3 10

1024-PSK 5dB

-4 10 0 20 40 60 80 100 120 signal to noise ratio(dB)

(e) 512-PSK

20 International Journal of Computer Applications (0975 – 888) Volume 48– No.20, June 2012

5.1.2 M-PSK over Nakagami Fading Channel Bit error rate for 256psk modulation for different channels 2/3 0 10 with Code Rate 2/3. STBC4 4X1 STBC4 4X2 STBC4 4X3

-1 STBC4 4X4 10 OFDM Bit error rate for 32psk modulation for different channels 2/3 0 10 STBC4 4X1

STBC4 4X2 -2 10 STBC4 4X3 STBC4 4X4

-1 rate bit error 10 OFDM

-3 10

-2 10

bit error rate bit error -4 10 0 20 40 60 80 100 120 signal to noise ratio(dB) -3 10 (d) 256-PSK

-4 10 Bit error rate for 512psk modulation for different channels 2/3 0 20 40 60 80 100 120 0 10 signal to noise ratio(dB) STBC4 4X1 (a) 32-PSK STBC4 4X2 STBC4 4X3

Bit error rate for 64psk modulation for different channels 2/3 -1 STBC4 4X4 0 10 10 OFDM STBC4 4X1 STBC4 4X2 STBC4 4X3 -2 -1 STBC4 4X4 10 10

OFDM bit error rate bit error

-3 -2 10 10

bit error rate bit error

-4 -3 10 10 0 20 40 60 80 100 120 signal to noise ratio(dB) (e) 512-PSK

-4 10 0 20 40 60 80 100 120 signal to noise ratio(dB) Bit error rate for 1024psk modulation for different channels 2/3 0 10 STBC4 4X1 (b) 64-PSK STBC4 4X2 STBC4 4X3 -1 STBC4 4X4 Bit error rate for 128psk modulation for different channels 2/3 10 0 OFDM 10 STBC4 4X1 STBC4 4X2 STBC4 4X3 -2 10 -1 STBC4 4X4 10

OFDM bit error rate bit error

-3 10 -2

10 bit error rate bit error

-4 10 -3 10 0 20 40 60 80 100 120 signal to noise ratio(dB)

(f) 1024-PSK -4 10 0 20 40 60 80 100 120 signal to noise ratio(dB) Figure 5.5: (a)-(e) SNR vs. BER plots for M- PSK over Nakagami channel with code rate 2/3 a) 32-PSK b) 64-PSK c) 128-PSK d) 256-PSK (c) 128-PSK e) 512-PSK (f) 1024-PSK

21 International Journal of Computer Applications (0975 – 888) Volume 48– No.20, June 2012

Bit error rate for 64psk modulation for different channels 1/2 0 SNR vs. BER plots for M-PSK over Nakagami channel for 10 MIMO-OFDM system with different code rates 2/3 have been STBC4 4X1 STBC4 4X2 presented in fig 5.5 (a) – (f) employing different antenna STBC4 4X3

-1 STBC4 4X4 configurations. These graphs depicts as we increasing the 10 OFDM number of transmitting and receiver antennas , the BER keeps on decreasing and provide better BER performance as

-2 compared to OFDM due to spatial diversity. 10

Table 5.5: SNR improvement for M-PSK in Nakagami rate bit error

-3 channel with 2/3 10

Different Modulation Levels SNR improvement

for -4 10 AWGN Channel 0 20 40 60 80 100 120 (db) signal to noise ratio(dB) 32-PSK 5 dB (b) 64-PSK

64-PSK 5 dB Bit error rate for 128psk modulation for different channels 3/4 0 10 STBC4 4X1 128-PSK 5 dB STBC4 4X2 STBC4 4X3 -1 STBC4 4X4 10 OFDM 256-PSK 5 dB

-2 10 512-PSK 5 dB

rate bit error

-3 1024-PSK 5dB 10

-4 10 5.1.3 M-PSK over Nakagami Fading Channel 0 20 40 60 80 100 120 signal to noise ratio(dB)

with Code Rate 3/4. (c) 128-PSK

Bit error rate for 32psk modulation for different channels 3/4 0 Bit error rate for 256psk modulation for different channels 3/4 10 0 10 STBC4 4X1 STBC4 4X1 STBC4 4X2 STBC4 4X2 STBC4 4X3 STBC4 4X3 -1 STBC4 4X4 10 -1 STBC4 4X4 OFDM 10 OFDM

-2 10 -2

bit error rate bit error bit error rate bit error

-3 10 -3 10

-4 10 -4 0 20 40 60 80 100 120 10 signal to noise ratio(dB) 0 20 40 60 80 100 120 signal to noise ratio(dB)

(a) 32-PSK (d) 256-PSK

22 International Journal of Computer Applications (0975 – 888) Volume 48– No.20, June 2012

Table5.6: SNR improvement for M-PSK in Nakagami Bit error rate for 512psk modulation for different channels 3/4 0 10 channel with 3/4 STBC4 4X1 STBC4 4X2 STBC4 4X3 Different Modulation Levels SNR

-1 STBC4 4X4 improvement 10 OFDM for AWGN Channel (db)

-2 32-PSK 5 dB 10

bit error rate bit error 64-PSK 5 dB

-3 10 128-PSK 5 dB

-4 10 0 20 40 60 80 100 120 256-PSK 5 dB signal to noise ratio(dB)

(e) 512-PSK 512-PSK 5 dB

Bit error rate for 1024psk modulation for different channels 3/4 0 1024-PSK 5 dB 10

STBC4 4X1 STBC4 4X2 STBC4 4X3

-1 STBC4 4X4 10 OFDM 5.2 Rician Channel 5.2.1 M-PSK over Rician Fading Channel with

-2 10 Code Rate 1/2 bit error rate bit error Bit error rate for 32psk modulation for different channels 1/2 0 -3 10 10 STBC4 4X1 STBC4 4X2 STBC4 4X3

-1 STBC4 4X4 10 -4 OFDM 10 0 20 40 60 80 100 120 signal to noise ratio(dB)

-2 (f) 1024-PSK 10

rate bit error Figure 5.6: (a)-(f) SNR vs. BER plots for M-PSK over -3 Nakagami channel with code rate 3/4 10 a) 32-PSK b) 64-PSK c) 128-PSK d) 256-PSK For M-PSK over Nakagami channel for MIMO-OFDM

system employing different antenna configurations with -4 10 different code rates 3/4 SNR vs. BER plots have been 0 20 40 60 80 100 120 signal to noise ratio(dB) presented in fig5.6 (a) – (f). Graphs shows as we increasing the number of transmitting and receiver (a) 32-PSK antennas, the BER keeps on decreasing due to spatial diversity and provide better BER performance as compared to OFDM.

23 International Journal of Computer Applications (0975 – 888) Volume 48– No.20, June 2012

Bit error rate for 512psk modulation for different channels 1/2 Bit error rate for 64psk modulation for different channels 1/2 0 0 10 10 STBC4 4X1 STBC4 4X1 STBC4 4X2 STBC4 4X2 STBC4 4X3 STBC4 4X3 STBC4 4X4 -1 STBC4 4X4 -1 10 10 OFDM OFDM

-2 -2 10

bit error rate bit error bit error rate bit error

-3 -3 10 10

-4 -4 10 10 0 20 40 60 80 100 120 0 20 40 60 80 100 120 signal to noise ratio(dB) signal to noise ratio(dB)

(b) 64-PSK (e) 512-PSK

Bit error rate for 1024psk modulation for different channels 1/2 Bit error rate for 128psk modulation for different channels 1/2 0 0 10 10 STBC4 4X1 STBC4 4X1 STBC4 4X2 STBC4 4X2 STBC4 4X3 STBC4 4X3 -1 STBC4 4X4 -1 STBC4 4X4 10 10 OFDM OFDM

-2 -2 10

10 bit error rate bit error bit error rate bit error

-3 -3 10 10

-4 -4 10 10 0 20 40 60 80 100 120 0 20 40 60 80 100 120 signal to noise ratio(dB) signal to noise ratio(dB)

Bit error rate for 256psk modulation for different channels 1/2 0 Figure 5.7: (a)-(f) SNR vs. BER plots for M-PSK 10 STBC4 4X1 over Rician channel with code rate1/2 STBC4 4X2 a) 32-PSK b) 64-PSK c) 128-PSK STBC4 4X3 d) 256-PSK e) 512-PSK (f) 1024-PSK

-1 STBC4 4X4 10 OFDM For code For MIMO-OFDM system with different code rates 3/4 SNR vs BER plots for M-PSK over Rician channel in MIMO-OFDM system have been presented in fig5.7 -2 10 (a) – (f). It shows as we increasing the number of

bit error rate bit error transmitting and receiver antennas, the BER keeps on decreasing and provide better BER performance as

-3 compared to OFDM due to spatial diversity. 10

-4 10 0 20 40 60 80 100 120 signal to noise ratio(dB)

(d) 256-PSK

24 International Journal of Computer Applications (0975 – 888) Volume 48– No.20, June 2012

Table 5.7: SNR improvement for M-PSK in Rician Bit error rate for 128psk modulation for different channels 2/3 0 10 channel with 1/2 STBC4 4X1 STBC4 4X2 Different Modulation Levels SNR improvement STBC4 4X3

forAWGNChannel -1 STBC4 4X4 10 (db) OFDM 32-PSK 5 dB

-2 64-PSK 5 dB 10

bit error rate bit error

128-PSK 5 dB -3 10

256-PSK 5 dB

-4 10 0 20 40 60 80 100 120 512-PSK 5 dB signal to noise ratio(dB)

Bit error rate for 256psk modulation for different channels 2/3 0 10 STBC4 4X1 STBC4 4X2 5.2.2 M-PSK Over Rician Fading Channel STBC4 4X3

-1 STBC4 4X4 With Code Rate 2/3 10 OFDM

Bit error rate for 32psk modulation for different channels 2/3 0 10 STBC4 4X1 -2 STBC4 4X2 10 STBC4 4X3

-1 STBC4 4X4 rate bit error 10 OFDM -3 10 -2 10

bit error rate bit error

-4 10 -3 10 0 20 40 60 80 100 120 signal to noise ratio(dB) (d) 256-PSK

-4 10 0 20 40 60 80 100 120 signal to noise ratio(dB) Bit error rate for 512psk modulation for different channels 2/3 0 10 (a) 32-PSK STBC4 4X1 STBC4 4X2 Bit error rate for 64psk modulation for different channels 2/3 0 10 STBC4 4X3 STBC4 4X1 -1 STBC4 4X4 10 STBC4 4X2 OFDM STBC4 4X3 -1 STBC4 4X4 10 OFDM

-2 10

-2

10 rate bit error

bit error rate bit error

-3 10 -3 10

-4 -4 10 10 0 20 40 60 80 100 120 0 20 40 60 80 100 120 signal to noise ratio(dB) signal to noise ratio(dB) (b) 64-PSK (e) 512-PSK

25 International Journal of Computer Applications (0975 – 888) Volume 48– No.20, June 2012

Bit error rate for 1024psk modulation for different channels 2/3 0 10 5.2.3 M-PSK Over Rician Fading Channel STBC4 4X1 STBC4 4X2 With Code Rate 3/4. STBC4 4X3

-1 STBC4 4X4 10 Bit error rate for 32psk modulation for different channels 3/4 OFDM 0 10 STBC4 4X1 STBC4 4X2

-2 STBC4 4X3 10 -1 STBC4 4X4 10 OFDM bit error rate bit error

-3 10 -2

10 bit error rate bit error

-4 10 -3 0 20 40 60 80 100 120 10 signal to noise ratio(dB)

(f) 1024-PSK -4 10 Figure 5.8: (a)-(f) SNR vs. BER plots for M-PSK over 0 20 40 60 80 100 120 signal to noise ratio(dB) Rician channel with code rate 2/3 a) 32-PSK b) 64-PSK c) 128-PSK d) 256-PSK (a) 32-PSK

Bit error rate for 64psk modulation for different channels 3/4 0 e) 512-PSK (f) 1024-PSK 10 STBC4 4X1 M-PSK over Rician channel for MIMO-OFDM system STBC4 4X2 employing different antenna configurations with different STBC4 4X3

-1 STBC4 4X4 code rates 2/3 SNR vs BER plots have been presented in 10 fig5.8 (a) – (f). These graphs depicts as we increasing OFDM the number of transmitting and receiver antennas , the BER keeps on decreasing due to spatial diversity and -2 provide better BER performance as compared to OFDM. 10

Table 5.8: SNR improvement for M-PSK in Rician rate bit error

channel with 2/3 -3 10 Different Modulation Levels SNR improvement for -4 AWGN Channel 10 (db) 0 20 40 60 80 100 120 signal to noise ratio(dB) 32-PSK 5 dB (b) 64-PSK

64-PSK 5 dB Bit error rate for 128psk modulation for different channels 3/4 0 10 STBC4 4X1 128-PSK 5 dB STBC4 4X2 STBC4 4X3 -1 STBC4 4X4 10 OFDM 256-PSK 5 dB

-2 10 512-PSK 5 dB

rate bit error

-3 1024-PSK 5dB 10

-4 10 0 20 40 60 80 100 120 signal to noise ratio(dB)

26 International Journal of Computer Applications (0975 – 888) Volume 48– No.20, June 2012

Bit error rate for 256psk modulation for different channels 3/4 For MIMO-OFDM system with different code rates 3/4 0 10 SNR vs. BER plots for M-PSK over Rician channel have STBC4 4X1 been presented in fig 5.9 (a) – (f). Graphs shows as we STBC4 4X2 STBC4 4X3 increasing the number of transmitting and receiver

-1 STBC4 4X4 antennas, the BER keeps on decreasing due to spatial 10 OFDM diversity and provide better BER performance as compared to OFDM.

-2 Table5.9: SNR improvement for M-PSK in Rician 10

channel with 3/4 bit error rate bit error

-3 Different Modulation Levels SNR improvement 10 for AWGN Channel (db) 32-PSK 5 dB -4 10 0 20 40 60 80 100 120 signal to noise ratio(dB)

64-PSK 5 dB (d) 256-PSK

Bit error rate for 512psk modulation for different channels 3/4 0 128-PSK 5 dB 10 STBC4 4X1 STBC4 4X2 STBC4 4X3 256-PSK 5 dB -1 STBC4 4X4 10 OFDM

512-PSK 5 dB

-2 10

bit error rate bit error 1024-PSK 5 dB

-3 10

-4 10 6. CONCLUSION 0 20 40 60 80 100 120 signal to noise ratio(dB) In the present work, an idea about the performance of the MIMO-OFDM systems at higher modulation levels (e) 512-PSK and for different antenna configurations is presented. (f) 1024-PSK Performance of MIMO OFDM system is analyzed under different fading channels. MIMO-OFDM system can be Figure 5.9: (a)-(f) SNR vs. BER plots for M-PSK over implemented using higher order modulations to achieve Rician channel with code rate 3/4 large data capacity. The motive of using high order a) 32-PSK b) 64-PSK c) 128-PSK d) 256-PSK e) 512-PSK antenna configuration (4 X 4) is to increase the space diversity, which will further decrease the BER at given SNR as compared to lower order Antenna configurations Bit error rate for 1024psk modulation for different channels 3/4 0 10 namely 1 X 1, 2 X 2, 4 X 4 and 6 X 6. By doing so, even STBC4 4X1 higher data capacity at any given SNR can be achieved. STBC4 4X2 STBC4 4X3 The system is tested under Nakagami and Rician channel

-1 STBC4 4X4 10 environments. The BER will decrease on increasing the OFDM no. of Transmitters or Receivers due to spatial diversity. The motive of using high order antenna configuration

-2 10 (4 X 4) is to increase the space diversity, which will further decrease the BER at given SNR as compared to bit error rate bit error lower order Antenna configurations namely 1 X 1, 2 X 2,

-3 4 X 4 and 6 X 6. By doing so, even higher data capacity 10 at any given SNR can be achieved.

-4 10 0 20 40 60 80 100 120 signal to noise ratio(dB) (f) 1024-PSK

27 International Journal of Computer Applications (0975 – 888) Volume 48– No.20, June 2012

7. ACKNOWLEDGEMENTS IEEE Midwest symposium on circuits and systems, Vol. 2, pp 938-942, 2001. It gives me great pleasure to have opportunity to acknowledge and to express gratitude to those who were associated with my [9] W. Henkel, G. Taubock, P. Odling, P. O. Borjesson & thesis. First of all I would like to thank to my guide Mr. Lavish N. Petersson, “The Cyclic Prefix of OFDM/DMT– A Kansal had given me his full support in guiding me. I would also Analysis”, International Zurich Seminar on Broadband like to thank Ms. Geetanjali for her kind support during this Communications, Issue 2, pp 1-3, 2002. work. I am also thankful to Mr. Bhupinder Verma, Head of Department, for providing us with the adequate [10] E. Casas & C. Leung, “Performance of OFDM/FM scheme for data transmission over fading mobile radio infrastructure in carrying the work. At last I shall always remain indebted to them for their excellent guidance in my thesis. channels”, 36th IEEE Vehicular Technology Conference, Vol. 36, Issue 5, pp 103-108, 1986. 8. REFERENCES [11] A. V. Zelst & T. C. W. Schenk, “Implementation of a MIMO OFDM-Based Wireless LAN System,” IEEE [1] Chang-Jun Ahn & lwao Sasase, “The effects of Transaction on Signal Processing, Vol. 52, Issue 2, pp modulation combination, target ber, doppler frequency, 483-494, February 2004. and adaptation interval on the performance of adaptive [12] H. Hourani, “An overview of diversity techniques in ofdm in broadband mobile channel” IEEE wireless communication systems,” IEEE JSAC, pp. Transactions on Consumer Electronics , Vol.48, Issue 1200-5, October 2004. 1, pp-167-174, 2002. [13] G. J. Foschini, “Layered space-time architecture for [2] Z. Jie, L. liang & LI jin , “Performance Analysis of wireless communication in a fading environment when Space Time Block Code in MIMO-OFDM Systems” using multi-element antennas”, Bell Labs Tech. J., vol. International Conference on Communication Software 1, no. 2, pp. 41 - 59, 1996. and Networks, pp-13-16, 2011. [14] G. J. Foschini, G. D. Golden, P. W. Wolniansky, & R. [3] S. H. & Deuk-Su Lyu, “Physical Layer A. Valenzuela, “Simplified processing for wireless Implementation and Evaluation of Multiple Input communication at high spectral efficiency”, IEEE J. Multiple Output- Orthogonal Frequency Division Select. Areas Commun. vol. 17, pp. 1841 – 1852, Nov. Multiplexing (MIMO-OFDM) System” International 1999. Conference on Communication Technology Proceedings, Vol.2, pp-1348-1352, 2003. [15] S. Verdu, Multiuser Detection. Cambridge University Press, 1998. [4] B. P. Lathi, “Modern Digital and Analog Communication Systems” by CBS College Publishing, [16] J. Huang, J. Zhang, Z. Liu, J. Li & X. Li, “Transmit 1983. Beam forming for MIMO-OFDM Systems with Limited Feedback”, IEEE Vehicular Technology Conference, pp [5] IEEE Standard 802.11a White Paper. IEEE Standards 1-5, 2008. Board. [17] V. Tarokh, N. Seshadri & A. R. Calderbank, “Space– [6] IEEE Standard 802.11a. IEEE Standards Board 1999 Time Codes for High Data Rate Wireless Edition. Piscatawa, USA. Communication: Performance Criterion and Code [7] P. S. Mundra, T. L. Singal & R. Kapur, “The Choice of Construction”, IEEE Transactions on Information A Digital Modulation, Schemes in A Mobile Radio Theory, Vol. 44, Issue 2, pp 744-765, 1998. System”, IEEE Vehicular Technology Conference, [18] Y. Huang, B. Pei, & H. Zhang, “System Performance Issue 5, pp 14, 1993. Research and Analysis of MIMO-OFDM .Based on [8] A. Sadat & W. B. Mikhael, “Fast Fourier Transform for Space Time Block Codes”, International Conference on High Speed OFDM Wireless Multimedia System”, 44th Intelligent Control and Information Processing, pp 414- 417, 2010.