Improvement Of BER Using MIMO-OFDM

Abstract

The MIMO-OFDM technology is used for developing various wireless communications. The combination of multiple input multiple output and orthogonal frequency division multiplexing gives improvement in Bit error rate, capacity and reliability. To achieve high throughput, MIMO with higher orders of modulations is used. The MIMO-OFDM technology in wireless helps to use maximum bandwidth with less cost. Space time block coding along with MIMO gives improvement in Bit Error Rate. The performances of the various systems are evaluated by comparing the BER and SNR.

Keywords: MIMO, OFDM, BER, BPSK, QPSK, QAM

Introduction

Recently, the mobile communication systems are experiencing a dramatic increase with even data rates more than 1gbps. A reliable link design is a challenging task in wireless environment. Various techniques are implementing to improve the performance of the MIMO systems. MIMO systems are the most promising technology for the future generations. MIMO gives the chance to improve link capacity and spectral efficiency.

The technique here we used is Space Time Block Coding which gives maximum data rate and diversity gain. OFDM is a well-known method to transmit the high data in wireless medium. Now the high rate wireless communications get attracted and research are being undertaken to challenge the context of the WLAN and in other multimedia networks. These wireless systems are very popular which helps in communication. OFDM converts wideband communication channel into parallel flat sub channels. OFDM is popular because of its bandwidth efficiency. OFDM is the multicarrier technique and was considered as the future generative networks. OFDM is now emerged as popular block modulation technique. OFDM combined with MIMO helps in making the wireless communication better.

The combination of MIMO and OFDM is considered as the most powerful technique. The MIMO - OFDM technology has been a great fame and a boon for the coming generation’s wireless networks and boost the performance of wireless communication systems. The MIMO-OFDM system performance is evaluated with the help of MIMO channel measurement data. The MIMO performance was compared to the other detection systems through computer simulations. The performance of MIMO-OFDM was evaluated by the Bit Error Rate versus Signal to Noise ratio. By this ISI was reduced and has high reliability and better performance, high data rate is achieved. In this paper, MIMO-OFDM techniques are used to increase the performance efficiency by having multiple transmits and receive antenna for the Rayleigh channel.

Bit Error Rate

In wireless communication, the information is transmitted in digital stream of 0’s and 1’s. During transmission, data can’t be received properly. Bit error rate is a parameter which can be used to analyse the performance of communication system. Bit Error Rate is the average rate at which bit errors occur during communication process. Bit Error Rate is defined as ratio of number of bits in error to number of bits transmitted. The bit error probability is the expected value of the BER in any wireless communication system, where there is a chance of error in communication system due to addition of noise. The BER can be improved by selecting a signal of strong strength, by selecting a slow and robust and proper modulation scheme or line coding scheme, and by applying channel coding schemes such as redundant forward error correction codes.

MIMO Technology

MIMO means Multiple Input Multiple Output. This means MIMO technology uses multiple antennas at transmitter side and as well as receiver side. By using multiple antennas at both transmitter and receiver side improves the system performance capabilities as compared to single antenna systems. The use of Multiple Input Multiple Output (MIMO) systems has increased due to its robustness against Multipath fading, increase in the Spatial Multiplexing Gain and Spatial Diversity Gain. The signal model of the MIMO is represented in a matrix form is given as: r = H. s + n

Where r is the vector of the receiver signal, s is the vector of the transmitted signal and n is the vector of the additive Gaussian noise with zero mean and a variance of. The linear form of the above equation is given by: For 2 x 2 MIMO the expression is reduced into: Fig: MIMO system for M transmitting and N receiving antennasThe multiple signals are transmitted simultaneously from the multiple antennas through the channel and the receiver receives the signals that are transmitted. By using multiple antennas we can achieve higher data transmission rates, diversity gain, spatial multiplexing gain, wider coverage and higher reliability without using additional frequency spectrum. A reliable performance is obtained by diversity which can be achieved in MIMO systems.

Space Time Block Coding

Space Time block coding is a technique to achieve high diversity performance which simultaneously transmits the same data over different antennas at different times. In Space Time Block Coding technique multiple copies of same data are transmitted over number of antennas and to exploit the various received versions of data to improve reliability of data transfer. The receiver combines all the copies of received signal in an optimal way to extract as much information from each of them. Fig: 2X2 STBC Where X1, X2 are modulated symbolsThe Received vectors areY1 = h1(X1) + h2(X2) + n’1 (First time slot)Y2 = h1(-X*2) + h2(X1*) + n2 (Second time slot) Space Time Block Coding is generally represented by a matrix

OFDM Technique

FDM means Orthogonal Frequency Division Multiplexing. It is a multicarrier modulation technique in which input data is divided in to a number of parallel sub streams and transmitted over the individual subcarriers which are orthogonal to each other. Hence, the frequency selective wideband channel is divided into number of parallel narrow band sub-channels which leads to flat fading. The individual sub carriers are orthogonal to each to each other and thus it avoids the interference between adjacent sub carriers. OFDM is a broad band system and operates on large bandwidth. Hence it gives higher data rates in wireless transmission. If the symbol time is very less than delay time then Inter symbol Interference will occur. To overcome this problem the entire bandwidth is divided into sub bands. For each sub band, there is a sub carry.

Hence by this way the symbol time is not less than the delay time. Therefore Inter Symbol Interference gets eliminated. The IFFT gives OFDM symbol consisting of the sequence x[n] of length N. The cyclic prefix is added to the OFDM symbol so that inter symbol interference is eliminated. The received signal is passed through the channel and at the receiver the cyclic prefix is eliminated. The samples are serial to parallel converted and passed through FFT. The output is demodulated to recover the data.

MIMO-OFDM System

The system performance is analysed by MATLAB software in terms of Bit Error Rate. Here the information sequence is generated using random integer generator. In this model we use convolution coding as forward error correction code. The output is converted into OFDM symbols and transmitted through multiple antennas by STBC technique over the multipath fading channel. Convolution coding is used to improve the performance of the communication systems. The main reason for applying convolution coding in wireless system is to reduce bit error rate.

Simulation Results

The MIMO OFDM system is performed for different modulation orders using efficient channel coding technique. The below figure shows BER plot of STBC-OFDM system. By increasing antenna number there is an improvement in BER. Fig: BER plot of 2X1 and 2X2 STBC – OFDM with convolution codingFig: Effect of Convolution codingFrom the above figure it is clear that the BER for the system with convolution coding (CC) is less than for the system without convolution coding. Thus the convolution coding reduces the errors as compared with encoded BER plots. Fig: BER plot of 2x2 STBC-OFDM with convolution coding

Conclusion

The MIMO system provides maximum capacity and maximum BER versus SNR theoretically and it is proved in the simulation results. The main objective of this paper is to evaluate the performance of MIMO systems in wireless communication. From this paper the MIMO-OFDM performance is decided as better result than SISO-OFDM and MISO-OFDM. It is proved from the simulation results obtained from MIMO and MIMO-OFDM with a random generated data. While comparing the BER vs. SNR among these three systems MIMO-OFDM obtains a better BER value and proved it is efficient for high rate data transmission in wireless communication. As an enhancement, BER rate is decreased by increasing efficiency. MIMO-OFDM can be compared with other similar techniques and the performance should be evaluated.