IRJET- Performance Analysis of MIMO-OFDM System using Different Antenna Configurations
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This document analyzes the performance of a MIMO-OFDM wireless communication system using different antenna configurations through simulation in MATLAB. It finds that the system performs better when diversity is increased at both the transmitter and receiver sides. Specifically, it shows that bit error rate decreases and signal-to-noise ratio increases as the number of receiving antennas is increased when using BPSK modulation over an AWGN channel. The performance of MIMO-OFDM is evaluated for different detection methods and antenna configurations, and zero-forcing with successive interference cancellation is found to improve bit error rate compared to other techniques.
IRJET- Performance Analysis of MIMO-OFDM System using Different Antenna Configurations
- 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 06 | June 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal Page 218 Performance Analysis of MIMO-OFDM System Using Different Antenna Configurations Prof. Nilesh P. Bodne1, Prof. Pranjali. Dahikar2, Priti E. Pote3 1,2,3Department of Electronics & Communication Engineering, Nagpur,India ---------------------------------------------------------------***---------------------------------------------------------------- Abstract:- MIMO-OFDM technology a simple wireless communication system is simulated based on the principles of technical analysis. It is a high data rate and low power consumption. It transmitted data through spatial multiplexing and spatial diversity to improve the data rate and reliability. MIMO-OFDM system performs better when the diversity of antenna is increased specially at receiver side. MIMO-OFDM system performed by using different antenna configuration in AWGN channel and Rayleigh fading channel. BER is determined by using two different detector such as ZF and MMSE with the help of MATLAB. Keywords:-MIMO,OFDM,BER,AWGN,ZF,MMSE,BPSK I. INTRODUCTION Wireless communication system is to provide high data rate wireless access at high quality of service(QOS). MIMO is the antenna technology for wireless communication in which multiple antenna are used at both the transmitter and receiver. The antenna at each end of the communication circuit are combined to minimize error and optimize data speed. The spatial multiplexing and spatial diversity used to improve the data rate and reliability. OFDM is a method of encoding digital data on multiple carrier frequencies. It is a frequency-division multiplexing (FDM) scheme used as a digital multi-carrier modulation method. OFDM is digital modulation in which the data stream is split into n parallel stream of reduced data rate with each of them transmitted on separate subcarriers. It has been proposed as a transmission method to support high-speed data transmission over wireless link in multipath environments. MIMO-OFDM is the interface for 4G and 5G broadband wireless communications. It combines multiple-input, multiple-output technology, which multiplies capacity by transmitting different signals over multiple antenna, and OFDM which divides a radio channel into a large number of closely spaced sub channels to provide more reliable communications at high speeds. MIMO-OFDM system gives good coverage in non-line-of-sight environment. Reliable transmission, high peak data rates as well as high spectral efficiency. II. MULTIPLE INPUT-MULTIPLE OUTPUT SYSTEM Most wireless communication systems use Single Input Single Output (SISO) systems where a single transmit (Tx) antenna is used for transmission to single receiver(Rx) antenna. Additional transmitting and receiving antennas can be used to provide better result at the receiver. Now a days Multiple input multiple output communication system used. MIMO technique have three categories. First category uses the increasing of spatial diversity o enhance the power efficiency. While the other category uses to increasing the capacity by using layered method. The third category analyzing the coefficient matrix of the channel and uses these analyzing unitary matrices of the filter in transmitter and receiver to improve the capacity. MIMO increase system capacity by means of spatial multiplexing. Making use of same frequency resources that would be utilized by a SISO system, MIMO systems benefit from multipath propagation and multiply transfer rates by taking advantages of random fading multipath delay spread. In additional MIMO uses spatial diversity and spatial multiplexing to transmission of data. Spatial diversity use at both at the transmitter and the receiver, it improve the transmission quality in terms of bit-error rate(BER). Spatial multiplexing used to increase the capacity of a MIMO links by transmitting independent data stream in the same time slot and frequency band simultaneously from each transmit antenna. Figure 1 shows the general structure of an M x N MIMO wireless system. It can be seen that the MIMO channel is an N x M matrix channel consisting of M·N sub channels. The MIMO system can also be viewed as a combination of multiple transmit beam formers, each transmitting to one of the m Rx antenna. The MIMO technology is a very effective method of increasing the capacity of the channel and system. We suppose, MT= the number of transmitting antennas. xj(t)= the transmitted signal, where j=1,…,MT. MR= the number of receiving antennas. yi(t)= the received signal, where, i=1,…, MR. then the relation between the transmitted signal and received signal is written as:
- 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 06 | June 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal Page 219 Where, ℎi,j(t) denotes the channel impulse response between the transmitting antenna of number j and the receiving antenna of number i. The channel of the MIMO system can be expressed by a matrix ……….(2) Fig 1. M×N MIMO System Fig 2.Block Diagram of MIMO System The receiver with multi-antenna can separate and decode the data stream by using advanced space-time coding. the N sub-streams are sent to the channel at the same time and each transmitted signal occupies the same frequency band. The bandwidth is not increase. If the channel are independent, the MIMO system can create a number of parallel space channels. It increase the data rate by using these channels to transmit information independently. A. MIMO Channel Capacity The channel capacity is given by ……………(3) Where IN is the identity matrix, the vector h represents the channel gain or transfer function between the single Tx antenna and the Rx antenna array, and ℎK is the Hermitian transpose of h, where H is the N x M MIMO channel matrix. III. ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING SYSTEM Fig 3. Block Diagram of OFDM System Fig shows the block diagram of OFDM system. OFDM is the combination of modulation and multiplexing. Multiplexing is applied to independent signals but these independent signals are a sub-set of the one main signal. In OFDM the signal itself is first split into independent channels. Modulated by data and then re-multiplexed to create the OFDM carrier. IV. Rayleigh Fading Rayleigh fading is a statistical model for the effect of a propagation environment on radio signal, it is used by wireless devices. Rayleigh fading models assume that the magnitude of a signal that has passed through such a transmission medium will vary randomly. Rayleigh fading is most applicable when there is no dominant propagation along a line of sight between the transmitter and receiver.
- 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 06 | June 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal Page 220 V. MIMO-OFDM MIMO-OFDM is the most competitive technology for 4G and 5G broadband wireless communication. The combination of MIMO-OFDM is useful for transmission of higher data rate. MIMO signal can improve wireless communication system through spatial diversity and special multiplexing method. We have OFDM system by using OFDM system we can transmit data or signal. For that purpose, we have to use either TDMA or FDMA in a serial port or in parallel port in different frequency format or single frequency format. By using our system we can eliminate problem which is found in data transmission over antennas and system quality of service. VI. SIMULATION RESULTS In MIMO-OFDM there is a one or more transmit antenna and one or more receive antenna. This technique is simulated by using MMSE (Minimum Mean Square Error Equalization) and ZF (Zero Forcing Equalization) detection for BPSK modulation with AWGN channel with the help of MATLAB version 9.4a. The simulation result plotted between bit error rate (BER) and signal to noise ratio (SNR). The bit error rate is detected for various SNR values. Fig 4.BER for BPSK modulation in AWGN with receiver diversity Fig shows the BER performance for MIMO-OFDM System using BPSK modulation Technique. Here we can use the one transmitting antenna and multiple receiving antenna just like 1*1,1*2,1*4,1*8. We perform the graph between the bit error rate and Eb/No, here bit error rate decreases and signal to noise ratio is increases. The bit error rate is calculated for simulation and theoretically and the bit rate is 10^6. The number of transmitting antenna as well as number of receiving antennas we will get better BER and the SNR value is also decreasing. Fig 5.shows the BER performance a MIMO-OFDM Fig shows the BER performance for MIMO-OFDM System using BPSK modulation technique for multiple configuration here zero forcing equalization (ZF),zero forcing equalization for successive interference cancellation and minimum mean square error detector are used. Fig 6.BER for BPSK modulation with 2×2 MIMO and ZF-SIC equalizer Fig shows the 2×2 MIMO system with zero forcing equalizer with 1*1 system for BPSK modulation in Rayleigh channel. The graph perform between Bit Error Rate and Average Eb/No it will try to improve the bit error rate performance by trying out successive interference cancellation. It consist of Rayleigh fading with multiple channel and BPSK modulation.
- 4. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 06 | June 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal Page 221 Fig 7.BER for BPSK modulation with 2×2 MIMO and ZF-SIC- sorted equalizer Fig shows that the BPSK modulation with 2 transmitter and 2 receiver MIMO system with zero forcing equalizer. It consist of Rayleigh fading with BPSK modulation. It improve the bit error rate performance by trying out successive interference cancellation with sorted equalizer. CONCLUSION Here we have analysis a simple MIMO-OFDM wireless communication system it is simulated in MATLAB. The simulation result shows that the system has good performance when diversity is increased both at the transmitter and receiver side of MIMO-OFDM system. The BER performance of MIMO-OFDM is analyzed for MMSE and ZF detection using different antenna configuration and BPSK modulation. REFERENCES 1. K. M. Ahmed and S. P. Majumder, “Performance Analysis of a MIMO- OFDM Wireless Communication System With Convolutional Coding,” in proceedings of 5th International Conference on Electrical and Computer Engineering (ICECE-2008), IEEE, pp. 892-899, December 2008. 2. Z. Iqbal and S. Nooshabadi, “Effects of channel coding and interleaving in MIMO-OFDM systems,” IEEE Int. Midwest Sym. on Cir. and Sys. (MWSCAS), Seoul, Korea, pp. 1–4, August 2011. 3. P. Samundiswary and SelviaKuriakose,” BER Analysis of MIMO-OFDM Using V-BLAST Syetem for Different modulation Schemes”, Dept of Electronics Engineering Pondicherry IEEE, 2012. 4. Z. Iqbal, S. Nooshabadi, and H.-N. Lee, “Efficient interleaver design for MIMO-OFDM based communication systems on FPGA,” IEEE Int. Sym. on Consumer Electron. (ISCE), Harrisburg, PA, pp. 62– 66, June 2012. 5. Z. Iqbal, S. Nooshabadi, and Heung-No Lee, “Analysis and Design of Coding and Interleaving in a MIMO- OFDM Communication System,” IEEE Transactions on Consumer Electronics, vol. 58, no. 3, pp. 758- 766, August 2012. 6. Muhammad Kamran asif ,KhanZeb , Muhammad Ali Danish,” Performance Analysis of MIMO-OFDM Communication System,” Department of Electrical Engineering IEEE,2014. 7. A. A. Sahrab and I. Marghescu, “MIMO-OFDM: Maximum Diversity using Maximum Likelihood Detector”, in proceedings of 10th International Conference on Communication (COMM) IEEE, pp. 1-4, May, 2014. 8. ArunAgrawal and SaurabhN.Mehta,”Design and performance analysis of MIMO-OFDM system using different antenna configurations”, International Conference on Electrical Electronics and Optimization Technique (ICEEOT) IEEE,2016.