Improving BER Performance of Massive MIMO Scheme over Rayleigh Fading Channel

In massive multiple input multiple output (mMIMO) scheme, the system capacity can be improved without additional bandwidth or transmit power by using a huge antenna array at base station with as much separation between antenna elements as possible. Unfortunately, its performance depends on having a perfect channel state estimate between the base state and the users. In this paper, the bit error rate (BER) performance of a mMIMO scheme is improved using genetic algorithm-based optimization with simulation performed in MATLAB software environment. The genetic algorithm used selects the best signal required for effective transmission. Four different antenna configurations in the order of 2x2, 4x4, 8x8 and 16x16 were considered for the simulation. The encoding and decoding were done using an STBC coded. Also, filter bank multicarrier-offset quadrature amplitude modulation (FBMC-OQAM) scheme was used and simulation was carried out for 4-FBMC-OQAM, 16 FBMC-OQAM, and 64 FBMC-OQAM order. The BER is computed for both the optimized and un-optimized mMIMO schemes, and the performance of both schemes is compared. Simulation results show a significant improvement in the BER of the optimized mMIMO compared to the normal (coded) MIMO scheme. The overall results show that the optimized mMIMO experience a reduced BER when compared to the normal mMIMO. In both cases, the BER reduces gradually as the number of antenna increases.