The Contribution of Artificial Intelligence in Blind Equalization Using SOSA-MIMO Algorithm with QOSTBC Coding

Abstract The recent evolution in communications forces us to rely on AI to improve the quality of communications. Artificial intelligence has become one of the necessities in the development of scientific life. In this article, we integrate artificial intelligence into blind equalization using the coding technique QOSTBC with Multi-input Multi-output (MIMO) transmission. The Multi-input Multi-output (MIMO) transmission and the blind equalizer schemes by using the QOSTBC coding have become the techniques of choice for increasing spectral efficiency in bandwidth-congested areas are hit in demand nowadays, especially in mobile applications, where devices with size, weight, and power constraints are common. In this paper, we propose a new blind equalizer using the second-order statistical algorithm in a MIMO system with QOSTBC coding used. QOSTBCs with MIMO-SOSA are used to enhance the energy efficiency of the communication system with 8; 4 and 2 antennas. We obtain the optimal performance that ensures full diversity and maximizes the QOSTBC minimum coding gain distance. Simulation results are presented for MIMO-SOSA under 5g wireless Rayleigh channels so that a fair performance comparison with other reference techniques can be established. The results show that by using MIMO-SOSA along with a coding QOSTBC and with diversity in the fading channel and thus low BER at high SNR can be ensured. More importantly, it is also shown that QOSTBC using MIMO-SOSA achieves a better error performance than those using conventional modulation format.