An Efficient MAPSO Model for Interference Cancellation and Optimal Channel Estimation in MIMO-OFDM System

Among numerous wireless communication networks, MIMO-OFDM plays a vital role in the enhanced data transmission rate. Numerous researches are performed based on estimating the channel to attain optimal output. However, because of the enhanced bit error rate, attaining an optimal estimated channel is a challenging task. So to decrease the bit error rate and to enhance the system performances, this article aims in proposing the mutable weight-based adaptive particle swarm optimization (MAPSO) based MIMO-OFDM approach for the optimal channel estimation. This approach consists of four phases: OFDM with MIMO, STBC based OFDM coding, signal recognition, and MC-CDMA for the evaluation of optimal channel estimation. The MAPSO algorithm is used in the MC-CDMA approach for tuning the parameters at every level of channel estimation to achieve optimal value. The metrics such as SER, BER, MSE, and NMSE are computed for the proposed approach to achieve better performance. The comparative analysis is carried out with several other existing approaches and the experimental results reveal that the proposed MAPSO based MIMO-OFDM approach outperformed other approaches.