Optimal channel estimation and interference cancellation in MIMO-OFDM system using MN-based improved AMO model

In recent years, MIMO-OFDM plays a significant role due to its high-speed transmission rate. Various research studies have been carried out regarding the channel estimation to obtain optimal output without affecting the system performances. But due to increased bit error rate achieving optimal channel estimation is considered as a challenging task. Therefore, this paper proposes the modified Newton’s (MN)-based Improved Animal Migration Optimization (IAMO) algorithm in MIMO-OFDM system. The significant objective of this proposed approach involves the minimization of bit error rate and to enhance the system performance. In this paper, a modified Newton’s method is utilized to determine the discover capability and to speed up the convergence rate thereby obtaining the optimum search space positions. In addition to this, the proposed method is utilized to restrict the interference in the MIMO-OFDM systems. Finally, the performance of the proposed method is compared with other channel estimation methods to determine the effectiveness of the system. The experimental and comparative analyses are carried out, and the results demonstrate that the proposed approach provides better frequency-selective channels than other state-of-the-art methods .