Loop Feedback Maximization for Channel Estimation in MIMO Communication

Abstract

Background: Signal estimation and its performance have always remained a challenge for wireless communication society. To achieve noise immunity, the conventional recursive least squares estimation needs information of the noise measurements of the filtered process. A new estimation approach has been proposed that does not take knowledge of the noise statistics. Statistical Methods: A new min-max channel estimation approach based on state stabilization is proposed to achieve the objective of noise mitigation and higher performance in MIMO systems, using time variant interference modelling. The approach proposed has been simulated using the MATLAB environment with random input data. Findings: The performance of the Bit Error Rate (BER) over the specific range of Signal to Noise ratio for the existing Recursive Least Squares estimation and proposed a Min-Max estimation approach of different noise densities and fading factors. Conclusion: The results obtained indicate that the bit error rate of Recursive Least Squares estimation is more when compared with the Min-Max approach. Therefore, it is concluded that the proposed Min-Max estimation approach is more efficient when compared with the Recursive Least Squares estimation.