Improved Minimum Variance Channel Estimation Techniques for OFDM Systems

Abstract

Orthogonal frequency division multiplexing (OFDM) systems face challenges in channel estimation due to noise, variability, and the doubly dispersive nature of wireless channels, which degrade performance. To address these challenges, a multichannel minimum variance double dispersive channel estimator is proposed. The method employs a hybrid approach that combines subspace and minimum variance techniques, optimizing the filter bank output power under a signal-to-noise ratio (SNR) constraint. This design preserves the desired signal while effectively suppressing disturbances, achieving robust performance with reduced computational complexity compared to existing methods. Simulation results demonstrate that the proposed estimator outperforms subspace and asymptotic methods in terms of normalized mean square error (NMSE) and bit error rate (BER), particularly under low SNR and frequency-selective conditions. These findings highlight its potential for enhancing spectral efficiency and data integrity in advanced OFDMbased communication systems