Adaptive Step Size Iterative Hard Thresholding-based Time-Varying Sparse Channel Estimator

Abstract

This paper focuses on addressing an issue related to the estimation of channels that are both time-varying and sparse in broadband wireless communication systems. To ensure coherent detection of a transmitted signal, there is a need for robust tracking and estimation of the sparse channel. An enhanced time-varying sparse channel estimator is proposed based on the exploitation of inherent temporal correlation in the channel. It is named adaptive step size iterative hard thresholding (ASS-IHT)- based time-varying, sparse channel estimator. The ASS-IHT-based estimator is documented in comparison with some other estimators. From the results obtained from the simulation performed, the proposed ASS-IHT-based estimator performs better than all the other estimators simulated in this paper. This unique performance can be attributed to (i) the effectiveness of the original algorithm, the iterative hard thresholding upon which the estimator is built, (ii) the exploitation of the sparse channel’s inherent temporal correlation, and (iii) the enhancing effects of the adaptive step size incorporated into the estimator. In terms of the comparative computational complexity costs, the proposed ASS-IHT-based time-varying estimator’s complexity cost is within the range of the complexity costs of other channel estimators simulated in this paper.