Semi-Blind Structure-Based SIMO System Estimation

Abstract

This paper introduces a new semi-blind single in-put multiple output (SIMO) channel estimation algorithm. The algorithm exploits both the training-based samples and the received samples to estimate the channel state information. The structure-subspace blind method, which uses the inherent Toeplitz structure that exists in many systems, combined with the least squares approach are used. The proposed algorithm is tested via simulation and showed an improved performance.