Performance evaluation of LS algorithm in both Training-Based and Semi-Blind channel estimations for MIMO Systems

Abstract

There are many algorithms that can be used in a channel estimator. In this investigation, performance of LS algorithm in a training-based as well as a semi-blind channel estimation evaluated and their results has been compared. Simulation results show that performance of a semi-blind estimator is better than a training-based estimator. It is interesting for us due to transmitting less required training bits than a training-based algorithm and hence lower redundancy. Therefore we will achieve more bandwidth efficiency with better performance. Training-based method needs 100 times more additional bits than semi-blind method whereas semi-blind method needs only 25% more computational time to convergence.