Stopping Criteria for Compressive Sensing OFDM Channel Estimation using OMP

Abstract

Compressive sensing channel estimation techniques can be used to exploit the sparse nature of the virtual channel when the dimensions of the virtual channel are larger than then number of physical paths in the multipath channel. Through use of compressive sensing and sparse recovery techniques we can achieve better channel estimates with fewer number of pilot resources used in traditional techniques. We present an analysis of stopping criteria when using the Orthogonal Matching Pursuit (OMP) sparse recovery method to estimate a single input single output Orthogonal Frequency Division Multiplexed channel. We show that under ideal conditions, the lower bound of performance can be reached in few pilot subcarriers and demonstrate that additional subcarriers provide no further benefit under simpli-fied conditions. We also demonstrate the impacts of imperfect stopping criteria and basis mismatch.