Effect of Side Information on the Number of Measurements and Dynamic Sparse Channel Tracking using Compressed Sensing

In this paper, the problem of dynamic sparse channel estimation in orthogonal frequency-division multiplexing (OFDM) systems is studied using norm-based methods. In this method, a mixture of norms is performed based on sparse recovery using side information for simultaneous extraction of both sparseness and dynamic features. For this purpose, temporal correlation of dynamic channels is considered as the side information whose effect on the number of measurements and dynamic channel tracking is investigated. Simulation results show an increase on both estimation accuracy and tracking of dynamic sparse channels for some decibels and also reduction of the number of measurements compared to some conventional reconstruction algorithms.