DCD-Based Joint Sparse Channel Estimation for OFDM in Virtual Angular Domain

Abstract

Massive Multiple Input Multiple Output (MIMO) is a promising technique for communications due to the high data transmission rate. To harvest the benefit from the massive MIMO, it is necessary to have accurate channel estimates. Such channels often exhibit sparsity in the virtual angular domain. This paper proposes a dichotomous coordinate descent (DCD) based algorithm for joint sparse channel estimation in the virtual angular domain for the orthogonal-frequency-division-multiplexing massive MIMO. We show that compared to the distributed sparsity adaptive matching pursuit algorithm previously proposed for this purpose, the DCD-based algorithm has significantly lower complexity and better channel estimation performance.

Keywords

• Channel estimation
• common sparsity
• compressive sensing
• dichotomous coordinate descent
• distributed sparsity adaptive matching pursuit
• joint sparse recovery