DOA Estimation for Coherently Distributed Sources Considering Circular and Noncircular Signals in Massive MIMO Systems

In mobile communication, the signal that a base station received cannot be regarded as a point source anymore because of the multipath propagation. A distributed source model is more suitable for the realistic scenarios. In this paper, an approach of direction-of-arrival (DOA) estimation is proposed for coherently distributed (CD) sources consisting of circular and noncircular signals in a massive or large-scale multiple-input multiple-output system. The noncircular characteristic can improve the performance of DOA estimation. However, most algorithms are not suitable for DOA estimation where circular and noncircular signals coexist. Based on the analysis of constraint conditions satisfied by the steering vector of mixed signals, a multiple signal classification (MUSIC) like approach is proposed for the DOA estimation of CD sources consisting of circular and noncircular signals. On the conditions of low signal-to-noise ratio, small snapshot numbers, and large source numbers, the pseudopeaking may appear. This phenomenon has been analyzed, and a modified MUSIC-like approach is proposed. Simulation results demonstrate that both two proposed algorithms can estimate more sources than the number of sensors. The estimation performances of the two proposed algorithms outperform the traditional MUSIC algorithm.