A new low complexity DOA estimation algorithm for massive MIMO systems
Xiao Hua Yang, Licheng Liu, Yide Wang · 2016
Massive MIMO systems have attracted lots of attention, and its performance is closely related to the estimation of direction of arrivals (DOA) of incoming sources. The conventional DOA estimation algorithms like MUSIC and ESPRIT are not suitable for massive MIMO systems, due to the complexity brought by the large number of antennas. The DOA estimation algorithm named Propagator Method (PM) has been proved efficient in terms of computational complexity, because it does not require the eigenvalue decomposition (EVD) of the covariance matrix of the received signals. In this paper, a new version of PM is proposed. By partitioning the covariance matrix of the received signals, the data contaminated by the main contribution of noise can be avoided, and the reconstruction of the system model in not needed, so the computational complexity can be decreased significantly. Some numerical simulations are given to prove its efficiency.