Low Complexity Channel Estimation for Hybrid Beamforming Systems

This paper considers the problem of channel estimation in hybrid beamforming systems at the user equipment (UE). After the beam sweeping process, UE estimates the channel such that the best beamforming vector can be derived accordingly to improve analog beamforming gain. To exploit the angular sparsity of millimeter-wave (mmWave) channels, a compressed sensing (CS) based channel estimation algorithm, termed as closed form simultaneous orthogonal matching pursuit (SOMP), is proposed. The proposed algorithm works for a class of beamforming codebooks and scenarios with very small number of beam sweeping symbols, with reduced complexity compared with the existing SOMP algorithm [1]. Simulation results show that the proposed algorithm achieves similar performance as that of the SOMP algorithm, and has advantages over the non-CS based channel estimation algorithm.