Hierarchical Codebook-Based Multiuser Beam Training for Millimeter Wave Massive MIMO

Abstract

In this paper, multiuser beam training based on hierarchical codebook for\nmillimeter wave massive multi-input multi-output is investigated, where the\nbase station (BS) simultaneously performs beam training with multiple user\nequipments (UEs). For the UEs, an alternative minimization method with a\nclosed-form expression (AMCF) is proposed to design the hierarchical codebook\nunder the constant modulus constraint. To speed up the convergence of the AMCF,\nan initialization method based on Zadoff-Chu sequence is proposed. For the BS,\na simultaneous multiuser beam training scheme based on an adaptively designed\nhierarchical codebook is proposed, where the codewords in the current layer of\nthe codebook are designed according to the beam training results of the\nprevious layer. The codewords at the BS are designed with multiple mainlobes,\neach covering a spatial region for one or more UEs. Simulation results verify\nthe effectiveness of the proposed hierarchical codebook design schemes and show\nthat the proposed multiuser beam training scheme can approach the performance\nof the beam sweeping but with significantly reduced beam training overhead.\n