Hierarchical multi‐beam training with the presence of the sub‐connected hybrid beamforming architecture

Abstract

AbstractMillimeter‐wave techniques have been developed significantly due to their benefits of higher data rate compared with the lower band and more extensive coverage compared to the higher frequency. However, because of the equipment of a large‐scale antenna array, further low‐complexity channel estimation and precoding algorithms in the hybrid beamforming structured wireless system must be researched for real‐world implementation. This study serves that aim, particularly on multi‐beam training, with the output of this work can be regarded as baseband equivalent channel estimation. First, we present a novel ternary‐tree‐based fully‐activated hierarchical codebook based on the sub‐array division technique. The proposed hierarchical codebook surpasses its conventional binary‐tree‐based counterpart designed by using antenna deactivation in charge of the training overhead and synthesis performance of the hierarchical search. Following that, inspired by multi‐beam linear search, we develop two hierarchical linear search methods according to our proposed hierarchical codebook. Finally, simulation results show that they outperform linear search schemes regarding training complexity and the effective achievable rate.