Bayesian Tree Search for Beamforming Training in Millimeter Wave Wireless Communication Systems

Abstract

In this paper, we propose novel algorithms of beamforming training for millimeter wave wireless communication systems. Instead of searching the whole codebook organized as a binary tree, we propose using Bayesian tree search algorithms to reduce the average delay of beamforming training. In addition, we design algorithms that derive an optimal threshold for the proposed opportunistic one-threshold tree search algorithm and an optimal pair of thresholds for the proposed opportunistic two-threshold tree search algorithm. Furthermore, we propose using quantization to efficiently calculate the likelihood ratio in the proposed opportunistic tree search algorithms. Our simulation results show that the proposed algorithms could significantly reduce the average delay of beamforming training.