Efficient Beam Training and Sparse Channel Estimation for Millimeter Wave Communications Under Mobility

In this paper, we propose an efficient beam training technique for millimeter-wave (mmWave) communications. Beam training should be performed frequently when some mobile users are under high mobility to ensure the accurate acquisition of the channel state information. To reduce the resource overhead caused by frequent beam training, we introduce a dedicated beam training strategy which sends the training beams separately to a specific high mobility user (called a target user) without changing the periodicity of the conventional beam training. The dedicated beam training requires a small amount of resources because the training beams can be optimized for the target user. To satisfy the performance requirement with a low training overhead, we propose the optimal training beam selection strategy which finds the best beamforming vectors yielding the lowest channel estimation error based on the target user's probabilistic channel information. This dedicated beam training is combined with the greedy channel estimation algorithm that accounts for sparse characteristics and temporal dynamics of the target user's channel. Our numerical evaluation demonstrates that the proposed scheme can maintain good channel estimation performance with significantly less training overhead compared to the conventional beam training protocols.

I. Introduction

In recent years, wireless communications using the millimeter-wave (mmWave) frequency band have received a great deal of attention as a means to meet the ever-increasing throughput demand of next generation communication systems [1]–[3]. A vast amount of bandwidth has not yet been explored by the current communication systems; thus, mmWave communications are a promising solution to meet the required data throughput. The significant path loss of mmWave channels is a major obstacle that makes seamless communication over the mmWave band difficult [4]–[6]. Compared to the conventional communication systems that use microwave radio waves, the mmWave band experiences high atmospheric attenuation when a transmit signal is absorbed by gas and humidity. Additionally, a significant path loss occurs when the signal is blocked by obstacles such as buildings, foliage, and the user’s body [2]. Beamforming, where two communication entities transmit and receive the signals with appropriately adjusted phase and amplitude using an array of antennas, is the key enabler in overcoming this drawback [3], [7]–[9]. By boosting the signal energy transmitted and received in the desired directions, the beamforming techniques can compensate for the large path loss of mmWave channels.