Fingerprint-aided mmWave Beam Selection for Enhanced Beamspace Massive MIMO Communication

Abstract

Millimeter-wave communications are suitable for application to massive multiple-input multiple-output systems in order to satisfy the ever-growing data traffic demands of the next-generation wireless communication. However, their practical deployment is hindered by the high cost of complex hardware, such as radio frequency (RF) chains. To this end, operation in the beamspace domain, through beam selection, is a viable solution. Generally, the conventional beam selection schemes focus on the feedback and exhaustive search techniques. In addition, since the same beam in the beamspace may be assigned to a different user, conventional beam selection schemes suffer serious multi-user interference. In addition, some RF chains may be wasted, since they do not contribute to the sum-rate performance. Thus, a fingerprint-based beam selection scheme is proposed to solve these problems. The proposed scheme conducts offline group-based fingerprint database construction and online beam selection to mitigate multi-user interference. In the offline phase, the contributing users with the same best beam are grouped. After grouping, a fingerprint database is created for each group. In the online phase, beam selection is performed for purposes of interference mitigation using the information contained in the group-based fingerprint database. The simulation results confirm that the proposed beam selection scheme can achieve a signal-to-interference-plus-noise ratio and sum-rate performance which is close to those of a fully digital system, and having much higher energy efficiency.