Low-Complexity Beam Selection via Beam Range Biasing for Beamspace MIMO Systems

Abstract

This letter proposes a computationally efficient beam selection (BS) technique that leverages beam range biasing (BRB) to improve the operational efficiency of beamspace multiple-input multiple-output (B-MIMO) systems. Conventional maximum magnitude BS (MM-BS) offers low complexity for B-MIMO; however, it leads to degradation in the system performance due to multi-user interference and inefficient radio frequency (RF) chain utilization. The proposed BRB technique adaptively penalizes the beams assigned to multiple users and promotes underutilized ones to mitigate interference. A two-stage user classification assigns beams to non-interfering users (NIU)s first, reducing the candidate set for others. Simulation results verify that the proposed algorithm perceptibly lowers computational overhead while delivering a sum-rate performance comparable to that of established benchmarks.