Beamspace Multi-ACB for mMTC in Massive MIMO System

Abstract

In the 5th generation (5G) and beyond, massive machine-type communication (mMTC) has been one of the most important technologies to support the Internet of Things (IoT). However, the random access (RA) throughput is limited by the scarce RA resources (e.g., preambles). Massive multiple-input-multiple-output (MIMO) can provide spatial degrees of freedom, which can be utilized for RA resource extension. In this paper, we propose a novel beamspace RA scheme, which achieves fully spatial preamble reuse. Specifically, the cell is divided into several beam zones via directional beams, and preambles are fully reused per beam. To mitigate preamble collision and side-lobe interference, we combine the access class barring (ACB) method with preamble reuse, which efficiently improves RA throughput. Meanwhile, an efficient algorithm is proposed to determine these multiple ACB factors. The proposed scheme is applicable to both grant-based and grant-free RA procedures. Through detailed analysis and simulation results, the proposed scheme can significantly improve the RA performance in bursty traffic model.