Analysis and Optimization of Successful Symbol Transmission Rate for Grant-free Massive Access with Massive MIMO

TL;DR

This paper introduces a new performance metric, the successful symbol transmission rate (SSTR), for grant-free massive access in massive MIMO systems, providing analytical expressions and optimization strategies to enhance system performance.

Contribution

It proposes SSTR as a more suitable metric for grant-free massive access and derives closed-form asymptotic expressions for MRC and ZF beamforming, including optimization methods.

Findings

Derived closed-form asymptotic SSTR expressions for MRC and ZF.

Optimized access parameters and pilot length for maximum SSTR.

Validated the effectiveness of the proposed metric and optimization.

Abstract

Grant-free massive access is an important technique for supporting massive machine-type communications (mMTC) for Internet-of-Things (IoT). Two important features in grant-free massive access are low-complexity devices and short-packet data transmission, making the traditional performance metric, achievable rate, unsuitable in this case. In this letter, we investigate grant-free massive access in a massive multiple-input multiple-output (MIMO) system. We consider random access control, and adopt approximate message passing (AMP) for user activity detection and channel estimation in the pilot transmission phase and small phase-shift-keying (PSK) modulation in the data transmission phase. We propose a more reasonable performance metric, namely successful symbol transmission rate (SSTR), for grant-free massive access. We obtain closed-form approximate expressions for the asymptotic SSTR in the cases of maximal ratio combining (MRC) and zero forcing (ZF) beamforming at the base station (BS), respectively. We also maximize the asymptotic SSTR with respect to the access parameter and pilot length.