Pre-Equalization Aided Grant-Free Massive Access in Massive MIMO System
Yueqing Wang, Yikun Mei, Zhen Gao, Ziwei Wan, Boyu Ning, De Mi, and, Sami Muhaidat

TL;DR
This paper introduces a pre-equalization aided grant-free massive access scheme for mMIMO systems that reduces pilot overhead and access latency by using an iterative detection algorithm with beacon-assisted channel estimation.
Contribution
It proposes a novel pre-equalization scheme with an iterative detection algorithm that enhances activity detection and data decoding in grant-free massive MIMO systems.
Findings
Outperforms existing grant-free NOMA schemes in simulation.
Reduces pilot overhead and access latency.
Improves detection accuracy with iterative algorithm.
Abstract
The spatial diversity and multiplexing advantages of massive multi-input-multi-output (mMIMO) can significantly improve the capacity of massive non-orthogonal multiple access (NOMA) in machine type communications. However, state-of-the-art grant-free massive NOMA schemes for mMIMO systems require accurate estimation of random access channels to perform activity detection and the following coherent data demodulation, which suffers from excessive pilot overhead and access latency. To address this, we propose a pre-equalization aided grant-free massive access scheme for mMIMO systems, where an iterative detection scheme is conceived. Specifically, the base station (BS) firstly activates one of its antennas (i.e., beacon antenna) to broadcast a beacon signal, which facilitates the user equipment (UEs) to perform downlink channel estimation and pre-equalize the uplink random access signal…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Advanced Wireless Communication Technologies · Wireless Communication Networks Research
MethodsBalanced Selection
