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arXiv · 2410.17068

Delay-Constrained Grant-Free Random Access in MIMO Systems: Distributed Pilot Allocation and Power Control

Jianan Bai·Zheng Chen·Erik. G. Larsson
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Abstract

We study a delay-constrained grant-free random access system with a multi-antenna base station. The users randomly generate data packets with expiration deadlines, which are then transmitted from data queues on a first-in first-out basis. To deliver a packet, a user needs to succeed in both random access phase (sending a pilot without collision) and data transmission phase (achieving a required data rate with imperfect channel information) before the packet expires. We develop a distributed, cross-layer policy that allows the users to dynamically and independently choose their pilots and transmit powers to achieve a high effective sum throughput with fairness consideration. Our policy design involves three key components: 1) a proxy of the instantaneous data rate that depends only on macroscopic environment variables and transmission decisions, considering pilot collisions and imperfect channel estimation; 2) a quantitative, instantaneous measure of fairness within each communication round; and 3) a deep learning-based, multi-agent control framework with centralized training and distributed execution. The proposed framework benefits from an accurate, differentiable objective function for training, thereby achieving a higher sample efficiency compared with a conventional application of model-free, multi-agent reinforcement learning algorithms. The performance of the proposed approach is verified by simulations under highly dynamic and heterogeneous scenarios.

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Jianan Bai, Zheng Chen, Erik. G. Larsson. 2024-10-22. Delay-Constrained Grant-Free Random Access in MIMO Systems: Distributed Pilot Allocation and Power Control. https://arxiv.org/abs/2410.17068

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