Title:	User Policy Optimization for Ultra-Reliable Low-Latency Communications
DNr:	NAISS 2023/22-1309
Project Type:	NAISS Small Compute
Principal Investigator:	Jianan Bai <jianan.bai@liu.se>
Affiliation:	Linköpings universitet
Duration:	2024-01-01 – 2025-01-01
Classification:	20203
Keywords:

Abstract

This project investigates decentralized user policy for ultra-reliable low-latency communications (URLLC). The main focus is grant-free multiple access (GFMA), during which the users start data transmission without a grant. Since users are uncoordinated during GFMA, the network performance can be severely degraded due to pilot collision and interference. Our interest is to explore machine learning algorithms, especially multi-agent reinforcement learning, to develop decentralized policy, such that the users can make access decisions cooperatively by only using local information.