User Policy Optimization for Ultra-Reliable Low-Latency Communications
| Title: |
User Policy Optimization for Ultra-Reliable Low-Latency Communications |
| DNr: |
SNIC 2022/22-1218 |
| Project Type: |
SNIC Small Compute |
| Principal Investigator: |
Jianan Bai <jianan.bai@liu.se> |
| Affiliation: |
Linköpings universitet |
| Duration: |
2023-01-01 – 2024-01-01 |
| Classification: |
20203 |
| Keywords: |
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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.