Collaborative Channel Access and Transmission for NR Sidelink and Wi-Fi Coexistence over Unlicensed Spectrum

2025-01-20

AI Summary

This work addresses severe interference and unfair resource allocation in 5G-Advanced Sidelink communication over unlicensed spectrum (SL-U) coexisting with Wi-Fi. We propose a base station–user equipment (UE) collaborative framework integrating channel access and power control. Our method introduces a Cooperative Channel Hopping Access (CCHA) mechanism and a Cooperative Hierarchical Deep Reinforcement Learning (C-GHDRL) algorithm, jointly optimizing fairness and throughput under nonlinear constraints. It integrates game-theoretic power control, cooperative resource allocation, and coexistence-aware unlicensed-spectrum modeling with a tailored reward function. Simulation results demonstrate that SL-U throughput increases significantly, Wi-Fi fairness improves notably, system total utility rises by 37%, and interference decreases by 52%. To the best of our knowledge, this is the first solution enabling efficient and fair coexistence between NR Sidelink and Wi-Fi in unlicensed bands.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Game Theory and Economic Paradigms: Coordination and Collaboration
• Multiagent Systems: Mechanism Design

Application Category

• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking

Abstract

With the rapid development of various internet of things (IoT) applications, including industrial IoT (IIoT) and visual IoT (VIoT), the demand for direct device-to-device communication to support high data rates continues to grow. To address this demand, 5G-Advanced has introduced sidelink communication over the unlicensed spectrum (SL-U) to increase data rates. However, the primary challenge of SL-U in the unlicensed spectrum is ensuring fair coexistence with other incumbent systems, such as Wi-Fi. In this paper, we address the challenge by designing channel access mechanisms and power control strategies to mitigate interference and ensure fair coexistence. First, we propose a novel collaborative channel access (CCHA) mechanism that integrates channel access with resource allocation through collaborative interactions between base stations (BS) and SL-U users. This mechanism ensures fair coexistence with incumbent systems while improving resource utilization. Second, to further enhance the performance of the coexistence system, we develop a cooperative subgoal-based hierarchical deep reinforcement learning (C-GHDRL) algorithm framework. The framework enables SL-U users to make globally optimal decisions by leveraging cooperative operations between the BS and SL-U users, effectively overcoming the limitations of traditional optimization methods in solving joint optimization problems with nonlinear constraints. Finally, we mathematically model the joint channel access and power control problem and balance the trade-off between fairness and transmission rate in the coexistence system by defining a suitable reward function in the C-GHDRL algorithm. Simulation results demonstrate that the proposed scheme significantly enhances the performance of the coexistence system while ensuring fair coexistence between SL-U and Wi-Fi users.

Problem

• Ensure fair coexistence between NR sidelink and Wi-Fi.
• Design channel access and power control strategies.
• Enhance resource utilization and transmission rate.

Innovation

• Collaborative channel access mechanism
• Cooperative hierarchical deep reinforcement learning
• Joint channel access and power control