Efficient User Association and Wireless Scheduling with Shorter Time-Scale Rate Adaptation

2026-09-08

AI Summary

研究通过结合MaxWeight算法和UCB估计，解决了用户关联、调度与速率自适应跨时间尺度联合设计问题，以最大化网络吞吐量并确保用户间公平性。

Abstract

Rate adaptation is a crucial mechanism in IEEE 802.11 networks and next-generation cellular systems. Since the time scale for rate adaptation is typically much shorter than that for user association and scheduling, we investigate a joint design of wireless user association and scheduling and rate adaptation across different time scales to maximize cumulative network throughput while ensuring desired fairness among users. We develop a MaxWeight-type user association and scheduling algorithm that integrates virtual queues -- tracking each user's scheduling debt to maintain fairness -- and Upper Confidence Bound (UCB) estimates in its weight measure. Each selected user then employs the UCB algorithm for rate adaptation on a short time scale. Our theoretical findings reveal that the proposed algorithm achieves cumulative regret that grows with the square root of the time horizon up to a logarithmic factor and results in zero cumulative fairness violation after a certain number of time frames. Furthermore, since the MaxWeight-type algorithm involves evaluating all the feasible schedules that can be exponential to the number of users due to the interference constraints, leading to high computational complexity, we introduce a low-complexity alternative utilizing the so-called pick-and-compare (PC) approach. We demonstrate the effectiveness of both algorithms through simulations based on real-world data traces.

Problem

• Rate Adaptation
• User Association
• Scheduling
• Network Throughput
• Fairness

Innovation

• Rate Adaptation
• Virtual Queues
• Upper Confidence Bound (UCB)
• MaxWeight Algorithm
• Pick-and-Compare Approach