Joint Channel Probing and Proportional Fair Scheduling in Wireless Networks

TL;DR

This paper introduces a joint channel probing and scheduling scheme for wireless networks that balances resource use and fairness, utilizing optimal stopping and learning algorithms to improve performance.

Contribution

It develops a novel joint probing and scheduling method that accounts for limited channel information and unknown statistics, enhancing efficiency and fairness.

Findings

Significant performance gains over existing schemes.

Effective joint learning, probing, and scheduling approach.

Improved resource utilization and user fairness.

Abstract

The design of a scheduling scheme is crucial for the efficiency and user-fairness of wireless networks. Assuming that the quality of all user channels is available to a central controller, a simple scheme which maximizes the utility function defined as the sum logarithm throughput of all users has been shown to guarantee proportional fairness. However, to acquire the channel quality information may consume substantial amount of resources. In this work, it is assumed that probing the quality of each user's channel takes a fraction of the coherence time, so that the amount of time for data transmission is reduced. The multiuser diversity gain does not always increase as the number of users increases. In case the statistics of the channel quality is available to the controller, the problem of sequential channel probing for user scheduling is formulated as an optimal stopping time problem. A joint channel probing and proportional fair scheduling scheme is developed. This scheme is extended to the case where the channel statistics are not available to the controller, in which case a joint learning, probing and scheduling scheme is designed by studying a generalized bandit problem. Numerical results demonstrate that the proposed scheduling schemes can provide significant gain over existing schemes.