Optimal Energy-Efficient Downlink Transmission Scheduling for Real-Time Wireless Networks

TL;DR

This paper develops an efficient method for optimal downlink transmission scheduling in real-time wireless networks, reducing energy consumption by decomposing the problem and enabling faster solutions than existing algorithms.

Contribution

It introduces a novel approach to decomposing the optimal sample path for energy-efficient scheduling, extending previous work with improved computational efficiency.

Findings

The proposed algorithm is significantly faster than the MoveRight algorithm.

Simulation results demonstrate effective energy savings in real-time wireless scenarios.

The method supports online scheduling with uncertain future task information.

Abstract

It has been shown that using appropriate channel coding schemes in wireless environments, transmission energy can be significantly reduced by controlling the packet transmission rate. This paper seeks optimal solutions for downlink transmission control problems, motivated by this observation and by the need to minimize energy consumption in real-time wireless networks. Our problem formulation deals with a more general setting than the paper authored by Gamal et. al., in which the MoveRight algorithm is proposed. The MoveRight algorithm is an iterative algorithm that converges to the optimal solution. We show that even under the more general setting, the optimal solution can be efficiently obtained through an approach decomposing the optimal sample path through certain "critical tasks" which in turn can be efficiently identified. We include simulation results showing that our algorithm is significantly faster than the MoveRight algorithm. We also discuss how to utilize our results and receding horizon control to perform on-line transmission scheduling where future task information is unknown.