Optimal wireless rate and power control in the presence of jammers using reinforcement learning

TL;DR

This paper presents a reinforcement learning approach for optimizing wireless rate and power control in the presence of jammers, improving throughput and energy efficiency in 802.11ac networks.

Contribution

It introduces a RL-based method for joint rate and power control with a normalized reward function, adaptable to different network priorities and tested against traditional algorithms.

Findings

RL agents outperform Minstrel in throughput and energy efficiency

The approach is effective in jammed wireless environments

Method is adaptable to various wireless network types

Abstract

Future wireless networks require high throughput and energy efficiency. This paper studies using Reinforcement Learning (RL) to do transmission rate and power control for maximizing a joint reward function consisting of both throughput and energy consumption. We design the system state to include factors that reflect packet queue length, interference from other nodes, quality of the wireless channel, battery status, etc. The reward function is normalized and does not involve unit conversion. It can be used to train three different types of agents: throughput-critical, energy-critical, and throughput and energy balanced. Using the NS-3 network simulation software, we implement and train these agents in an 802.11ac network with the presence of a jammer. We then test the agents with two jamming nodes interfering with the packets received at the receiver. We compare the performance of our RL optimal policies with the popular Minstrel rate adaptation algorithm: our approach can achieve (i) higher throughput when using the throughput-critical reward function; (ii) lower energy consumption when using the energy-critical reward function; and (iii) higher throughput and slightly higher energy when using the throughput and energy balanced reward function. Although our discussion is focused on 802.11ac networks, our method is readily applicable to other types of wireless networks.