# On Maximizing Energy and Data Delivery in Dense Wireless Local Area Networks

## TL;DR

This paper investigates optimal scheduling policies for wireless access points to maximize energy transfer and data delivery in dense WLANs, using a Markov Decision Process model to evaluate different strategies.

## Contribution

It introduces a finite-horizon MDP model to analyze transmission policies for balancing energy transfer and data queue management in dense WLANs.

## Key findings

- Max weight policy outperforms others in queue length reduction.
- Max weight policy delivers the most energy to devices.
- Analysis provides insights into scheduling for energy and data in dense WLANs.

## Abstract

Devices can now be powered wirelessly by Access Points (APs). However, an AP cannot transmit frequently to charge devices as it may starve other nearby APs operating on the same channel. Consequently, there is a need to schedule the transmissions of APs to ensure their data queues remain short whilst charging energy-harvesting devices. We present a finite-horizon Markov Decision Process (MDP) to capture the queue states at APs and also channel conditions to nodes. We then use the MDP to investigate the following transmission policies: max weight, max queue, best channel state and random. Our results show that the max weight policy has the best performance in terms of queue length and delivered energy.