Access Strategy in Super WiFi Network Powered by Solar Energy Harvesting: A POMDP Method

TL;DR

This paper introduces a POMDP-based framework for user access strategy in solar-powered Super Wi-Fi networks, addressing power management and network selection to improve efficiency over traditional methods.

Contribution

It presents a novel POMDP approach for user access decision-making in energy harvesting Super Wi-Fi networks, considering battery states and network selection.

Findings

The proposed POMDP method outperforms traditional CSMA in simulations.

Efficient network access strategies improve performance in EH-powered Super Wi-Fi.

Battery state awareness enhances network selection effectiveness.

Abstract

The recently announced Super Wi-Fi Network proposal in United States is aiming to enable Internet access in a nation-wide area. As traditional cable-connected power supply system becomes impractical or costly for a wide range wireless network, new infrastructure deployment for Super Wi-Fi is required. The fast developing Energy Harvesting (EH) techniques receive global attentions for their potential of solving the above power supply problem. It is a critical issue, from the user's perspective, how to make efficient network selection and access strategies. Unlike traditional wireless networks, the battery charge state and tendency in EH based networks have to be taken into account when making network selection and access, which has not been well investigated. In this paper, we propose a practical and efficient framework for multiple base stations access strategy in an EH powered Super Wi-Fi network. We consider the access strategy from the user's perspective, who exploits downlink transmission opportunities from one base station. To formulate the problem, we used Partially Observable Markov Decision Process (POMDP) to model users' observations on the base stations' battery situation and decisions on the base station selection and access. Simulation results show that our methods are efficacious and significantly outperform the traditional widely used CSMA method.