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Access point selection game with mobile users using correlated equilibrium.

¹Division of Electronics & Electrical Engineering, Dongguk University-Seoul, Seoul, Republic of Korea.

|March 19, 2015

Summary

This study introduces a game theory approach for mobile users to select access points (APs) in wireless local area networks (WLANs). The novel regret-based learning algorithm ensures correlated equilibrium (CE) for optimal system throughput.

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Area of Science:

Computer Science
Electrical Engineering
Game Theory

Background:

Access Point (AP) selection is a critical challenge in Wireless Local Area Network (WLAN) systems with multiple APs.
Game theory provides a framework for analyzing multi-player interactions, with correlated equilibrium (CE) offering a more general solution concept than Nash equilibrium for mixed strategy games.

Purpose of the Study:

To formulate the AP selection problem in WLANs with mobile users using a game-theoretic approach.
To introduce a novel regret-based learning scheme to achieve correlated equilibrium (CE) for AP selection.

Main Methods:

A game-theoretic model was developed for the AP selection problem considering mobile users.
A regret-based learning procedure was designed and implemented as a novel scheme.
Convergence analysis was performed to demonstrate the achievement of CE.

Main Results:

The proposed algorithm effectively converges to a correlated equilibrium (CE).
Simulations in a realistic WLAN environment with user mobility validated the algorithm's effectiveness.
The algorithm achieved maximum system throughput as defined by the game-theoretic formulation.

Conclusions:

The regret-based learning scheme provides an effective solution for the AP selection problem in mobile WLAN environments.
The game-theoretic formulation and proposed algorithm successfully achieve correlated equilibrium (CE) and optimize system throughput.
This approach offers a robust method for managing user interactions and improving performance in complex wireless networks.