Automated Dynamic Offset Applied to Cell Association

TL;DR

This paper introduces a hierarchical Bayesian game framework for dynamic offset selection in cell association, enabling operators to optimize network utility while considering user behavior and strategic interactions.

Contribution

It develops a novel Stackelberg game model for dynamic offset configuration, balancing global network performance and user utility with minimal signaling.

Findings

The framework achieves a good trade-off between network performance and signaling.

Operators can optimize global utility by strategic information sharing.

The approach addresses misleading association issues when network and user goals differ.

Abstract

In this paper, we develop a hierarchical Bayesian game framework for automated dynamic offset selection. Users compete to maximize their throughput by picking the best locally serving radio access network (RAN) with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a Stackelberg game, in which the base station is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We study the Price of Anarchy (PoA) of such system, where the PoA is the ratio of the social welfare attained when a network planner chooses policies to maximize social welfare versus the social welfare attained in Nash/Stackeleberg equilibrium when users choose their policies strategically. We show by means of a Stackelberg formulation, how the operator, by sending appropriate information about the state of the channel, can configure a dynamic offset that optimizes its global utility while users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem.