More about Base Station Location Games

TL;DR

This paper analyzes the strategic placement of base stations in a high-density mobile area, exploring equilibrium existence, uniqueness, and dynamic adjustment methods like reinforcement learning.

Contribution

It provides a comprehensive Nash equilibrium analysis for base station placement and introduces dynamic adjustment algorithms with numerical illustrations.

Findings

Nash equilibrium existence and uniqueness established.

Dynamic adjustment methods demonstrated through simulations.

Insights into the efficiency of different placement strategies.

Abstract

This paper addresses the problem of locating base stations in a certain area which is highly populated by mobile stations; each mobile station is assumed to select the closest base station. Base stations are modeled by players who choose their best location for maximizing their uplink throughput. The approach of this paper is to make some simplifying assumptions in order to get interpretable analytical results and insights to the problem under study. Specifically, a relatively complete Nash equilibrium (NE) analysis is conducted (existence, uniqueness, determination, and efficiency). Then, assuming that the base station location can be adjusted dynamically, the best-response dynamics and reinforcement learning algorithm are applied, discussed, and illustrated through numerical results.