Green Broadcast Transmission in Cellular Networks: A Game Theoretic Approach

TL;DR

This paper introduces a game-theoretic distributed algorithm for minimizing power consumption in multi-cell broadcast networks, demonstrating its effectiveness through extensive simulations and comparisons with other approaches.

Contribution

It presents a novel group formation game-based distributed algorithm for mobile assignment, addressing the NP-hard problem with practical heuristics and simulations.

Findings

The hedonic decision algorithm performs well compared to centralized solutions.

Distributed algorithms achieve near-optimal power savings.

Simulations validate the effectiveness of the proposed methods.

Abstract

This paper addresses the mobile assignment problem in a multi-cell broadcast transmission seeking minimal total power consumption by considering both transmission and operational powers. While the large scale nature of the problem entails to find distributed solutions, game theory appears to be a natural tool. We propose a novel distributed algorithm based on group formation games, called \textit{the hedonic decision algorithm}. This formalism is constructive: a new class of group formation games is introduced where the utility of players within a group is separable and symmetric being a generalized version of parity-affiliation games. The proposed hedonic decision algorithm is also suitable for any set-covering problem. To evaluate the performance of our algorithm, we propose other approaches to which our algorithm is compared. We first develop a centralized recursive algorithm called \textit{the hold minimum} being able to find the optimal assignments. However, because of the NP-hard complexity of the mobile assignment problem, we propose a centralized polynomial-time heuristic algorithm called \textit{the column control} producing near-optimal solutions when the operational power costs of base stations are taken into account. Starting from this efficient centralized approach, a \textit{distributed column control algorithm} is also proposed and compared to \textit{the hedonic decision algorithm}. We also implement the nearest base station algorithm which is very simple and intuitive and efficiently manage fast-moving users served by macro BSs. Extensive simulation results are provided and highlight the relative performance of these algorithms. The simulated scenarios are done according to Poisson point processes for both mobiles and base stations.