Energy Efficient Price Based Power Allocation in a Small Cell Network by Using a Stackelberg Game

M. Lashgari, B. Maham, H. Kebriaei
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引用次数: 6

Abstract

Small cell networks are playing a pivotal role in increasing coverage and capacity of cellular networks which are extensively in last few years. However, the limited number of methods for optimal control of cross-layer interference and energy efficiency issues are paramount challenges of these networks. In this paper, a novel approach for an energy efficient communication in a two-tier small cell network is proposed. We have suggested pricing on interference and controlling transmit power to mitigate cross-layer interference and improve energy efficiency. In order to formulate the problem, the macrocell base station (MBS) and femtocell base stations (FBSs) act as leader and followers of a Stackelberg game, respectively. The MBS uses the pricing on the amount of the received interference to protect itself against the interference caused by FBSs. The FBSs goal is to maximize their energy efficiency and minimize the amount of price that should be paid to MBS by using a power control under the maximum allowable transmit power constraint. Maximizing energy efficiency is a non-linear fractional programming which is transformed to a subtractive form, and thus, it can be solved by using the iterative power allocation algorithm. The efficiency of the proposed algorithm is investigated through simulation results.
基于Stackelberg博弈的小蜂窝网络节能电价分配
近年来,小型蜂窝网络在增加蜂窝网络的覆盖范围和容量方面发挥着举足轻重的作用。然而,跨层干扰的最优控制方法有限以及能效问题是这些网络面临的最大挑战。本文提出了一种在两层小蜂窝网络中实现高效节能通信的新方法。我们建议根据干扰定价,控制发射功率,以减轻跨层干扰,提高能源效率。为了表述该问题,宏蜂窝基站(MBS)和飞蜂窝基站(FBSs)分别作为Stackelberg博弈的领导者和追随者。MBS根据接收到的干扰量进行定价,以保护自己免受fbs造成的干扰。fbs的目标是在最大允许发射功率约束下使用功率控制,使其能源效率最大化,并将应支付给MBS的价格最小化。能源效率最大化问题是一个转化为减法形式的非线性分式规划问题,可采用迭代功率分配算法求解。仿真结果验证了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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