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

机译:使用Stackelberg博弈的小型蜂窝网络中基于能效价格的功率分配

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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.
机译:小型蜂窝网络在增加蜂窝网络的覆盖范围和容量方面起着举足轻重的作用。然而,用于最佳控制跨层干扰和能源效率问题的方法数量有限,是这些网络面临的最大挑战。在本文中,提出了一种在两层小型蜂窝网络中进行节能通信的新颖方法。我们建议对干扰进行定价,并控制发射功率以减轻跨层干扰并提高能效。为了解决这个问题,宏小区基站(MBS)和毫微微小区基站(FBS)分别充当Stackelberg游戏的领导者和追随者。 MBS使用接收到的干扰量的定价来保护自己免受FBS造成的干扰。 FBS的目标是通过在最大允许的发射功率约束下使用功率控制来最大程度地提高其能量效率,并减少应向MBS支付的价格。最大化能量效率是非线性分数规划,可以将其转换为减法形式,因此可以通过使用迭代功率分配算法来解决。仿真结果研究了该算法的有效性。

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