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Dense femtocell networks power self‐optimization: an exact potential game approach
Author(s) -
Wang Xidong,
Zheng Wei,
Lu Zhaoming,
Wen Xiangming,
Li Wei
Publication year - 2014
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.2788
Subject(s) - femtocell , computer science , nash equilibrium , mathematical optimization , telecommunications link , transmitter power output , optimization problem , power control , game theory , computer network , throughput , cellular network , power (physics) , wireless , telecommunications , transmitter , base station , algorithm , mathematics , mathematical economics , channel (broadcasting) , physics , quantum mechanics
Summary Femtocell is regarded as a promising technology to enhance indoor coverage and improve network capacity. However, highly dense and self‐organized femtocells in urban environment will result in serious inter‐femtocell interference. To solve this problem, this paper proposes a distributed power self‐optimization scheme for the downlink operation of dense femtocell networks. First, a novel convex pricing mechanism is presented to price the transmit power of femtocells and construct the utility function of femtocells. Then, a noncooperative game framework for power self‐optimization of femtocells in dense femtocell networks is established on the basis of the exact potential game theory, which is demonstrated to converge to a pure and unique Nash equilibrium. Finally, combined with firefly algorithm, an effective power self‐optimization algorithm with guaranteed convergence is proposed to achieve the Nash equilibrium of the proposed game. With practical LTE parameters and a 3GPP dual‐strip femtocell model, simulation results show that the proposed game with convex pricing mechanism increases the femtocell network throughput by 7% and reduces the average transmit power of femtocells by 50% in dense femtocell networks, with respect to the compared schemes. Copyright © 2014 John Wiley & Sons, Ltd.