NDLI: Normalized nash equilibrium for power allocation in femto base stations in heterogeneous network

Content Provider	IEEE Xplore Digital Library
Author	Ghosh, A. Cottatellucci, L. Altman, E.
Copyright Year	2015
Description	Author affiliation: Sch. of Electr. & Syst. Eng., Univ. of Pennsylvania, Philadelphia, PA, USA (Ghosh, A.) \|\| INRIA, Sophia Antipolis, France (Altman, E.) \|\| Mobile Commun. Dept., Eurecom, Sophia Antipolis, France (Cottatellucci, L.)
Abstract	We consider heterogeneous networks with multiple femtocells and macrocells. Femto-base stations (femto-BS) are constrained to allocate transmitting powers such that the total interference at each macro-user terminal (macro-UT) is below a given threshold. We formulate a power allocation problem as a concave game with femto-BSs as players and multiple macro-UTs enforcing coupled constraints. Equilibrium selection is based on the concept of normalized Nash equilibrium (NNE). When the interference at a femto-user terminal (femto-UT) from adjacent femto-BSs is negligible, for any strictly concave nondecreasing utility the NNE is unique and the NNE is the solution of a concave potential game. We also propose a distributed algorithm which converges to the unique NNE. When the interference is not negligible, an NNE may not be unique and the computation of NNE has exponential complexity. We introduce the concept of weakly normalized Nash equilibrium (WNNE) which keeps the most of NNEs' interesting properties but, in contrast to the latter, the WNNE can be determined with low complexity. We show the usefulness of the WNNE concept for the relevant case of Shannon capacity as femto-BS's utility.
Starting Page	411
Ending Page	418
File Size	344644
Page Count	8
File Format	PDF
ISBN	9783901882746
DOI	10.1109/WIOPT.2015.7151100
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-25
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	IFIP
Subject Keyword	Games Artificial neural networks Interference Hafnium Complexity theory Resource management Distributed algorithms
Content Type	Text
Resource Type	Article

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