Game Based Self-Organizing Scheme for Femtocell Networks

• Published in: Game Theory for Networks pp. 57 - 75
• Main Authors: Han, Kwanghun, Choi, Seunghyun, Kang, Du Ho, Choi, Sunghyun
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2012
• Series: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
• Subjects: Candidate solution; Cochannel interference; Convergence properties; Dynamic frequency selection; Femtocell; Femtocells; Frequency Channel; Frequency channels; Game theory; Indoor environment; Interference environments; Macro cells; Medium Access Control; Operating frequency; Optimality; Potential Game; Potential games; Queueing networks; Self-organizing scheme; Tabu List; Tabu Search; Transmit power; Transmit power control; Wireless coverage
• ISBN: 9783642303722; 3642303722
• ISSN: 1867-8211; 1867-822X
• DOI: 10.1007/978-3-642-30373-9_5

A femto base station (BS) is an emerging candidate solution to guarantee wireless coverage and enhance capacity in indoor environments. Ideally, femto BSs should be designed to be installed by customers without their manual configuration. Hence, a femtocell network should be automatically organized by configuring the operating frequency channel and transmit power level of the femto BSs adaptively according to the interference environment. However, in order to enhance the capacity of femtocell users, the femto BSs in the network should be carefully configured since they can cause severe co-channel interference to the existing macrocell networks operating in the same frequency channel. In this work, we propose an automatic self-organizing scheme for a femtocell network by jointly considering transmit power control and dynamic frequency selection, which tries to maximize the mean sum downlink achievable rate of the femtocell users and to guarantee the performance of the macrocell users by limiting the co-channel interference from the femtocells. The proposed scheme is based on a potential game which guarantees a convergence property, and we enhance the scheme with a Tabu search, which attempts to achieve the optimality.