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Wireless Networks
Erschienen in: Wireless Networks 4/2015

01.05.2015

Distributed channel assignment for network MIMO: game-theoretic formulation and stochastic learning

verfasst von: Li-Chuan Tseng, Feng-Tsun Chien, Ronald Y. Chang, Wei-Ho Chung, ChingYao Huang, Abdelwaheb Marzouki

Erschienen in: Wireless Networks | Ausgabe 4/2015

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Abstract

The cooperative frequency reuse among base stations (BSs) can improve the system spectral efficiency by reducing the intercell interference through channel assignment and precoding. This paper presents a game-theoretic study of channel assignment for realizing network multiple-input multiple-output (MIMO) operation under time-varying wireless channel. We propose a new joint precoding scheme that carries enhanced interference mitigation and capacity improvement abilities for network MIMO systems. We formulate the channel assignment problem from a game-theoretic perspective with BSs as the players, and show that our game is an exact potential game given the proposed utility function. A distributed, stochastic learning-based algorithm is proposed where each BS progressively moves toward the Nash equilibrium (NE) strategy based on its own action-reward history only. The convergence properties of the proposed learning algorithm toward an NE point are theoretically and numerically verified for different network topologies. The proposed learning algorithm also demonstrates an improved capacity and fairness performance as compared to other schemes through extensive link-level simulations.
Vorheriger Artikel High-throughput transmission-quality-aware broadcast routing in cognitive radio networks
Nächster Artikel Interference alignment with delayed channel state information and dynamic AR-model channel prediction in wireless networks

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Fußnoten
1
Note that with the approximated utility function the existence of a pure strategy NE is no longer guaranteed theoretically. However, as will be shown in Sect. 6, convergence to NE is observed numerically.
 
2
Note that Fig. 5 simulates a different topology and shows a slightly different comparison result. However, both Figs. 5 and 9a demonstrate the efficacy of the proposed distributed learning method as compared to a centralized scheme.
 
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Metadaten
Titel
Distributed channel assignment for network MIMO: game-theoretic formulation and stochastic learning
verfasst von
Li-Chuan Tseng
Feng-Tsun Chien
Ronald Y. Chang
Wei-Ho Chung
ChingYao Huang
Abdelwaheb Marzouki
Publikationsdatum
01.05.2015
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 4/2015
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-014-0844-5

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