Network selection in cognitive heterogeneous networks using stochastic learning

Li Chuan Tseng, Feng-Tsun Chien, Daqiang Zhang, Ronald Y. Chang, Wei Ho Chung, Ching-Yao Huang

研究成果: Article同行評審

32 引文 斯高帕斯(Scopus)

摘要

Coexistence of multiple radio access technologies (RATs) is a promising paradigm to improve spectral efficiency. This letter presents a game-theoretic network selection scheme in a cognitive heterogeneous networking environment with time-varying channel availability. We formulate the network selection problem as a noncooperative game with secondary users (SUs) as the players, and show that the game is an ordinal potential game (OPG). A decentralized, stochastic learning-based algorithm is proposed where each SU's strategy progressively evolves toward the Nash equilibrium (NE) based on its own action-reward history, without the need to know actions in other SUs. The convergence properties of the proposed algorithm toward an NE point are theoretically and numerically verified. The proposed algorithm demonstrates good throughput and fairness performances in various network scenarios.

原文English
文章編號6646498
頁(從 - 到)2304-2307
頁數4
期刊IEEE Communications Letters
17
發行號12
DOIs
出版狀態Published - 1 12月 2013

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