Green transmit power assignment for cognitive radio networks by applying multi-agent Q-learning approach

Xianfu Chen, Zhifeng Zhao, Honggang Zhang

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

11 Citations (Scopus)


As the scarce spectrum resource is becoming overcrowded, cognitive wireless mesh networks (CogMesh) indicate great flexibility to improve the spectrum utilization by opportunistically accessing the authorized frequency bands. In this paper, we consider non-cooperative green power assignment in CogMesh with the consideration of energy efficiency. The problem is modeled as a stochastic learning process. We extend the single-agent Q-learning to a multi-user context, and propose a conjecture based multi-agent Q-learning scheme to obtain the optimal strategies with private and incomplete information. A learning secondary user performs Q-function updates based on the conjecture about other secondary users' behaviors. Simulations are used to verify the performance of our algorithm and demonstrate its effectiveness of improving the energy efficiency.

Original languageEnglish
Title of host publicationEuropean Microwave Week 2010, EuMW2010
Subtitle of host publicationConnecting the World, Conference Proceedings - European Wireless Technology Conference, EuWiT 2010
PublisherIEEE Institute of Electrical and Electronic Engineers
ISBN (Electronic)978-2-87487-018-7
ISBN (Print)978-1-4244-7233-8
Publication statusPublished - 15 Dec 2010
MoE publication typeA4 Article in a conference publication
Event13th European Microwave Week 2010, EuMW2010: Connecting the World - 3rd European Wireless Technology Conference - Paris, France
Duration: 27 Sept 201028 Sept 2010


Conference13th European Microwave Week 2010, EuMW2010


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