Mobility

Power Entangling and Matching in Cognitive Wireless Mesh Networks by Applying Conjecture Based Multi-Agent QQ-Learning Approach

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Executive Summary

As the scarce spectrum resource is becoming overcrowded, cognitive wireless mesh networks express great flexibility to improve the spectrum utilization by opportunistically accessing the authorized frequency bands. One of the critical challenges for realizing such networks is how to adaptively match transmit powers and allocate frequency resources among Secondary Users (SUs) of the licensed frequency bands whilst maintaining the Quality-of-Service (QoS) requirement of the Primary Users (PUs), even in mutually entangled interference environment. In this paper, the authors discuss the non-cooperative power allocation matching problem in cognitive wireless mesh networks formed by a number of clusters with the consideration of energy efficiency. Due to the secondary users' selfish and spontaneous features, the problem is modeled as a stochastic learning process.

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