Distributed dynamic resource allocation for ofdmabased cognitive small cell networks using a regret-matching game approach

Wei Sheng Lai*, Tsung Hui Chang, Ta-Sung Lee

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations

Abstract

Game theoretical approaches have been used to develop distributed resource allocation technologies for cognitive heterogeneous networks. In this chapter, we present a novel distributed resource allocation strategy for cognitive small cell networks based on orthogonal frequency-division multiple access. In particular, we consider a heterogeneous network consisting of macrocell networks overlaid with cognitive small cells that opportunistically access the available spectrum. We focus on a regret-matching game approach, aiming at maximizing the total throughput of the small cell network subject to cross-tier interference and quality of service (QoS) constraints. The regret-matching game approach exploits a regret procedure to learn the optimal resource allocation strategy from the regrets of the actions of cognitive users. Furthermore, the regret-matching game approach is extended to the joint resource allocation and user admission control problem. Numerical results are presented to demonstrate the effectiveness of the proposed regre-matching approaches.

Original languageEnglish
Title of host publicationGame Theory Framework Applied to Wireless Communication Networks
PublisherIGI Global
Pages230-253
Number of pages24
ISBN (Electronic)9781466686434
ISBN (Print)1466686421, 9781466686427
DOIs
StatePublished - 26 Aug 2015

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    Lai, W. S., Chang, T. H., & Lee, T-S. (2015). Distributed dynamic resource allocation for ofdmabased cognitive small cell networks using a regret-matching game approach. In Game Theory Framework Applied to Wireless Communication Networks (pp. 230-253). IGI Global. https://doi.org/10.4018/978-1-4666-8642-7.ch009