A Three-Level Market-Based Scheme of Spectrum Allocation for Cognitive Ad hoc Networks

Lin Yu-qing; Zhu Qi; Zhu Hong-bo

doi:10.3724/SP.J.1146.2009.00332

Volume 32 Issue 3

Aug. 2010

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2010 > 32(3): 643-648

Lin Yu-qing, Zhu Qi, Zhu Hong-bo. A Three-Level Market-Based Scheme of Spectrum Allocation for Cognitive Ad hoc Networks[J]. Journal of Electronics & Information Technology, 2010, 32(3): 643-648. doi: 10.3724/SP.J.1146.2009.00332

Citation:

Lin Yu-qing, Zhu Qi, Zhu Hong-bo. A Three-Level Market-Based Scheme of Spectrum Allocation for Cognitive Ad hoc Networks[J]. Journal of Electronics & Information Technology, 2010, 32(3): 643-648. doi: 10.3724/SP.J.1146.2009.00332

Citation:

PDF( 334 KB)

A Three-Level Market-Based Scheme of Spectrum Allocation for Cognitive Ad hoc Networks

doi: 10.3724/SP.J.1146.2009.00332

Received Date: 2009-03-13
Rev Recd Date: 2009-09-18
Publish Date: 2010-03-19

Abstract

Abstract

Clustering is the main framework of large scale Ad Hoc networks, and one of its key technologies is spectrum allocation. In this paper, a novel three-level market-based scheme of spectrum allocation is proposed for cognitive clustered Ad Hoc networks. In this scheme, cluster headers buy spectrum from spectrum administrator of primary service according to the estimation of their demands, and a market-based algorithm which stems from microeconomic theory is adopted in the spectrum allocation within each cluster. An analysis is given on the iterative pricing algorithms of Excess Demand-Based (EDB) and Successive Over-Relaxation (SOR) for in-cluster market as well as on the process of spectrum purchase based on demand executed by cluster headers. The simulation results show that cluster profit is maximized by adopting the market-based algorithm, and that a significantly utility improvement is achieved by demand-based purchase of cluster headers compared with equal purchase. As a result, the spectrum allocation scheme proposed in this paper can improve the system performance efficiently. The convergence of EDB and SOR iterative algorithms is also proved by simulation.

FullText(HTML)

References(1)

References

Akyildiz I F, Lee W Y, Vuran C, and Mohanty S. Nextgeneration/dynamic spectrum access/cognitive radio wirelessnetworks: a survey[J].Computer Networks.2006, 50(13):2127-2159[2]Haykin S. Cognitive radio: brain-empowered wirelesscommunications [J].IEEE Journal on Selected Areas inCommunications.2005, 23(2):201-220[3]Serbetli S and Yener A. Relay assisted F/TDMA Ad hocnetworks: node classification, power allocation and relayingstrategies[J].IEEE Transactions on Communications.2008,56(6):937-947[4]Ibi S and Sampei S. A cluster relay coded cooperativestrategy in broadband wireless Ad-hoc networks[C].Information Theory and Its Applications, 2008. ISITA 2008.International Symposium, Auckland, New Zealand. Dec. 2008:1-6.[5]Kim Bongsoo, Choi Younghwan, Jung Kwansoo, ChoHochoong, Yu Fucai, and Kim Sang-Ha. A dynamicsingle-hop clustering mechanism adapted to overlaymulticast in mobile Ad hoc networks[C]. Asia-PacificConference on Communications. Busan, Republic of Korea.Aug. 31-Sept.1, 2006: 1-5.[6]Huang Chuan-he, Zhang Yuan-yuan, Jia Xiao-hua, ShiWen-ming, Cheng Yong, and Zhou Hao. An on-demandclustering mechanism for hierarchical routing protocol in Adhoc networks[C]. Wireless Communications, Networking andMobile Computing. Wuhan, China. Sep. 2006: 1-6.[7]赵林亮, 姜月秋, 张臻杰, 王光兴. Ad hoc 网络中资源管理的研究[J]. 小型微型计算机系统, 2005, 26(12): 2092-2095.[8]郑少仁，王海涛，赵志峰，米志超，黎宁. Ad hoc 网络技术[M]. 北京：人民邮电出版社，2005, 1: 91-96.[9]Perumal S, Baras J S, Graff C J, and Yee D G. Aerialplatform placement algorithms to satisfy connectivity,capacity and survivability constraints in wireless ad-hocnetworks [C]. Military Communications Conference.MILCOM 2008. San Diego, Nov. 2008: 1-7.[10]Niyato D and Hossain E. Hierarchical Spectrum sharing incognitive radio: a microeconomic approach[C]. WirelessCommunications and Networking Conference. Hong Kong.Mar. 2007: 3822-3826.[11]Gomes E R and Kowalczyk R. Learning the IPA market withindividual and social rewards[C]. Intelligent AgentTechnology, 2007. IEEE/WIC/ACM InternationalConference. Silicon Valley, USA. Nov. 2007: 328-334.[12]Gomes E and Kowalczyk R. Learning in market-basedresource allocation[C]. Computer and Information Science.ICIS 2007. Qubec, Canada. Jul. 2007: 475-482.[13]Qiu Y and Marbach P. Bandwidth allocation in Ad-hocnetworks: A price-based approach [C][J].Proc of IEEEINFOCOM2003. Washington DC. IEEE.2003, 2:797-807[14]Xin W and Henning S. Pricing network resources for adaptiveapplications[J]. IEEE/ACM Transaction on Networking.2006, 14(3): 506-519.

Relative Articles

Supplements(0)

Cited By

Proportional views