skip to main content
10.1145/2811587.2811599acmconferencesArticle/Chapter ViewAbstractPublication PagesmswimConference Proceedingsconference-collections
research-article

Communication and Block Game in Cognitive Radio Networks

Published: 02 November 2015 Publication History

Abstract

In this paper, we initiate the Communication and Block Game between two unlicensed users and an adversary in Cognitive Radio Networks (CRNs). In each time slot, the two unlicensed users can successfully communicate on the common available channel if it is not blocked by the adversary. In the communication and block game, the two un-licensed users aim to maximize their communication load, denoted as the number of time slots of their successful communications, while the adversary aims to minimize it. We propose efficient algorithms for both users and the adversary and we prove the proposed algorithms will lead a Nash Equilibrium, i.e. the users can achieve the maximum communication load against any adversary's blocking strategy, while the adversary can minimize the users' communication load against any users' channel accessing strategy. We also present efficient algorithms for both users and adversary for the multiple channels scenario where the users and the adversary are equipped with multiple radios. These algorithms also guarantee high communication load for the users, while the adversary can also block a considerable number of users'communications. Our simulations validate the theoretical analyses.

References

[1]
I. Akyildiz, W. Lee, M. Vuran, and S. Mohanty. NeXt Generation Dynamic Spectrum Access Cognitive Radio Wireless Networks: A Survey. Computer Networks, 50(13): 2127--2159, 2006.
[2]
.J. Aumann(2008). "Game Theory" Introduction, The New Palgrave Dictionary of Economics, 2nd Edition.
[3]
K. Bian, J.-M. Park. Maximizing Rendezvous Diversity in Rendezvous Protocols for Decentralized Cognitive Radio Networks. IEEE Trans. on Mobile Computing, 12(7):1294--1307, 2013.
[4]
S. Chen, A. Russell, A. Samanta, and R. Sundaram. Deterministic Blind Rendezvous in Cognitive Radio networks. In ICDCS, 2014.
[5]
I. Chuang, H.-Y. Wu, K.-R. Lee. and Y.-H. Kuo. Alternate Hop-and-Wait Channel Rendezvous Method for Cognitive Radio Networks. In INFOCOM, 2013.
[6]
L. DaSilva, and I. Guerreiro. Sequence-Based Rendezvous for Dynamic Spectrum Access. In DySPAN, 2008.
[7]
. Gao, Z. Gu, Q.-S. Hua and H. Jin. Multi-Radio Channel Detecting Jamming Attack Against Enhanced Jump-Stay Based Rendezvousin Cognitive Radio Networks. In COCOON, 2015.
[8]
Z. Gu, Q.-S. Hua, Y. Wang, and F. C.M. Lau. Nearly Optimal Asynchronous Blind Rendezvous Algorithm for Cognitive Radio Networks. In SECON, 2013.
[9]
Z. Gu, Q.-S. Hua, and W. Dai. Local Sequence Based Rendezvous Algorithms for Cognitive Radio Networks. In SECON, 2014.
[10]
Z. Gu, Q.-S. Hua, and W. Dai. Fully Distributed Algorithms for Blind Rendezvous in Cognitive Radio Networks. In MOBIHOC, 2014.
[11]
. Lee, S. Oh and M. Gerla. Frequency Quorum Rendezvousfor Fast and Resilient Key Establishment under Jamming Attack. In Mobicom Poster, 2010.
[12]
G. Li, Z. Gu, X. Lin, H. Pu, and Q.-S. Hua. Deterministic Distributed Rendezvous Algorithms for Multi-Radio Cognitive Radio Networks. In MSWiM, 2014.
[13]
H. Liu, Z. Lin, X. Chu, and Y.-W. Leung. Jump-Stay Rendezvous Algorithm for Cognitive Radio Networks. IEEE Trans. on Parallel and Distributed Systems, 23(10):1867--1881, 2012.
[14]
. Oh and D. Thuente. Limitations of Quorum-based Rendezvous and key establishment schemes against sophisticated jamming attacks. In phMILCOM, 2012.
[15]
. Oh and D. Thuente. Channel Detecting Jamming Attacks Against Jump-Stay Based Channel Hopping Rendezvous Algorithm for Cognitive Radio Networks. In phICCCN, 2013.
[16]
. Pu, Z. Gu, Q.-S. Hua, H. Jin. Communication and Block Game in Cognitive Radio Networks. http://grid.hust.edu.cn/qshua/mswim15full.pdf
[17]
. Rahamn and M. Krunz. Game-theoretic Quorum-based Frequency Hoppingfor Anti-jamming Rendezvous in DSA Networks. In phDySPAN, 2014.
[18]
P. Shin, D. Yang, and C. Kim. A Channel Rendezvous Scheme for Cognitive Radio Networks. phIEEE Communications Letters, 14(10):954--956, 2010.
[19]
. Strasser, C. Popper and S. Capkun. Efficient uncoordianted fhss anti-jamming communication. In phMOBIHOC, 2009.
[20]
N. Tadayon, and S. Aissa. Multi-Channel Cognitive Radio Networks: Modeling, Analysis and Synthesis. phIEEE Journal on Selected Areas in Communications, 2014.

Index Terms

  1. Communication and Block Game in Cognitive Radio Networks

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      MSWiM '15: Proceedings of the 18th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems
      November 2015
      358 pages
      ISBN:9781450337625
      DOI:10.1145/2811587
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Sponsors

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 02 November 2015

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. cognitive radio networks
      2. game theory
      3. rendezvous

      Qualifiers

      • Research-article

      Funding Sources

      • National Basic Research Program of China
      • National Natural Science Foundation of China

      Conference

      MSWiM'15
      Sponsor:

      Acceptance Rates

      MSWiM '15 Paper Acceptance Rate 34 of 142 submissions, 24%;
      Overall Acceptance Rate 398 of 1,577 submissions, 25%

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)2
      • Downloads (Last 6 weeks)0
      Reflects downloads up to 13 Feb 2025

      Other Metrics

      Citations

      View Options

      Login options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Figures

      Tables

      Media

      Share

      Share

      Share this Publication link

      Share on social media