Skip to main content
SpringerLink
Log in

Binary decision-based collaborative spectrum sensing in infrastructure-less cognitive radio network

  • Published:
Annals of Telecommunications Aims and scope Submit manuscript

Abstract

Collaborative spectrum sensing (CSS) plays a vital role in achieving accurate spectrum sensing results in a cognitive radio network (CRN). However, CSS in infrastructure-less CRNs is a challenging task as there is no central authority which aggregates individual sensing reports to take a final decision. Hence, it becomes the responsibility of each node to aggregate sensing reports of other nodes to take the final decision. Towards this end, we present two collaborative spectrum sensing techniques for infrastructure-less CRN based on message passing. The first technique is distributed binary decision-based CSS (DBCSS), in which a node broadcasts its sensing report and uses the binary decisions of its h-hop neighbors for making its final sensing decision. The second one is distributed cluster-based CSS (DCCSS) in which a cluster head consolidates the sensing reports in its cluster into a message and broadcast this message in the network. We support the validity of the proposed schemes through extensive simulation results.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

References

  1. Mitola J (1999) Cognitive radio for flexible mobile multimedia communications. In: Proceedings of IEEE international workshop on mobile communications, San Diego, pp 3-10

  2. Mitola J (2000) Cognitive radio: an integrated agent architecture for software defined radio. Royal Institute of Technology (KTH, Ph.D. dissertation

    Google Scholar 

  3. Ghasemi A, Sousa E (2005) Collaborative spectrum sensing for opportunistic access in fading environment. In: Proceedings of IEEE DySPAN, USA, pp 131-136

  4. Mishra S, Sahai A, Brodersen R (2006) Cooperative sensing among cognitive radio. In: Proceedings of IEEE international conference on communications, Turkey, 1658-1663

  5. Letaief K B, Zhang W (2009) Cooperative communications for cognitive radio networks. Proc IEEE 97 (5):878–893

    Article  Google Scholar 

  6. Chen R, Park J, Hou T, Reed J (2008) Towards secure distributed spectrum sensing in cognitive radio networks. IEEE Commun Magazine 46(4):50–55

    Article  Google Scholar 

  7. Fragkidakis A G, Tragos E Z, Askoxylakis I G (2013) A survey on security threats and detection techniques in cognitive radio networks. IEEE Commun Surv Tutorials 15(1):428–445

    Article  Google Scholar 

  8. Ian Akyildiz F, Won-Yeol L, Mehmet Varun C, Mohanty S (2006) Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Comp Netws 50(13):2127–2159

    Article  Google Scholar 

  9. Garin F, Schenato L (2010) A survey on distributed estimation and control applications using linear consensus algorithms. In: Networked control systems. LNCIS, vol 406. Springer, London, pp 75–107

    Chapter  Google Scholar 

  10. Kar S, José Moura MF (2009) Distributed consensus algorithms in sensor networks with imperfect communication: link failures and channel noise. IEEE Trans Signal Process 57(1):355–369

    Article  MathSciNet  Google Scholar 

  11. Yildizy ME, Aysaly TC, Barnet KE (2009) In-network cooperative spectrum sensing. In: Proceedings of 17th European signal processing conference, UK, pp 1903-1907

  12. Ejaz W, Hasan N, Seok Kim H, Azam MA (2011) Fully distributed cooperative spectrum sensing for cognitive radio AdHoc networks. In: Proceedings of frontiers of information technology. FIT, Islamabad, pp 9–13

  13. Zhiqiang L, Yu F R, Huang M (2010) A distributed consensus-based cooperative spectrum-sensing scheme in cognitive radios. IEEE Trans Veh Technol 59(1):383–393

    Article  Google Scholar 

  14. Zhiqiang L, Yu F R, Minyi H (2009) Distributed spectrum sensing in cognitive radio networks. In: Proceedings of IEEE wireless communications and networking conference. WCNC, Budapest, pp 1–5

  15. Raza A, Ahmed S S, Ejaz W, Hyung SK (2012) Cooperative spectrum sensing among mobile nodes in cognitive radio distributed network. In: Proceedings of 10th international conference on frontiers of information technology. FIT, Islamabad, pp 18–23

  16. Yu F R, Huang M, Tang H (2010) Biologically inspired consensus-based spectrum sensing in mobile AdHoc networks with cognitive radios. IEEE Netw 24(3):26–30

    Article  Google Scholar 

  17. Yu F R, Tang H, Huang M, Zhiqiang L, Mason PC (2009) Defense against spectrum sensing data falsification attacks in mobile ad hoc networks with cognitive radios. In: Proceedings of IEEE military communications conference (MILCOM), Boston, USA, pp 1–7

  18. Tang H, Yu F R, Huang M, Li Z (2012) Distributed consensus-based security mechanisms in cognitive radio mobile ad hoc networks. IET Commun 6(8):974–983

    Article  MathSciNet  Google Scholar 

  19. Sheng L, Zhu H, Li S, Xu L, Chen C, Guan X (2012) An adaptive deviation-tolerant s scheme for distributed cooperative spectrum sensing. In: Proceedings of IEEE GLOBECOM, USA, pp 603-608

  20. Qiben Y, Ming L, Jiang T, Wenjing L, Hou YT (2012) Vulnerability and protection for distributed consensus-based spectrum sensing in cognitive radio networks. In: Proceedings of IEEE INFOCOM, USA, pp 900-908

  21. Vosoughi A, Cavallaro JR, Marshall A (2015) Robust consensus-based cooperative spectrum sensing under insistent spectrum sensing data falsification attacks. In: Proceedings of IEEE GLOBECOM, San Diego, pp 1-6

  22. Vosoughi A, Cavallaro J R, Marshall A (2016) Trust-aware consensus-inspired distributed cooperative spectrum sensing for cognitive radio Ad Hoc networks. IEEE Trans Cogn Commun Netws 2(1):24–37

    Article  Google Scholar 

  23. Vosoughi A, Cavallaro JR, Marshall A (2014) A cooperative spectrum sensing scheme for cognitive radio ad hoc networks based on gossip and trust. In: Proceeding IEEE GlobalSIP, Atlanta, pp 1175-1179

  24. Wang J, Chen IR, Tsai JJP, Wang DC (2016) Trust-based cooperative spectrum sensing against SSDF attacks in distributed cognitive radio networks. In: Proceedings of IEEE CQR, USA, pp 1-6

  25. Zheng S, Yang X, Lou C (2011) Distributed consensus algorithms for decision fusion based cooperative spectrum-sensing in cognitive radios. In: Proceedings of 11th international conference on communications and information technologies. ISCIT, China, pp 217–221

  26. Li H, Liu X, Xu L (2014) Analysis of distributed consensus-based spectrum sensing algorithm in cognitive radio networks. In: Proceedings of 10th international conference on computational intelligence and security (CIS), Kunming, pp 593–597

  27. Bera D, Maheshwari S, Chakrabati I, Pathak SS (2014) Decentralised cooperative spectrum sensing in cognitive radio without fusion center. In: Proceedings of 20th national conference on communication. NCC, Kanpur, pp 1–5

  28. Rajkumari R, Marchang N (2015) Distributed binary decision-based collaborative spectrum sensing in infrastructure-less cognitive radio network. In: Proceedings of 3rd international symposium on women in computing and informatics. WCI, India, pp 335–340

  29. Jeng A A, Jan R H (2007) The r-neighborhood graph: an adjustable structure for topology control in wireless Adhoc networks. IEEE Trans Parallel and Dist Syst 18(14):536–549

    Article  Google Scholar 

  30. Lin C R, Gerla M (1997) Adaptive clustering for mobile wireless networks. IEEE J Sel Areas Commun 15 (7):1265–1275

    Article  Google Scholar 

  31. Yucek T, Arslan H (2011) A survey of spectrum algorithms for cognitive radio applications. IEEE Commun Surv Tutorials 11(1):116–130

    Article  Google Scholar 

  32. Althunibat S, Palacios R, Granelli F (2012) Energy-efficient spectrum sensing in cognitive radio networks by coordinated reduction of the sensing users. In: Proceedings of IEEE international conference on communications. ICC, Ottawa, pp 1399–1404

  33. Carlos C, Ghosh M, Cavalcanti D, Challapali K (2007) Spectrum sensing for dynamic access of TV bands. In: Proceedings of IEEE 2nd international conference on cognitive radio oriented wireless networks and communications, USA, pp 225–233

Download references

Author information

Authors and Affiliations

  1. Computer Science and Engineering Department, NERIST, Nirjuli, Arunachal Pradesh, 791109, India

    Roshni Rajkumari & Ningrinla Marchang

Authors
  1. Roshni Rajkumari
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ningrinla Marchang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Roshni Rajkumari.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rajkumari, R., Marchang, N. Binary decision-based collaborative spectrum sensing in infrastructure-less cognitive radio network. Ann. Telecommun. 73, 677–688 (2018). https://doi.org/10.1007/s12243-018-0670-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12243-018-0670-3

Keywords

Search

Navigation