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Performance analysis of secondary users under heterogeneous licensed spectrum environment in cognitive radio ad hoc networks

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Abstract

Cognitive radio (CR) is a hopeful technology to sort out spectrum scarcity and underutilization problem in ad hoc networks. With the help of cognitive radio technology, unlicensed users can efficiently utilize the unused part of heterogeneous licensed spectrum. In this article, we present a three-dimensional (3D) Markov chain analysis for spectrum management scheme under heterogeneous licensed bands of two different licensed spectrum pools in cognitive radio ad hoc networks. We present the concept of interpool and intrapool spectrum handoff in the proposed model and derive blocking probability, dropping probability, non-completion probability, and throughput to estimate the performance of the secondary users under heterogeneous licensed spectrum environment. The impact of secondary users dynamic along with the primary users’ activity model on the performance measuring metrics in terms of blocking probability, dropping probability, non-completion probability, and throughput for three different cases is also investigated. The proposed model offers significant improvement in the performance of secondary users under heterogeneous licensed spectrum environment in a CR ad hoc network.

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References

  1. (2016) Cisco Visual Networking Index: Mobile data traffic forecast update, 2015–2020. CISCO, San Jose

  2. Bezabih H, Ellingsaeter B, Noll J, Maseng TT (2012) Digital broadcasting: increasing the available white space spectrum using TV receiver information. IEEE Veh Technol Mag 7(1):24–30

    Article  Google Scholar 

  3. Das D, Das S (2015) A survey on Spectrum occupancy measurement for cognitive radio. Springer Wirel Pers Commun 85(4):2581–2598

    Article  Google Scholar 

  4. Wang B, Liu KJR (2011) Advances in cognitive radio networks: a survey. IEEE J Sel Top Sign Proces 5(1):5–23

    Article  Google Scholar 

  5. Federal Communications Commission (FCC) (2003) Notice for Proposed Rulemaking (NPRM 03 322): Facilitating Opportunities for Flexible, Efficient, and Reliable Spectrum Use Employing Spectrum agile Radio Technologies. ET Docket No. 03 108

  6. Mitola J, Maguire GQ (1999) Cognitive radio: making software radios more personal. IEEE Pers Commun 6(4):13–18

    Article  Google Scholar 

  7. Haykin S (2005) Cognitive radio: brain-empowered wireless communications. IEEE J Sel Areas Commun 23(2):201–220

    Article  Google Scholar 

  8. Jouini W, Moy C, Palicot J (2012). Decision making for cognitive radio equipment: analysis of the first 10 years of exploration. In: Springer EURASIP Journal on Wireless Communications and Networking. https://doi.org/10.1186/1687-1499-2012-26

  9. Stevenson CR, Chouinard G, Lei Z, Hu W, Shellhammer SJ, Caldwell W (2009) IEEE 802.22: the first cognitive radio wireless regional area network standard. IEEE Commun Mag 47(1):130–138

    Article  Google Scholar 

  10. Zhu X, Shen L, Yum TSP (2007) Analysis of cognitive radio spectrum access with optimal channel reservation. IEEE Commun Lett 11(4):304–306

    Article  Google Scholar 

  11. Xing Y, Chandramouli R, Mangold S, N S S. (2006) Dynamic spectrum access in open spectrum wireless networks. IEEE J Sel Areas Commun 24(3):626–637

    Article  Google Scholar 

  12. Akyildiz IF, Lee WY, Vuran MC, Mohanty S (2006) Next generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Elsevier Comput Netw 50(13):2127–2159

    Article  Google Scholar 

  13. Wang LC, Chen A, Wei DSL (2007) A Cognitive MAC Protocol for QoS Provisioning in Overlaying Ad Hoc Networks. 2007 4th IEEE consumer communications and networking conference, Las Vega, 1139–1143

  14. Kalil MA, Al-Mahdi H, Mitschele-Thiel A (2009) Analysis of opportunistic spectrum access in cognitive ad hoc networks. 16th springer international conference on analytical and stochastic Modelling techniques and applications, Madrid, 16–28

  15. Kalil MA, Al-Mahdi H, Mitschele-Thiel A (2013) Performance evaluation of secondary users operating on a heterogeneous spectrum environment. Springer Wirel Pers Commun 72(4):2251–2262

    Article  Google Scholar 

  16. Zhi-jin Z, Lu-ping Z, Hai-quan W (2015) Spectrum handoff based on adaptive weights adjustment. IET Commun 9(5):674–680

    Article  Google Scholar 

  17. Hoque S, Arif W (2019) Performance analysis of spectrum handoff under heterogeneous spectrum environment in ad hoc and centralized CR networks. Ad Hoc Netw 91:101877

    Article  Google Scholar 

  18. Mathonsi TE, Kogeda OP (2016) Handoff delay reduction model for heterogeneous wireless networks," 2016 IST-Africa week conference, Durban, 1–7

  19. Bayrakdar ME, Çalhan A (2016) Performance analysis of proactive decision spectrum handoff for MAC protocols in cognitive radio networks. 2016 24th signal processing and communication application conference (SIU), Zonguldak, 481–484

  20. Alhammadi A, Roslee M, Alias MY (2016) Analysis of spectrum handoff schemes in cognitive radio network using particle swarm optimization. 2016 IEEE 3rd international symposium on telecommunication technologies (ISTT), Kuala Lumpur, 103-107

  21. Arif W, Hoque S, Sen D, Baishya S (2015) A comprehensive analysis of spectrum handoff under different distribution models for cognitive radio networks. Springer Wirel Pers Commun 85(4):2519–2548

    Article  Google Scholar 

  22. Hoque S, Arif W (2017) Performance analysis of cognitive radio networks with generalized call holding time distribution of secondary user. Telecommun Syst 66:95–108. https://doi.org/10.1007/s11235-017-0283-6

    Article  Google Scholar 

  23. Gkionis G, Sgora A, Vergados D D, Michalas A (2017) An effective spectrum handoff scheme for cognitive radio ad hoc networks. 2017 wireless telecommunications symposium (WTS), Chicago, 1–7

  24. Sheikholeslami F, Nasiri-Kenari M, Ashtiani F (2015) Optimal probabilistic initial and target channel selection for spectrum handoff in cognitive radio networks. IEEE Trans Wirel Commun 14(1):570–584

    Article  Google Scholar 

  25. Tayel AF, Rabia SI, Abouelseoud Y (2016) An optimized hybrid approach for spectrum handoff in cognitive radio networks with non-identical channels. IEEE Trans Commun 64(11):4487–4496

    Article  Google Scholar 

  26. Al-Mahdi H, Kalil MA, Liers F, Thiel AM (2009) Increasing spectrum capacity for ad hoc networks using cognitive radios: an analytical model. IEEE Commun Lett 13(9):676–678

    Article  Google Scholar 

  27. Jee A, Hoque S, Arif W. (2017) Analysis of non completion probability for cognitive radio ad hoc networks. 2017 IEEE Calcutta Conference (CALCON), Kolkata, pp 80–84

  28. Jee A, Hoque S, Talukdar B, Arif W (2018) Analysis of link maintenance probability for cognitive radio ad hoc networks. 2018 5th international conference on signal processing and integrated networks (SPIN), Noida, pp 385–389

  29. Kalil MA, Al-Mahdi H, Hammam H, Saroit IA (2017) A buffering and switching scheme for admission control in cognitive radio networks. IEEE Wireless Commun Lett 6(3):358–361

    Article  Google Scholar 

  30. Chu TMC, Phan H, Zepernick HJ (2014) Dynamic spectrum access for cognitive radio networks with prioritized traffics. IEEE Commun Lett 18(7):1218–1221

    Article  Google Scholar 

  31. Bayrakdar ME, Çalhan A (2017) Improving spectrum handoff utilization for prioritized cognitive radio users by exploiting channel bonding with starvation mitigation. Int J Electron Commun (AEÜ) 71(C):181–191

    Article  Google Scholar 

  32. El-Toukhey AT, Ammar AA, Tantawy NM, Tarrad IF (2017) Performance analysis of different opportunistic access based on secondary users priority using licensed channels in cognitive radio networks. 2017 34th National Radio Science Conference (NRSC), Alexandria, 160–169

  33. Zhang L (2017) Complete balance equation and blocked probability for secondary radio limited access scheme in cognitive radio networks. 2017 ninth international conference on ubiquitous and future networks (ICUFN), Milan, 976–978

  34. Bharathi PS, Raj KK, Singh HK, Kumar D (2014) Throughput analysis of different traffic distribution in cognitive radio network. 2014 international conference on recent trends in information technology, Chennai, 1–6

  35. Lee WY, Akyildiz IF (2012) Spectrum-aware mobility management in cognitive radio cellular networks. IEEE Trans Mob Comput 11(4):529–542

    Article  Google Scholar 

  36. Yue W, Matsumoto Y (2002) Performance analysis of multi-channel and multi-traffic on wireless communication networks. Kluwer Academic Publishers

  37. Gross D, Harris C (1985) Fundamentals of queueing theory. Wiley

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Acknowledgments

The authors highly acknowledge the Project (File Number: SRG/2019/001744 dated 17-Dec-2019), Science and Engineering Research Board (SERB), and Government of India for the resources provided and also their never ending support and motivation for the research work.

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Authors and Affiliations

  1. Department of Electrical Engineering, Indian Institute of Technology Delhi, Delhi, India

    Anand Jee

  2. Department of Electronics and Communication Engineering, Madanapalle Institute of Technology & Science, Madanapalle, India

    Shanidul Hoque

  3. Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Silchar, India

    Wasim Arif

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  1. Anand Jee
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  2. Shanidul Hoque
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  3. Wasim Arif
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Correspondence to Shanidul Hoque.

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Jee, A., Hoque, S. & Arif, W. Performance analysis of secondary users under heterogeneous licensed spectrum environment in cognitive radio ad hoc networks. Ann. Telecommun. 75, 407–419 (2020). https://doi.org/10.1007/s12243-020-00761-8

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  • DOI: https://doi.org/10.1007/s12243-020-00761-8

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