Skip to main content
SpringerLink
Log in

Adaptive Spectrum Detecting Algorithm in Cognitive Radio

  • Conference paper
  • First Online:
Foundations and Practical Applications of Cognitive Systems and Information Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 215))

  • 3014 Accesses

Abstract

Cognitive radio (CR) network can make an opportunistic access of spectrum licensed to a primary user (PU). The CR must perform spectrum sensing to detect active PU, thereby avoiding interfering with it. This chapter focuses on adaptively spectrum sensing, so that negative impacts to the performance of the CR network are minimized when CR users experience both stochastic data arrival and time-varying channel. Since the frequency of the spectrum sensing has a directly impact on system throughput and the probability of collision between the PU and CR user, the PU activity is modeled based on the characteristic analysis of the PU spectrum utilization. Based on that, an efficient adaptive sensing algorithm that takes into account the system stability, collision, and throughput is proposed. The CR users can make a balance between them by utilizing a “periodic control factor” which controls the adaptive adjustment of the spectrum sensing frequency. The simulation results indicate that the proposed algorithm has excellent performance on collision probability and throughput compared with conventional periodic spectrum sensing scheme. Meanwhile, it is shown that the proposed algorithm has low implementation complexity for practical applications.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. ITU Internet Reports (2005) The internet of things. http://www.itu.int/internetofthings/. Accessed 15 Feb 2010

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

    Google Scholar 

  3. Mchenry M, Spectrum white space measurements. http://www.Newamerica.net/.2007.7

  4. Federal Communications Commission: Spectrum policy task force report. http://www.Fcc.gov/sptf/.2007.7

  5. Prasad RV, Pawelczak P, Hoffmeyer HA, Berger HS (2008) Cognitive functionality in next generation wireless networks: standardization efforts. IEEE Commun Mag 46(4):72–78

    Google Scholar 

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

    Google Scholar 

  7. Akyidiz IF, Lee WY, Vuran MC, Mohanty S (2006) Next generation, dynamic spectrum access/cognitive radio wireless networks:a survey. Comput Network J 50(13):2127–2159

    Google Scholar 

  8. Haykin S, Thomson DJ, Reed JH (2009) Spectrum sensing for cognitive radio. Proc IEEE 97:849–877

    Google Scholar 

  9. Moghimi F, Nasri A, Schober R (2011) Adaptive Lp–norm spectrum sensing for cognitive radio networks. IEEE Trans Commun 59(7):1934–1945

    Google Scholar 

  10. Kim S, Lee J, Wang H, Hong D (2009) Sensing performance of energy detector with correlated multiple antennas. IEEE Signal Process Lett 16:671–674

    Article  Google Scholar 

  11. Shen J, Liu S, Zeng L, Xie G, Gao J, Liu Y Optimisation of cooperative spectrum sensing in cognitive radio network. IET Commun 3(7):1170–1178

    Google Scholar 

  12. Du K-L, Mow WH (2010) Affordable cyclostationarity-based spectrum sensing for cognitive radio with smart antennas. IEEE Trans Veh Technol 59(4):1877–1886

    Google Scholar 

  13. Liang YC, Zeng Y, Peh E, Hoang T (2008) Sensing-throughput tradeoff for cognitive radio networks. IEEE Trans Commun 7(4):1326–1337

    Google Scholar 

  14. Lee WY, Akyildiz IF (2008) Optimal spectrum sensing framework for cognitive radio networks. IEEE Trans Wirel Commun 7(10):3845–3857

    Google Scholar 

  15. Zhao Q, Chen Y (2007) Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: a POMDP framework. IEEE J Sel Areas Commun 25(3):589–600

    Google Scholar 

  16. Chen Y, Zhao Q, Swami A (2008) Joint design and separation principle for opportunistic spectrum access in the presence of sensing errors. IEEE Trans Inf Theory 54(5):2053–2071

    Google Scholar 

  17. Zhao Q, Krishnamachari B, Liu K (2008) On myopic sensing for multichannel opportunistic access: structure, optimality, and performance. IEEE Trans Wirel Commun 7(12):5431–5440

    Google Scholar 

  18. Hoang AT, Liang Y-C, Wong DTC, Zeng Y, Zhang R (2009) Opportunistic spectrum access for energy-constrained cognitive radios. IEEE Trans Wirel Commun 8(3):1206–1211

    Google Scholar 

  19. Geirhofer S, Tong L, Sadler BM (2007) Dynamic spectrum access in the time domain: modeling and exploiting white space. IEEE Commun Mag 45(5):66–72

    Google Scholar 

  20. Geirhofer S, Tong L, Sadler BM (2008) Cognitive medium access: constraining interference based on experimental models. IEEE J Sel Areas Commun 26(1):95–105

    Google Scholar 

  21. Zhao Q, Geirhofer S, Tong L, Sadler BM (2008) Opportunistic spectrum access via periodic channel sensing. IEEE Trans Signal Process 56(2):785–796

    Google Scholar 

  22. Wellens M, de Baynast A, Mahonen P (2008) Exploiting historical spectrum occupancy information for adaptive spectrum sensing. In: Proceedings of IEEE WCNC, Las Vegas, pp 717–722

    Google Scholar 

  23. Datla D, Rajbanshi R, Wyglinski AM, Minden GJ (2007) Parametric adaptive spectrum sensing framework for dynamic spectrum access network. In: Proceedings of DySPAN, Dublin, Ireland, pp 482–485

    Google Scholar 

  24. Han N, Shon SH, Joo JO, Kim JM (2006) Spectral correlation based signal detection method for spectrum sensing in IEEE 802.22 WRAN systems. In: Proceedings of the international conference on advanced communication technology

    Google Scholar 

  25. Zeng YH, Liang YC (2009) Eigenvalue based sensing algorithms for cognitive radio. IEEE Trans Commun 57(6):1784–1793

    Google Scholar 

  26. Choi KW (2010) Adaptive sensing technique to maximize spectrum utilization in cognitive radio. IEEE Trans Veh Technol 59(2):992–998

    Google Scholar 

  27. Hoang AT, Liang Y-C, Zeng Y (2010) Adaptive joint scheduling of spectrum sensing and data transmission in cognitive radio networks. IEEE Trans Commun 58(1):235–246

    Google Scholar 

  28. Kim H, Shin KG (2008) Efficient discovery of spectrum opportunities with MAC-layer sensing in cognitive radio networks. IEEE Trans Mob Comput 7(5):533–545

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Communication and Technology Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Yun Liu, Qicong Peng, Huaizong Shao & Ling Wang

  2. State Key Lab of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China

    Fuchun Sun

  3. State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, CAS, Beijing, 100101, China

    Xingfeng Chen

Authors
  1. Yun Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qicong Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fuchun Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Huaizong Shao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xingfeng Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ling Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fuchun Sun .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, Beijing, People's Republic of China

    Fuchun Sun

  2. College of Mechatronics and Automation, National University of Defense Technolog, Changsha, People's Republic of China

    Dewen Hu

  3. Department of Computer Science and Techn, Tsinghua University, Beijing, People's Republic of China

    Huaping Liu

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Liu, Y., Peng, Q., Sun, F., Shao, H., Chen, X., Wang, L. (2014). Adaptive Spectrum Detecting Algorithm in Cognitive Radio. In: Sun, F., Hu, D., Liu, H. (eds) Foundations and Practical Applications of Cognitive Systems and Information Processing. Advances in Intelligent Systems and Computing, vol 215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37835-5_40

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-37835-5_40

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37834-8

  • Online ISBN: 978-3-642-37835-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation