Abstract
Cooperation among secondary users improves the spectrum sensing performance by allowing local decisions measured over independent sensing channels. This reduces the miss detection and false alarm probabilities. Most of the works in cooperative spectrum sensing techniques assume perfect channels between the cooperating secondary users. In this paper, we considered the effect of imperfect channels. Total error rate and success probabilities are calculated for an additive white Gaussian noise channel and a Rayleigh fading channel. The optimal number of cooperative secondary users is estimated over nonfading and fading channels. Simulation results show the variation of success probability with respect to channel imperfection for different number of secondary users. This is useful for identifying the unutilized spectrum.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Mitola J, Macguire GQ (1999) Cognitive radio: making software radios more personal. IEEE Pers Commun Mag 6(4):13–18
Spectrum Policy Task Force (2002) Rep. ET Docket, Washington, D.C., USA
Yucek T, Arslan H (2009) A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Commun Surv Tuts 11(1):116–130
Zeng Y, Liang Y-C, Hoang AT, Zhang R (2010) A review on spectrum sensing for cognitive radio: challenges and solutions. EURASIP J Adv Signal Process
Quan Z, Cui S, Sayed A, Poor H (2009) Optimal multiband joint detection for spectrum sensing in cognitive radio networks. IEEE Trans Signal Process 57(3):1128–1140
Rif-Pous H, Blasco M, Garrigues C (2012) Review of robust cooperative spectrum sensing techniques for cognitive radio networks. Wireless Pers Commun 67(2):175–198
Akyildiz IF, Lo BF, Balakrishnan R (2011) Cooperative spectrum sensing in cognitive radio networks: a survey. Elsevier Phys Commun 4(1):40–62
Nallagonda S, Suraparaju S, Roy SD, Kundu S (2011) Performance of energy detection based spectrum sensing in fading channels. In: Proceedings of IEEE International Conference on Computer and Communication Technology (ICCCT’11), pp 575–580
Ghasemi A, Sousa ES (2007) Opportunistic spectrum access in fading channels through collaborative sensing. IEEE J Sel Areas Commun 2(2):71–82
Ghasemi A, Sousa ES (2006) Impact of user collaboration on the performance of opportunistic spectrum access. In: Proceedings of the IEEE Vehicular Technology Conference (VTC Fall’06), Montreal
Lee SH, Lee YH (2009) Hard decision combining-based cooperative spectrum sensing in cognitive radio systems. In: proceedings of the international conference on wireless communication and mobile computing, 21–24 June, ISBN: 978-1-60558-569-7, pp 906–910
Armi N, Saad NM, Arshad M (2009) Hard decision fusion based cooperative spectrum sensing in cognitive radio system. ITB 3(2):109–122
Singh A, Bhatnagar MR, Mallik RK (2016) Performance of an improved energy detector in multi hop cognitive radio networks. IEEE Trans Veh Technol 65:732–743
SethiR, Bala I (2013) Performance evaluation of energy detector for cognitive radio networks. In: IOSR J Electron Commun Eng 8:46–51
Stuber GL (2002) Principles of mobile communications, 2nd edn. Kluwer Academic Publishers, Norwell, MA
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sudhamani, C., Satya Sai Ram, M. (2019). Cooperative Spectrum Sensing Over Rayleigh Fading Channel. In: Saini, H., Singh, R., Patel, V., Santhi, K., Ranganayakulu, S. (eds) Innovations in Electronics and Communication Engineering. Lecture Notes in Networks and Systems, vol 33. Springer, Singapore. https://doi.org/10.1007/978-981-10-8204-7_24
Download citation
DOI: https://doi.org/10.1007/978-981-10-8204-7_24
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-8203-0
Online ISBN: 978-981-10-8204-7
eBook Packages: EngineeringEngineering (R0)