Matlab Implementation of Simple Counting Based Weighted Cooperative Spectrum Sensing and Initial Condition Rule


  • Nuria Ata Employee in INSA and former Graduate of Ajou university, Bisrate Gebriel, Addis Ababa, 124498, Ethiopia
  • Lee Chaewoo Professor in Ajou University, 206,world cup-roYeongtong-gu,Suwon-si Gyeonggi-do, 443-749, South Korea


Secondary user, optimal weight, simple counting rule, error probability, initial condition rule


Cooperative spectrum sensing allows strict regulatory performance requirement to be relaxed on local sensing. In practice secondary users are more likely to experience distinct signal strength depending on distance from primary transmitter. This shows the need for weighting local decision by local reliability. In this paper we discuss implementation issue of simple counting based decision weighting method. And we provide solution and a complete MATLAB implementation code. We demonstrate, by carefully selecting the initial conditions, we can get stable performance. And also our results shows that the optimal weighted method outperforms the existing equal weight combining in terms of lower total error probability.


. P. K. Verma , S. Taluja , R. L. Dua.“Performance analysis of energy detection, matched filter detection & cyclostationray feature detection spectrum sensing techniques.” IJCER, vol.2, Sep. 2012.

. A. Ghasemi, E. S. Sousa.” Spectrum sensing in cognitive radio networks: requirements, challenges and design trade-offs. “ Commun. Magazine, IEEE, pp.32-39, vol.46, Apr. 2008.

. D. Sun , T. Song , M. Wu, J. Hu , J. Guo , B. Gu.“Optimal sensing time of soft decision cooperative spectrum sensing in cognitive radio networks”, 2013 IEEE WCNC, pp. 4124-4128, Apr. 2013.

. N. Nguyen-Thanh, I. Koo.” Acluster-based selective cooperative spectrum sensing scheme in cognitive radio.” EURASIP J. Wireless. Commun. Networking, Jun. 2013.

. X. Huang, N. Han, G. Zheng, S. Sohn. “Weighted-collaborative spectrum sensing in cognitive radio.“ Commun. On Networking, China, pp.110-114, Aug. 2007.

. S. A. Alvi, M. S. Younis, M. Imran, Fazal-e-Amin. “A weighted linear combining scheme for cooperative spectrum sensing.” International Conference on Ambient Systems, Networks and Technology, pp.149-157, vol. 32, Jun. 2014.

. L. Xiao, K. Liu, and L. Ma.“A weighted cooperative spectrum sensing in cognitive radio networks” , ICINA, pp. v2-45 - v2-48, vol. 2, Oct. 2010.

. S. Maleki, S. P. Chepuri, G. Leus.“Energy and throughput efficient strategies for cooperative spectrum sensing in cognitive radios.” SPAWC, 2011 IEEE 12th International Workshop on, pp.71-75.

. Z. Chair, P. K. Varshney.“Optimal data fusion in multiple sensor detection systems.” IEEE Transactions on, Aerospace and Electronic Systems, vol. AES-22, pp.98-101, Jan.1986.

. N. Mansouri, M. Fathi.“Simple counting rule for optimal data fusion.” Proc. IEEE. Conf. on Control Applications, vol.2, pp.1186-1191, Jun 2003.




How to Cite

Ata, N. ., & Chaewoo , L. . (2021). Matlab Implementation of Simple Counting Based Weighted Cooperative Spectrum Sensing and Initial Condition Rule. American Scientific Research Journal for Engineering, Technology, and Sciences, 76(1), 56–70. Retrieved from