Fast Cooperative Spectrum Sensing Method Based on Improved Particle Swarm Optimization

doi:10.13438/j.cnki.jdzk.2018.04.006

Abstract

Abstract:

To improve the computation efficiency and the sensing performance,a new linear cooperative spectrum sensing algorithm is developed for cognitive radio.In the proposed method,the improved particle swarm optimization (PSO) is utilized to obtain the optimal weight vector to maximize the probability of detection by dynamically changing the inertia weight in each iteration.Due to using the of time varying inertia weight,the proposed PSO based cooperative spectrum sensing algorithm has good global exploration capability at the beginning of the swarm flight,and with the increase in the number of iterations,especially in the late swarm flight,has good local search capability.The simulation results illustrate that the proposed method has faster convergence speed than the method based on the traditional PSO.At the same time,it shows better detection performance than both the method based on modified deflection coefficient and the method based on traditional PSO.The simulation results under different sensing scenarios validate the effectiveness of the proposed cooperative sensing algorithm.

Key words: cognitive radio, cooperative spectrum sensing, particle swarm optimization, energy detection, modified deflection coefficient

LIU Yaofeng,DENG Yu,SHU Ting,LEI Kejun. Fast Cooperative Spectrum Sensing Method Based on Improved Particle Swarm Optimization[J]. Journal of Jishou University（Natural Sciences Edition), DOI: 10.13438/j.cnki.jdzk.2018.04.006.

References

[1] SENGUPTA S,SUBBALAKSHMI K P.Open Research Issues in Multi-Hop Cognitive Radio Networks[J].Communications Magazine IEEE,2013,51(4):168-176.
[2] ZHOU F,BEAULIEU N C,LI Z,et al.Energy-Efficient Optimal Power Allocation for Fading Cognitive Radio Channels:Ergodic Capacity,Outage Capacity,and Minimum-Rate Capacity[J].IEEE Transactions on Wireless Communications,2016,15(4):2 741-2 755.
[3] MONEMIAN M,MAHDAVI M,OMIDI M J.Optimum Sensor Selection Based on Energy Constraints in Cooperative Spectrum Sensing for Cognitive Radio Sensor Networks[J].IEEE Sensors Journal,2016,16(6):1 829-1 841.
[4] WU X,FU N,LABEAU F.Relay-Based Cooperative Spectrum Sensing Framework Under Imperfect Channel Estimation[J].IEEE Communications Letters,2014,19(2):239-242.
[5] GHASEMI A,SOUSA E S.Collaborative Spectrum Sensing for Opportunistic Access in Fading Environments[C].First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.IEEE,2005:131-136.
[6] VISOTSKY E,KUFFNER S,PETERSON R.On Collaborative Detection of TV Transmissions in Support of Dynamic Spectrum Sharing[C].First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.IEEE,2005:338-345.
[7] QUAN Z,CUI S,SAYED A H.Optimal Linear Cooperation for Spectrum Sensing in Cognitive Radio Networks[J].IEEE Journal of Selected Topics in Signal Processing,2008,2(1):28-40.
[8] QUAN Z,CUI S,SAYED A H.An Optimal Strategy for Cooperative Spectrum Sensing in Cognitive Radio Networks[C].Global Telecommunications Conference,GLOBECOM '07,IEEE,2007:2 947-2 951.
[9] ZHENG S,LOU C,YANG X.Cooperative Spectrum Sensing Using Particle Swarm Optimisation[J].Electronics Letters,2010,46(22):1 525-1 526.
[10] KRISHNAMOORTHY K.Handbook of Statistical Distributions with Applications[M].Chapman & Hall/CRC,Boca Raton,FL,USA,2006.

[1]	TAN Zhewen, LEI Kejun, YANG Xi, WANG Xuming, TAN Yuhao. Spectrum Sensing Algorithm Based on Joint Detection of Skewness and Kurtosis [J]. Journal of Jishou University(Natural Sciences Edition), 2023, 44(6): 14-19.
[2]	TIAN Chong, LIU Tingting, TAN Zhewen, TAN Yuhao, LEI Kejun, YANG Xi. Optimal Multiband Collaborative Spectrum Sensing Algorithm Based on Constrained PSO Algorithm [J]. Journal of Jishou University(Natural Sciences Edition), 2023, 44(3): 34-38.
[3]	WANG Lin. Reactive Power Optimization of Power System Based on Phasor Particle Swarm Optimization [J]. Journal of Jishou University（Natural Sciences Edition), 2020, 41(4): 33-37.
[4]	HUANG Xiaoyu, TIAN Kun, WANG Xiangmin, YANG Xi. Blind Primary User Signal Detection Algorithm Based on Matrix Eigenvalues [J]. Journal of Jishou University（Natural Sciences Edition), 2020, 41(1): 35-41.
[5]	YU Dawei, ZHOU Haipeng, SUN Min, LI Yang, ZHANG Enbao, LI Qianqian. Adaptive Quantum Particle Swarm Optimization Algorithm Based on Normal Cloud Model [J]. Journal of Jishou University（Natural Sciences Edition), 2019, 40(6): 29-39.
[6]	JIN Jieli, JIAN Aiwen, ZHANG Shuo, ZHANG Xuanyu. Course Arrangement System Based on Self-Adaptive Particle Swarm Optimization [J]. Journal of Jishou University（Natural Sciences Edition), 2019, 40(6): 17-20.
[7]	SONG Mongpei, MO Liping, ZHOU Kaiqing. Influence of Inertia Weight and Learning Factor on Performance of Standard PSO Algorithm [J]. Journal of Jishou University（Natural Sciences Edition), 2019, 40(4): 24-32.
[8]	WANG Hanrui,LI Manjiang,TANG Pengcheng,YANG Xi,LEI Kejun. A Novel Spectrum Sensing Algorithm Based on MED for Cognitive Radio [J]. Journal of Jishou University（Natural Sciences Edition), 2018, 39(2): 50-54.
[9]	WANG Hanrui,HUANG Xiaoyu,JIANG Wei,ZHAI Fengyun,LEI Kejun. An Improved Blind Spectrum Sensing Algorithm Based on the Ratio of Eigenvalues of the Sample Covariance Matrix [J]. Journal of Jishou University（Natural Sciences Edition), 2017, 38(6): 40-44.
[10]	DENG Yu，ZHANG Jun，YIN Jie，YANG Xi. Broadband Spectrum Sensing Algorithm Based on the Particle Swarm Optimization [J]. Journal of Jishou University（Natural Sciences Edition), 2016, 37(3): 47-50.
[11]	ZHAO Can-Hui, ZHU Yan-Bin, LI Ming-Gang. Improved Particle Swarm Optimization Algorithm Based on Transformer Substation Grounding System [J]. journal6, 2016, 37(1): 49-53.
[12]	LEI Shi-Hua, DING Lei, LI Jian-Feng, ZENG Shui-Ling. Improved Intrusion Detection Algorithm Based on DCA [J]. journal6, 2015, 36(6): 27-29.
[13]	LIU Chuan-Qing. A Hybrid Weighted Algorithm of Cooperative Spectrum Sensing in Cognitive Radio Networks [J]. journal6, 2010, 31(5): 50-54.