caa a22 4500 605469539 CHVBK 20210128100323.0 cr unu---uuuuu 210128e20150301xx s 000 0 eng 10.1007/s00500-014-1280-2 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1280-2 Cooperative spectrum sensing based on an efficient adaptive artificial bee colony algorithm [Elektronische Daten] [Xinbin Li, Lu Lu, Lei Liu, Guoqiang Li, Xinping Guan] In this paper, we present an efficient adaptive artificial bee colony (EA-ABC) algorithm that includes an adaptive mutation mechanism, guaranteed convergence mechanism and optimal tracking mechanism. The EA-ABC algorithm is applied to cooperative spectrum sensing for a cognitive radio field. An efficient sensing scheme can reduce the false alarm probability and enhance the detection probability, which can improve spectrum utilization. Simulations are conducted to compare the performance of the proposed cooperative spectrum sensing method based on the EA-ABC algorithm with that of the cooperative spectrum sensing method using the ABC, particle swarm optimization (PSO), and modified PSO algorithms. The simulation results validate the effectiveness and reliability of the proposed method and demonstrate that EA-ABC-based can achieve higher detection probability than other methods under the same false alarm probability. Springer-Verlag Berlin Heidelberg, 2014 Artificial bee colony nationallicence Adaptive nationallicence Cooperative spectrum sensing nationallicence Cognitive radio nationallicence Li Xinbin Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Hebei, China aut Lu Lu Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Hebei, China aut Liu Lei Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Hebei, China aut Li Guoqiang Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Hebei, China aut Guan Xinping Institute of Automation, Shanghai Jiaotong University, 200030, Shanghai, China aut Soft Computing Springer Berlin Heidelberg 19/3(2015-03-01), 597-607 1432-7643 19:3<597 2015 19 500 https://doi.org/10.1007/s00500-014-1280-2 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1280-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Li Xinbin Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Hebei, China aut NATIONALLICENCE 700 1- Lu Lu Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Hebei, China aut NATIONALLICENCE 700 1- Liu Lei Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Hebei, China aut NATIONALLICENCE 700 1- Li Guoqiang Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Hebei, China aut NATIONALLICENCE 700 1- Guan Xinping Institute of Automation, Shanghai Jiaotong University, 200030, Shanghai, China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/3(2015-03-01), 597-607 1432-7643 19:3<597 2015 19 500