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题名:
Optimization spectrum decision parameters in CR using autonomously search algorithm
作者: Li YC(李永程); Shen H(申海); Wang, Manxi
作者部门: 信息服务与智能控制技术研究室
通讯作者: 申海
会议名称: 2016 IEEE 13th International Conference on Signal Processing (ICSP)
会议日期: November 6-10, 2016
会议地点: Chengdu, China
会议录: 2016 IEEE 13th International Conference on Signal Processing (ICSP)
会议录出版者: IEEE
会议录出版地: New York
出版日期: 2016
页码: 1146-1151
收录类别: EI ; CPCI(ISTP)
ISSN号: 2164-5221
ISBN号: 978-1-5090-1344-9
关键词: Cognitive Engine ; Bio-inspired Computing ; Cognitive Radio ; Automously Search Algorithm ; multi-objective optimization problem
摘要: In order to solve the contradiction between wireless communication service demand and spectrum resource shortage and enhance the utilization rate of spectrum, Cognitive Radio technology is necessary. Firstly, this paper presents a cognitive engine framework structure, and then the concept of bio-inspired and its application in CR computing were emphatically introduced. Finally, in order to solve spectrum parameters problem, this paper proposed based on autonomously search algorithm. Based on population evolution, ASA algorithm employs the foraging, reproduction, selection and mutation operators, and was tested under the multicarrier simulation environment. The experiment results show that ASA algorithm can better adjust each subcarrier communication parameters according to the requirement of cognitive engine parameters optimization, which include transmitted power, modulation mode, and bit-error-rate and so on, and finally satisfy the channel condition and the dynamic changes of the user service.
语种: 英语
产权排序: 2
EI收录号: 20171403516592
WOS记录号: WOS:000406056300223
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/20286
Appears in Collections:信息服务与智能控制技术研究室_会议论文

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Recommended Citation:
Li YC,Shen H,Wang, Manxi. Optimization spectrum decision parameters in CR using autonomously search algorithm[C]. 2016 IEEE 13th International Conference on Signal Processing (ICSP). Chengdu, China. November 6-10, 2016.Optimization spectrum decision parameters in CR using autonomously search algorithm.
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