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基于视频业务质量优化的认知无线电传输信道选择
引用本文:刘金霞,陈莲娜,刘延伟,王遵义,彭光超. 基于视频业务质量优化的认知无线电传输信道选择[J]. 计算机应用, 2015, 35(6): 1527-1530. DOI: 10.11772/j.issn.1001-9081.2015.06.1527
作者姓名:刘金霞  陈莲娜  刘延伟  王遵义  彭光超
作者单位:1. 浙江万里学院 基础学院, 浙江 宁波315100;2. 中国计量学院 信息工程学院, 杭州 310018;3. 中国科学院 声学研究所, 北京 100190
基金项目:国家自然科学基金资助项目,浙江省自然科学基金资助项目,浙江省公益技术研究工业项目,宁波市创新团队项目,浙江省高校访问学者教师专业发展项目
摘    要:认知无线电网络中,次级用户选择信道的传统技术基于信道特性对传输信道进行随机选择,忽略了应用层视频业务对信道质量的要求。针对该问题提出了一种基于视频业务质量优化的信道选择技术,优化视频业务端到端的传输质量。通过最小化端到端视频失真,跨层优化综合选择物理层传输信道、自适应调制与编码模式以及应用层的编码量化参数。该方法在多信道认知无线电网络下进行了大量的视频传输仿真模拟实验。实验结果表明该方法能够比不含信道选择的跨层优化方法提高认知无线电网络下次级用户的视频传输业务客观质量1.5 dB以上。

关 键 词:认知无线电网络  信道选择  跨层优化  视频传输业务  
收稿时间:2014-12-30
修稿时间:2015-03-28

Transmission channel selection of cognitive radio networks based on quality optimization for video streaming
LIU Jinxia,CHEN Lianna,LIU Yanwei,WANG Zunyi,PENG Guangchao. Transmission channel selection of cognitive radio networks based on quality optimization for video streaming[J]. Journal of Computer Applications, 2015, 35(6): 1527-1530. DOI: 10.11772/j.issn.1001-9081.2015.06.1527
Authors:LIU Jinxia  CHEN Lianna  LIU Yanwei  WANG Zunyi  PENG Guangchao
Affiliation:1. Junior College, Zhejiang Wanli University, Ningbo Zhejiang 315100, China;
2. College of Information Engineering, China Jiliang University, Hangzhou Zhejiang 310018, China;
3. Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
Abstract:The conventional channel selection approach in cognitive radio network is random selection of the transmission channel based on the channel characteristics while neglecting the channel quality requirement of the video streaming at the application layer. Aiming at solving this problem, a cross-layer optimized channel selection method targeting on the video streaming quality optimization was presented. Via minimizing the end-to-end video distortion, the video encoding quantization parameter at the application layer and the adaptive modulation and channel coding as well as the specific transmission channel at the physical layer were jointly selected. A large number of video transmission simulation experiments were made for the proposed algorithm over the multi-channel cognitive radio networks. The experimental results show that this kind of cross-layer optimized channel selection approach can efficiently improve the objective quality of second user video streaming more than 1.5 dB over the cross-layer optimization without channel-selection method over cognitive radio networks.
Keywords:cognitive radio network  channel selection  cross-layer optimization  video streaming
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