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基于SDR和改进能量检测算法的频谱感知 被引量:3

Spectrum Sensing Based on SDR and Improved Energy Detection Algorithm
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摘要 针对人为性的电磁频谱资源匮乏问题,搭建一套通用软件定义无线电(SDR)系统作为通信平台,并提出一种改进的双阈值能量检测算法。该算法通过在混淆区域内添加额外阈值,细化判决结果后进行融合判决,减少了传统算法造成的传感信息浪费,降低真实信道下的噪声影响。在SDR系统中对授权用户频段使用情况进行实时检测,实现了频谱感知并为次用户的频谱接入提供依据。实验结果表明,相比于单阈值能量检测和传统双阈值能量检测算法,该算法在低信噪比情况下具有更高的检测概率。 To address the man-made shortage of electromagnetic spectrum resources,a general Software Defined Radio(SDR)system is established as a communication platform,and an improved dual threshold energy detection algorithm is proposed.The algorithm adds additional thresholds into the confusion region in order to refine the decision result,and then performs the fusion decision,which reduces the waste of sensor information caused by the traditional algorithm and reduces the noise impact under the real channel.In the SDR system,real time detection of the frequency band usage of authorized users is carried out,which realizes spectrum sensing and provides a basis for the spectrum access of the secondary user.Experimental results show that compared with the single threshold energy detection and the traditional double threshold energy detection method,the proposed algorithm has a higher detection probability in cases of a low Signal-to-Noise Ratio(SNR).
作者 冉超 方志军 张彦宇 RAN Chao;FANG Zhijun;ZHANG Yanyu(School of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201620,China)
出处 《计算机工程》 CAS CSCD 北大核心 2020年第9期198-204,共7页 Computer Engineering
基金 国家自然科学基金(61831018,61772328)。
关键词 软件定义无线电 认知无线电 频谱感知 能量检测 双阈值 Software Defined Radio(SDR) cognitive radio spectrum sensing energy detection double threshold
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  • 1王翔.无线通信技术发展分析[J].通信技术,2007,40(6):60-62. 被引量:21
  • 2赵知劲,郑仕链,尚俊娜.认知无线电技术[M].北京:科学出版社,2008.
  • 3Peng Chunyi, Zheng Haitao, Zhao B Y. Utilization and Fairness in Spectrum Assignment for Opportunistic Spectrum Access[J]. ACM Mobile Networks and Applications, 2006, 11 (4): 555-576.
  • 4Rahimi-Vahed A, Mirzaei A H. Solving a Bi-criteria Permutation Flow-shop Problem Using Shuffled Frog-leaping Algorithm[J]. Soft Computing, 2008, 12(5): 435-452.
  • 5Eusuff M, Lansey K, Pasha E Shuffled Frog-leaping Algorithm: A Memetic Meta-heuristic for Discrete Optimization[J]. Engineering Optimization, 2006, 38(2): 129-154.
  • 6王庭昌.软件无线电技术的回顾与展望[J].现代军事通信,2007,15(3):1-7.
  • 7MITOLA J,GERALD Q,MAGUIRE JR.Cognitive Radios:Making Software Radios More Personal[J].IEEE Personal Communications.1999,6(04):13-18.
  • 8栗苹,赵国庆,杨小牛等.信息对抗技术[M].北京:清华大学出版社,2007.
  • 9SOROUCHYARI E. Blind Separation of Sources[J]. Signal Processing, 1991, 24(1): 21-29.
  • 10杨小牛,楼才义,徐建良.软件无线电原理与应用[M].北京:电子工业出版社,2005.

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