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美国Prairie View A&M University王永会副教授来访

      应谢磊教授邀请,美国Prairie View A&M University王永会副教授于2013年9月29日至30日对西北工业大学计算机学院和陕西省语音与图像处理重点实验室进行了学术访问。王永会博士长期从事图像与信号处理、数据编码以及小波的研究工作。9月30日下午14:00分,王永会教授在计算机学院105报告厅做了题目为“Spectrum Situation Recovery in Cognitive Radio Networks with Image Processing Algorithm”的学术报告。报告会由计算机学院谢磊教授主持,包括蒋冬梅教授在内的师生50余人参加了报告会。报告会后,王永会教授与师生展开了讨论,现场气氛热烈。王永会教授访问期间,参观了陕西省语音与图像信息处理重点实验室在语音与音频处理、图像与视频处理等方面的研究成果,并同谢磊教授、蒋冬梅教授进行了深入讨论。

      目报告题目:Spectrum Situation Recovery in Cognitive Radio Networks with Image Processing Algorithm

      报告人简介:Dr. Yonghui Wang received the B.S. degree in technical physics from Xidian University, Xi’an, China, in 1993, the M.S. degree in electrical engineering from Beijing Polytechnic University, Beijing, China, in 1999, and the Ph.D. degree in computer engineering from Mississippi State University, Starkville, MS, in 2003. From 1993 to 1996, he was an Engineer with the 41st Electrical Research Institute, Bengbu, China. From July 1999 to December 1999, he worked as an IT Specialist in IBM China, Beijing, China. From 2000 to 2003, he was a research assistant with the Visualization, Analysis, and Imaging Laboratory (VAIL), the GeoResources Institute (GRI), Mississippi State University. He is currently an Associate Professor with the Department of Engineering Technology, Prairie View A&M University, Prairie View, TX. His research interests include image and signal processing, data coding, and wavelets.

      报告摘要: The introduction of cognitive radio (CR) shifts the paradigm of spectrum management from command and control to dynamic spectrum access for the CR users or secondary users, and thus improves the spectrum utilization. In order to fulfill this transition, spectrum awareness is a must and spectrum sensing plays a pivotal role in achieving such awareness. In this talk, we want to introduce an application of image inpainting algorithm for spectrum awareness in wireless network communication. Specifically, the problem of spectrum situation reconstruction is considered for large CR ad hoc networks. Spectrum sensing and spectrum decision are critical for CR network throughput and hence obtaining accurate knowledge of the spectrum situation is vitally important to better spectrum usage decisions. The major challenge of this type of problem lies in the fact that for a network covering a large geographical area, only very limited measurements of spectrum occupancy during spectrum sensing may be obtained by the CR users for a certain location in any given time slot. This is due to both the hardware limitations as well as the tradeoff between spectrum sensing time and data throughput of the CR users. By representing the spectrum sensing results across the network as an image, spectrum situation reconstruction as an image recovery problem is formulated. The method of total variation inpainting is applied to solve the problem with low recovery error. The proposed method takes advantage of the correlations in multiple dimensions and the numerical results demonstrate the effectiveness of the proposed scheme.

     

 

 

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