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A signal detection scheme for wireless sensor networks based on convex optimization

  • Beihang University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

Identifying and detecting the unknown abnormal sparse signal has become an important issue for distributed networks. In this paper, we proposed a new detection scheme based on convex optimization for wireless sensor networks. Under the Neyman-Pearson testing framework, the detection scheme first estimates the unknown signal by employing the convex optimization at the fusion center. Then the sensor nodes transmit sufficient statistics rather than raw data to the fusion center. It is verified that the proposed distributed detection scheme has performance in close proximity to ideal detector with less than one third of communication overhead compared with the centralized scheme.

源语言英语
主期刊名IEEE Sensors, SENSORS 2016 - Proceedings
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9781479982875
DOI
出版状态已出版 - 5 1月 2016
活动15th IEEE Sensors Conference, SENSORS 2016 - Orlando, 美国
期限: 30 10月 2016 → 2 11月 2016

丛书

姓名Proceedings of IEEE Sensors
卷0
ISSN(印刷版)1930-0395
ISSN(电子版)2168-9229

会议

会议15th IEEE Sensors Conference, SENSORS 2016
国家/地区美国
市Orlando
时期30/10/16 → 2/11/16

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