Subspace-Based Algorithms for Blind ML Frequency and Transition Time Estimation in Frequency Hopping Systems

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题名:	Subspace-Based Algorithms for Blind ML Frequency and Transition Time Estimation in Frequency Hopping Systems
作者:	陳永芳;Fu, Kuo-Ching;Chen, Yung-Fang
贡献者:	資訊電機學院通訊工程學系
关键词:	Communications Engineering;Computer Communication Networks;Engineering;Networks;Signal,Image and Speech Processing
日期:	2016-07-01
上传时间:	2026-04-23 13:09:14 (UTC+8)
出版者:	Springer Netherlands;New York: Springer US
摘要:	摘要： Frequency hopping spread spectrum (FHSS) is a technology for combating narrow band interference. Two parameters required for estimation in FHSS are transition time and hopping frequency. In this paper, blind subspace-based schemes with a maximum likelihood (ML) criterion for estimating frequency and transition time without using reference signals are proposed. The selection of the related parameters is discussed. Subspace-based algorithms are applied with the help of the proposed block selection scheme. The performance is improved with a block selection algorithm to overcome the unbalanced processing block problems in various algorithms. The proposed method significantly reduces computational complexity compared with a greedy search ML-based algorithm. The performance is shown to outperform an existing iterative ML-based algorithm with a comparable complexity. 其他題名： Wireless Pers Commun 出版者： New York: Springer US 出版日期： 2016-07-01 出處： Wireless personal communications, 2016-07, Vol.89 (2), p.303-318 版權： Springer Science+Business Media New York 2016 識別號： ISSN: 0929-6212 識別號： EISSN: 1572-834X 識別號： DOI: 10.1007/s11277-016-3364-z
显示于类别:	[通訊工程學系] 期刊論文

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