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

Kuo Ching Fu, Yung Fang Chen

研究成果: 雜誌貢獻期刊論文同行評審

1 引文 斯高帕斯(Scopus)

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.

原文???core.languages.en_GB???
頁(從 - 到)303-318
頁數16
期刊Wireless Personal Communications
89
發行號2
DOIs
出版狀態已出版 - 1 7月 2016

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