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
