An anti-jamming framework of spread spectrum communications with ICA
Paper
8 June 2012 An anti-jamming framework of spread spectrum communications with ICA
Miao Yu, Mingyue Wang, Shengyong Guan
Author Affiliations +
Proceedings Volume 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012); 833446 (2012) https://doi.org/10.1117/12.968570
Event: Fourth International Conference on Digital Image Processing (ICDIP 2012), 2012, Kuala Lumpur, Malaysia
Abstract
When jamming signal is strong enough, the performance of spread spectrum (SS) communications will decline quickly. According to the independence between the SS signal and the jamming signal in baseband, a novel anti-jamming framework of SS communication with independent component analysis (ICA) is proposed in this paper. This anti-jamming framework utilizes the particular structure of SS communications to reduce the degree of the received mixed signals. Because of the advantage of ICA, no prior knowledge of the jamming signal is needed any more, so the operations such as detection and parameter estimation of the jamming signal can be saved. The proposed anti-jamming framework deals with common jamming signals in a unifying framework, which needs not to switch among several anti-jamming techniques corresponding to different type of the jamming. The validity of the proposed method is proved by numerical simulation results at last.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Miao Yu, Mingyue Wang, and Shengyong Guan "An anti-jamming framework of spread spectrum communications with ICA", Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 833446 (8 June 2012); https://doi.org/10.1117/12.968570
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Independent component analysis

Telecommunications

Interference (communication)

Monte Carlo methods

Receivers

Signal detection

Signal processing

Back to Top