Blind despreading and deconvolution of asynchronous multiuser direct sequence spread spectrum signals under multipath channels
Abstract In non‐cooperative scenarios, the spreading sequences or waveforms of the direct sequence spread spectrum (DSSS) signals is unknown to the receiver. This paper focuses on addressing the problem of blind estimation of the spreading waveform under multipath channels. In the scenario of direct...
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| Format: | Article |
| Language: | English |
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Wiley
2023-05-01
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| Series: | IET Signal Processing |
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| Online Access: | https://doi.org/10.1049/sil2.12220 |
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| author | Liangliang Li Huaguo Zhang Songmao Du Tao Liang Lin Gao |
| author_facet | Liangliang Li Huaguo Zhang Songmao Du Tao Liang Lin Gao |
| author_sort | Liangliang Li |
| collection | DOAJ |
| description | Abstract In non‐cooperative scenarios, the spreading sequences or waveforms of the direct sequence spread spectrum (DSSS) signals is unknown to the receiver. This paper focuses on addressing the problem of blind estimation of the spreading waveform under multipath channels. In the scenario of direct signal path transmission, the spreading sequences can be directly obtained based on the estimated spreading waveforms. However, in the presence of multipath channels, the spreading waveform becomes the convolution of the spreading sequence and channel response, thus deconvolution should also be performed after estimating the spreading waveforms. In order to perform blind despreading and deconvolution of asynchronous multiuser DSSS signals under multipath channels, the authors propose to exploit the finite symbol characteristics of information and spreading sequences and then the iterative least square with projection method is adopted. Besides, the Cramer‐Rao bound of spreading waveforms is derived in such a circumstance as a performance benchmark. The effectiveness of the proposed method is verified via simulation experiments. |
| format | Article |
| id | doaj-art-63060123a4a64e92a6aec8b3bf3cafaa |
| institution | Kabale University |
| issn | 1751-9675 1751-9683 |
| language | English |
| publishDate | 2023-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Signal Processing |
| spelling | doaj-art-63060123a4a64e92a6aec8b3bf3cafaa2025-02-03T06:47:34ZengWileyIET Signal Processing1751-96751751-96832023-05-01175n/an/a10.1049/sil2.12220Blind despreading and deconvolution of asynchronous multiuser direct sequence spread spectrum signals under multipath channelsLiangliang Li0Huaguo Zhang1Songmao Du2Tao Liang3Lin Gao4School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu ChinaSchool of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu ChinaSchool of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu ChinaSchool of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu ChinaSchool of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu ChinaAbstract In non‐cooperative scenarios, the spreading sequences or waveforms of the direct sequence spread spectrum (DSSS) signals is unknown to the receiver. This paper focuses on addressing the problem of blind estimation of the spreading waveform under multipath channels. In the scenario of direct signal path transmission, the spreading sequences can be directly obtained based on the estimated spreading waveforms. However, in the presence of multipath channels, the spreading waveform becomes the convolution of the spreading sequence and channel response, thus deconvolution should also be performed after estimating the spreading waveforms. In order to perform blind despreading and deconvolution of asynchronous multiuser DSSS signals under multipath channels, the authors propose to exploit the finite symbol characteristics of information and spreading sequences and then the iterative least square with projection method is adopted. Besides, the Cramer‐Rao bound of spreading waveforms is derived in such a circumstance as a performance benchmark. The effectiveness of the proposed method is verified via simulation experiments.https://doi.org/10.1049/sil2.12220blind equalisersblind source separationchannel estimationcode division multiple accessGaussian distributionleast squares approximations |
| spellingShingle | Liangliang Li Huaguo Zhang Songmao Du Tao Liang Lin Gao Blind despreading and deconvolution of asynchronous multiuser direct sequence spread spectrum signals under multipath channels IET Signal Processing blind equalisers blind source separation channel estimation code division multiple access Gaussian distribution least squares approximations |
| title | Blind despreading and deconvolution of asynchronous multiuser direct sequence spread spectrum signals under multipath channels |
| title_full | Blind despreading and deconvolution of asynchronous multiuser direct sequence spread spectrum signals under multipath channels |
| title_fullStr | Blind despreading and deconvolution of asynchronous multiuser direct sequence spread spectrum signals under multipath channels |
| title_full_unstemmed | Blind despreading and deconvolution of asynchronous multiuser direct sequence spread spectrum signals under multipath channels |
| title_short | Blind despreading and deconvolution of asynchronous multiuser direct sequence spread spectrum signals under multipath channels |
| title_sort | blind despreading and deconvolution of asynchronous multiuser direct sequence spread spectrum signals under multipath channels |
| topic | blind equalisers blind source separation channel estimation code division multiple access Gaussian distribution least squares approximations |
| url | https://doi.org/10.1049/sil2.12220 |
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