Novel Maximum-based Timing Acquisition for Spread-Spectrum Communications
Abstract
This paper proposes and analyzes a new packet detection and timing acquisition method for spread spectrum systems. The proposed method provides an enhancement over the typical thresholding techniques that have been proposed for direct sequence spread spectrum (DS-SS). The effective implementation of thresholding methods typically require accurate knowledge of the received signal-to-noise ratio (SNR), which is particularly difficult to estimate in spread spectrum systems. Instead, we propose a method which utilizes a consistency metric of the location of maximum samples at the output of a filter matched to the spread spectrum waveform to achieve acquisition, and does not require knowledge of the received SNR. Through theoretical study, we show that the proposed method offers a low probability of missed detection over a large range of SNR with a corresponding probability of false alarm far lower than other methods. Computer simulations that corroborate our theoretical results are also presented. Although our work here has been motivated by our previous study of a filter bank multicarrier spread-spectrum (FB-MC-SS) system, the proposed method is applicable to DS-SS systems as well.
- Authors:
- Publication Date:
- Research Org.:
- Idaho National Lab. (INL), Idaho Falls, ID (United States)
- Sponsoring Org.:
- USDOE Office of Nuclear Energy (NE)
- OSTI Identifier:
- 1358404
- Report Number(s):
- INL/CON-16-40152
- DOE Contract Number:
- DE-AC07-05ID14517
- Resource Type:
- Conference
- Resource Relation:
- Conference: Globecom, Washington D.C., December 4–8, 2016
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 99 GENERAL AND MISCELLANEOUS; DS-SS; FB-MC-SS; LTE; OFDM; PSD; SNR
Citation Formats
Sibbetty, Taylor, Moradiz, Hussein, and Farhang-Boroujeny, Behrouz. Novel Maximum-based Timing Acquisition for Spread-Spectrum Communications. United States: N. p., 2016.
Web. doi:10.1109/GLOCOMW.2016.7848972.
Sibbetty, Taylor, Moradiz, Hussein, & Farhang-Boroujeny, Behrouz. Novel Maximum-based Timing Acquisition for Spread-Spectrum Communications. United States. https://doi.org/10.1109/GLOCOMW.2016.7848972
Sibbetty, Taylor, Moradiz, Hussein, and Farhang-Boroujeny, Behrouz. 2016.
"Novel Maximum-based Timing Acquisition for Spread-Spectrum Communications". United States. https://doi.org/10.1109/GLOCOMW.2016.7848972. https://www.osti.gov/servlets/purl/1358404.
@article{osti_1358404,
title = {Novel Maximum-based Timing Acquisition for Spread-Spectrum Communications},
author = {Sibbetty, Taylor and Moradiz, Hussein and Farhang-Boroujeny, Behrouz},
abstractNote = {This paper proposes and analyzes a new packet detection and timing acquisition method for spread spectrum systems. The proposed method provides an enhancement over the typical thresholding techniques that have been proposed for direct sequence spread spectrum (DS-SS). The effective implementation of thresholding methods typically require accurate knowledge of the received signal-to-noise ratio (SNR), which is particularly difficult to estimate in spread spectrum systems. Instead, we propose a method which utilizes a consistency metric of the location of maximum samples at the output of a filter matched to the spread spectrum waveform to achieve acquisition, and does not require knowledge of the received SNR. Through theoretical study, we show that the proposed method offers a low probability of missed detection over a large range of SNR with a corresponding probability of false alarm far lower than other methods. Computer simulations that corroborate our theoretical results are also presented. Although our work here has been motivated by our previous study of a filter bank multicarrier spread-spectrum (FB-MC-SS) system, the proposed method is applicable to DS-SS systems as well.},
doi = {10.1109/GLOCOMW.2016.7848972},
url = {https://www.osti.gov/biblio/1358404},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Dec 01 00:00:00 EST 2016},
month = {Thu Dec 01 00:00:00 EST 2016}
}