NDLI: Parameter estimation of frequency hopping signal based on MWC

Content Provider	IET Digital Library
Author	Yixuan, Guo Zhi, Li Jian, Li Jianhua, Zhou
Abstract	Aiming at the problem that single-network hopping signals have not fully utilised its frequency domain sparse characteristic in the parameter estimation, this study proposes a parameter estimation of frequency hopping (FH) signal based on multi-measurement vector sparse Bayesian learning (MSBL) in modulation wideband converter (MWC). Since the FH signal is sparse in the frequency domain, the authors apply the MSBL method to estimate its parameters. After the signal is sampled by the MWC, the MSBL algorithm is used to reconstruct its support set. Then the time–frequency ridge method is used to estimate the signal's hop duration, time-hopping, and carrier frequency based on the time–frequency map. Simulation experiments show that under the condition of low signal-to-noise ratio, the parameter estimation performance in the case can be improved by up to 65% and anti-noise performance can be improved up to 6 db compared with the existing method. The result is very close to the Nyquist full sampling and can greatly improve the accuracy of the FH signal parameter estimation in the MWC system and relieve the pressure of the hardware.
Starting Page	1642
Ending Page	1649
Page Count	8
ISSN	17518628
Volume Number	14
e-ISSN	17518636
Issue Number	Issue 10, Jun (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/14/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2019.0987
Journal	IET Communications
Publisher Date	2020-03-17
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Antinoise Performance Improvement Bayes Method Carrier Frequency Estimation Digital Signal Processing FH Signal Parameter Estimation Frequency Domain Sparse Characteristic Frequency Hop Communication Knowledge Engineering Technique Learning in AI Low Signal-to-noise Ratio Mathematical Analysis Modulation Modulation And Coding Method Modulation Wideband Converter MSBL Algorithm MSBL Method Multimeasurement Vector Sparse Bayesian Learning MWC System MWC-MSBL Reconstruction Nyquist Full Sampling Parameter Estimation Parameter Estimation Performance Radio Link And Equipment Signal Hop Duration Estimation Signal Processing And Detection Signal Reconstruction Signal Sampling Single-network Hopping Signal Statistics Time-frequency Analysis Time-frequency Map Time-frequency Ridge Method Time-hopping Estimation
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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