NDLI: Joint channel estimation and detection using Markov chain Monte Carlo method over sparse underwater acoustic channels

Content Provider	IET Digital Library
Author	Jing, Lianyou He, Chengbing Huang, Jianguo Ding, Zhi
Abstract	This study proposes a novel approach to joint channel estimation and detection of orthogonal frequency division multiplexing transmission over underwater acoustic (UWA) multipath channels exhibiting cluster sparsity. Unlike most sparse channel estimations, the authors exploit the cluster-sparsity characteristic of UWA channels without additional prior information. They adopt a modified spike-and-slab prior model in their non-parametric Bayesian learning framework. To avoid the need for a closed-form Bayesian estimate, they apply the Markov chain Monte Carlo technique to joint achieve channel estimation and signal detection. The proposed solution is amenable to being integrated with soft-input soft-output decoding to improve the performance through turbo iteration. Simulation results demonstrate improved bit error rate of the proposed algorithm over existing algorithms.
Starting Page	1789
Ending Page	1796
Page Count	8
ISSN	17518628
Volume Number	11
e-ISSN	17518636
Issue Number	Issue 11, Aug (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/11/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2016.1339
Journal	IET Communications
Publisher Date	2017-05-12
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Acoustic And Other Telecommunication System And Equipment Bayes Method Bit Error Rate Channel Estimation Closed-form Bayesian Estimation Cluster Sparsity Code Communication Channel Equalisation And Identification Error Statistics Interpolation And Function Approximation Iterative Method Joint Channel Estimation And Signal Detection Approach Markov Chain Monte Carlo Method Markov Processes Modified Spike-and-slab Prior Model Monte Carlo Method Multipath Channel Nonparametric Bayesian Learning Framework Numerical Analysis OFDM Modulation Orthogonal Frequency Division Multiplexing Transmission Signal Detection Soft-input Soft-output Decoding Sparse Channel Estimation Sparse Underwater Acoustic Channel Turbo Code Turbo Iteration Underwater Acoustic Communication UWA Multipath Channel Wireless Channel
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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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