The University of Southampton
University of Southampton Institutional Repository

LDPC coded compressive sensing for joint source-channel coding in wireless sensor networks

LDPC coded compressive sensing for joint source-channel coding in wireless sensor networks
LDPC coded compressive sensing for joint source-channel coding in wireless sensor networks
The novel concept of joint Compressive Sensing (CS) and Low Density Parity Check (LDPC) coding is conceived for Joint Source-Channel Coding (JSCC) in Wireless Sensor Networks (WSNs) supporting a massive number of signals. More explicitly, we demonstrate this concept for a specific scheme, which supports a massive number of signals simultaneously, using a small number of Internet of Things Nodes (IoTNs) based on the concept of CS. The compressed signals are LDPC coded in order to protect them from poor transmission channels. We also propose the new iterative joint source-channel decoding philosophy for exchanging soft extrinsic information, which combines CS decoding and LDPC decoding by merging their respective factor graphs. We then characterize this scheme using Extrinsic Information Transfer (EXIT) chart analysis. Our BLock Error Rate (BLER) results show that the proposed iterative joint LDPC-CS decoding scheme attains about 1.5 dB gain at a BLER of 10−3 compared to a benchmarker, which employs separate CS and LDPC decoding. Naturally, this gain is achieved at the cost of approximately doubling the complexity of the proposed iterative joint LDPC-CS decoding scheme.
0018-9545
Chen, Jue
14b8e7c8-7f5e-4e68-a250-fd0989e1567b
Shao, Shuai
59ba0bf5-d953-4967-8655-4de394007f2a
Wang, Tsang Yi
7f1c0642-9107-4096-b255-799aff0b3176
Wu, Jwo Yuh
1c95bdaf-16e4-4c34-85b7-2df0eb2a1c0e
Li, Chih Peng
aa5cdbec-f67a-41c7-8b87-037db1ae69e3
Ng, Soon Xin
e19a63b0-0f12-4591-ab5f-554820d5f78c
Maunder, Rob
76099323-7d58-4732-a98f-22a662ccba6c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Chen, Jue
14b8e7c8-7f5e-4e68-a250-fd0989e1567b
Shao, Shuai
59ba0bf5-d953-4967-8655-4de394007f2a
Wang, Tsang Yi
7f1c0642-9107-4096-b255-799aff0b3176
Wu, Jwo Yuh
1c95bdaf-16e4-4c34-85b7-2df0eb2a1c0e
Li, Chih Peng
aa5cdbec-f67a-41c7-8b87-037db1ae69e3
Ng, Soon Xin
e19a63b0-0f12-4591-ab5f-554820d5f78c
Maunder, Rob
76099323-7d58-4732-a98f-22a662ccba6c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Chen, Jue, Shao, Shuai, Wang, Tsang Yi, Wu, Jwo Yuh, Li, Chih Peng, Ng, Soon Xin, Maunder, Rob and Hanzo, Lajos (2022) LDPC coded compressive sensing for joint source-channel coding in wireless sensor networks. IEEE Transactions on Vehicular Technology. (doi:10.1109/TVT.2022.3212025). (In Press)

Record type: Article

Abstract

The novel concept of joint Compressive Sensing (CS) and Low Density Parity Check (LDPC) coding is conceived for Joint Source-Channel Coding (JSCC) in Wireless Sensor Networks (WSNs) supporting a massive number of signals. More explicitly, we demonstrate this concept for a specific scheme, which supports a massive number of signals simultaneously, using a small number of Internet of Things Nodes (IoTNs) based on the concept of CS. The compressed signals are LDPC coded in order to protect them from poor transmission channels. We also propose the new iterative joint source-channel decoding philosophy for exchanging soft extrinsic information, which combines CS decoding and LDPC decoding by merging their respective factor graphs. We then characterize this scheme using Extrinsic Information Transfer (EXIT) chart analysis. Our BLock Error Rate (BLER) results show that the proposed iterative joint LDPC-CS decoding scheme attains about 1.5 dB gain at a BLER of 10−3 compared to a benchmarker, which employs separate CS and LDPC decoding. Naturally, this gain is achieved at the cost of approximately doubling the complexity of the proposed iterative joint LDPC-CS decoding scheme.

Text
paper_finalversion - Accepted Manuscript
Download (2MB)
Text
LDPC_Coded_Compressive_Sensing_for_Joint_Source-Channel_Coding_in_Wireless_Sensor_Networks (1) - Version of Record
Restricted to Repository staff only
Request a copy

More information

Accepted/In Press date: 2 October 2022

Identifiers

Local EPrints ID: 470976
URI: http://eprints.soton.ac.uk/id/eprint/470976
ISSN: 0018-9545
PURE UUID: 83b1f1af-9711-47de-9b70-88036fe7cd10
ORCID for Shuai Shao: ORCID iD orcid.org/0000-0003-4135-7973
ORCID for Soon Xin Ng: ORCID iD orcid.org/0000-0002-0930-7194
ORCID for Rob Maunder: ORCID iD orcid.org/0000-0002-7944-2615
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 21 Oct 2022 16:41
Last modified: 22 Oct 2022 01:40

Export record

Altmetrics

Contributors

Author: Jue Chen
Author: Shuai Shao ORCID iD
Author: Tsang Yi Wang
Author: Jwo Yuh Wu
Author: Chih Peng Li
Author: Soon Xin Ng ORCID iD
Author: Rob Maunder ORCID iD
Author: Lajos Hanzo ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×