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.
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1-16
Chen, Jue
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Shao, Shuai
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Wang, Tsang Yi
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Wu, Jwo Yuh
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Li, Chih Peng
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Ng, Soon Xin
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Maunder, Rob
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Hanzo, Lajos
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5 October 2022
Chen, Jue
14b8e7c8-7f5e-4e68-a250-fd0989e1567b
Shao, Shuai
59ba0bf5-d953-4967-8655-4de394007f2a
Wang, Tsang Yi
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Wu, Jwo Yuh
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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).
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.
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LDPC_Coded_Compressive_Sensing_for_Joint_Source-Channel_Coding_in_Wireless_Sensor_Networks (1)
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Accepted/In Press date: 2 October 2022
e-pub ahead of print date: 5 October 2022
Published date: 5 October 2022
Additional Information:
Publisher Copyright:
IEEE
Keywords:
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Identifiers
Local EPrints ID: 470976
URI: http://eprints.soton.ac.uk/id/eprint/470976
ISSN: 0018-9545
PURE UUID: 83b1f1af-9711-47de-9b70-88036fe7cd10
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Date deposited: 21 Oct 2022 16:41
Last modified: 18 Mar 2024 03:09
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Contributors
Author:
Jue Chen
Author:
Shuai Shao
Author:
Tsang Yi Wang
Author:
Jwo Yuh Wu
Author:
Chih Peng Li
Author:
Soon Xin Ng
Author:
Rob Maunder
Author:
Lajos Hanzo
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