Wireless sensor networks (WSNs) deployed for temperature monitoring in indoor environments call for systems that perform efficient compression and reliable transmission of the measurements. This is known to be a challenging problem in such deployments, as highly efficient compression mechanisms impose a high computational cost at the encoder. In this paper, we propose a new distributed joint source-channel coding (DJSCC) solution for this problem. Our design allows for efficient compression and error-resilient transmission, with low computational complexity at the sensor. A new Slepian–Wolf code construction, based on non-systematic Raptor codes, is devised that achieves good performance at short code lengths, which are appropriate for temperature monitoring applications. A key contribution of this paper is a novel Copula-function-based modeling approach that accurately expresses the correlation amongst the temperature readings from colocated sensors. Experimental results using a WSN deployment reveal that, for lossless compression, the proposed Copula-function-based model leads to a notable encoding rate reduction (of up to 17.56%) compared with the state-of-the-art model in the literature. Using the proposed model, our DJSCC system achieves significant rate savings (up to 41.81%) against a baseline system that performs arithmetic entropy encoding of the measurements. Moreover, under channel losses, the transmission rate reduction against the state-of-the-art model reaches 19.64%, which leads to energy savings between 18.68% to 24.36% with respect to the baseline system.
Deligiannis, N, Zimos, E, Ofrim, DM, Andreopoulos, Y & Munteanu, A 2015, 'Distributed Joint Source-Channel Coding With Copula-Function-Based Correlation Modeling for Wireless Sensors Measuring Temperature', IEEE Sensors Journal, vol. 15, no. 8, pp. 4496-4507. https://doi.org/10.1109/JSEN.2015.2421821
Deligiannis, N., Zimos, E., Ofrim, D. M., Andreopoulos, Y., & Munteanu, A. (2015). Distributed Joint Source-Channel Coding With Copula-Function-Based Correlation Modeling for Wireless Sensors Measuring Temperature. IEEE Sensors Journal, 15(8), 4496-4507. https://doi.org/10.1109/JSEN.2015.2421821
@article{37bdf39801754630aa0ed78452e3c49a,
title = "Distributed Joint Source-Channel Coding With Copula-Function-Based Correlation Modeling for Wireless Sensors Measuring Temperature",
abstract = "Wireless sensor networks (WSNs) deployed for temperature monitoring in indoor environments call for systems that perform efficient compression and reliable transmission of the measurements. This is known to be a challenging problem in such deployments, as highly efficient compression mechanisms impose a high computational cost at the encoder. In this paper, we propose a new distributed joint source-channel coding (DJSCC) solution for this problem. Our design allows for efficient compression and error-resilient transmission, with low computational complexity at the sensor. A new Slepian–Wolf code construction, based on non-systematic Raptor codes, is devised that achieves good performance at short code lengths, which are appropriate for temperature monitoring applications. A key contribution of this paper is a novel Copula-function-based modeling approach that accurately expresses the correlation amongst the temperature readings from colocated sensors. Experimental results using a WSN deployment reveal that, for lossless compression, the proposed Copula-function-based model leads to a notable encoding rate reduction (of up to 17.56%) compared with the state-of-the-art model in the literature. Using the proposed model, our DJSCC system achieves significant rate savings (up to 41.81%) against a baseline system that performs arithmetic entropy encoding of the measurements. Moreover, under channel losses, the transmission rate reduction against the state-of-the-art model reaches 19.64%, which leads to energy savings between 18.68% to 24.36% with respect to the baseline system.",
keywords = "Wireless sensor networks, distributed joint source-channel coding, correlation modeling, copula function, temperature monitoring",
author = "Nikolaos Deligiannis and Evangelos Zimos and Ofrim, {Dragos Mihai} and Yiannis Andreopoulos and Adrian Munteanu",
year = "2015",
month = aug,
doi = "10.1109/JSEN.2015.2421821",
language = "English",
volume = "15",
pages = "4496--4507",
journal = "IEEE Sensors Journal",
issn = "1530-437X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "8",
}