Correlated data gathering in body area networks calls for systems that perform efficient compression and reliable trans- mission of the measurements, while imposing a small computational burden at the sensors. Highly-efficient compression mechanisms, e.g., adaptive arithmetic entropy encoding, do not address the problem adequately, as they have high computational demands. In this paper, we propose a new distributed joint source-channel coding (DJSCC) solution for this problem. Following the principles of distributed source coding, our design allows for efficient compression and error-resilient transmission while exploiting the correlation amongst sensors' readings at energy-robust sink nodes. In this way, the computational complexity and in turn, the energy consumption at the sensor node is kept to a mini- mum. Our DJSCC design is based on a new non-systematic Slepian-Wolf Raptor code construction that achieves good performance at short code lengths, which are appropriate for low-rate data gathering within local or body area sensor networks. Experimental results using a Wireless Sensor Network (WSN) deployment for temperature monitoring reveal that, for lossless compression, the proposed system leads to a 30.08% rate reduction against a baseline system that performs adaptive arithmetic entropy encoding of the temperature readings. Moreover, under AWGN and Rayleigh fading channel losses, the pro- posed system leads to energy savings between 12.19% to 16.51% with respect to the baseline system.
Deligiannis, N, Zimos, E, Ofrim, DM, Andreopoulos, Y & Munteanu, A 2014, Distributed Joint Source-Channel Coding with Raptor Codes for Correlated Data Gathering in Wireless Sensor Networks. in Proceedings of the 9th International Conference on Body Area Networks. pp. 279-285, 9th International Conference on Body Area Networks, London, United Kingdom, 29/09/14.
Deligiannis, N., Zimos, E., Ofrim, D. M., Andreopoulos, Y., & Munteanu, A. (2014). Distributed Joint Source-Channel Coding with Raptor Codes for Correlated Data Gathering in Wireless Sensor Networks. In Proceedings of the 9th International Conference on Body Area Networks (pp. 279-285)
@inproceedings{a91448eb31834a5f821f738b9d9c3dad,
title = "Distributed Joint Source-Channel Coding with Raptor Codes for Correlated Data Gathering in Wireless Sensor Networks",
abstract = "Correlated data gathering in body area networks calls for systems that perform efficient compression and reliable trans- mission of the measurements, while imposing a small computational burden at the sensors. Highly-efficient compression mechanisms, e.g., adaptive arithmetic entropy encoding, do not address the problem adequately, as they have high computational demands. In this paper, we propose a new distributed joint source-channel coding (DJSCC) solution for this problem. Following the principles of distributed source coding, our design allows for efficient compression and error-resilient transmission while exploiting the correlation amongst sensors' readings at energy-robust sink nodes. In this way, the computational complexity and in turn, the energy consumption at the sensor node is kept to a mini- mum. Our DJSCC design is based on a new non-systematic Slepian-Wolf Raptor code construction that achieves good performance at short code lengths, which are appropriate for low-rate data gathering within local or body area sensor networks. Experimental results using a Wireless Sensor Network (WSN) deployment for temperature monitoring reveal that, for lossless compression, the proposed system leads to a 30.08% rate reduction against a baseline system that performs adaptive arithmetic entropy encoding of the temperature readings. Moreover, under AWGN and Rayleigh fading channel losses, the pro- posed system leads to energy savings between 12.19% to 16.51% with respect to the baseline system.",
keywords = "Wireless sensor networks (WSNs), Distributed joint source-channel coding (DJSCC), Raptor Codes,, Temperature monitoring",
author = "Nikos Deligiannis and Evangelos Zimos and Ofrim, {Dragos Mihai} and Yiannis Andreopoulos and Adrian Munteanu",
year = "2014",
month = oct,
day = "29",
language = "English",
pages = "279--285",
booktitle = "Proceedings of the 9th International Conference on Body Area Networks",
note = "9th International Conference on Body Area Networks ; Conference date: 29-09-2014 Through 01-10-2014",
}