A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit <a rel="external noopener" href="http://www.ee.ucl.ac.uk/~iandreop/Deligiannis_BODYNETS2014.pdf">the original URL</a>. The file type is <code>application/pdf</code>.
Distributed Joint Source-Channel Coding with Raptor Codes for Correlated Data Gathering in Wireless Sensor Networks
<span title="">2014</span>
<i title="ICST">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hdtexni3n5gtbhjgnktdwprk5y" style="color: black;">Proceedings of the 9th International Conference on Body Area Networks</a>
</i>
Preserved Fulltext
Correlated data gathering in body area networks calls for systems that perform efficient compression and reliable transmission 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
<span class="external-identifiers">
<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4108/icst.bodynets.2014.257111">doi:10.4108/icst.bodynets.2014.257111</a>
<a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/bodynets/DeligiannisZOAM14.html">dblp:conf/bodynets/DeligiannisZOAM14</a>
<a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dnagfdkelbcyrnkgspjmz7fcoy">fatcat:dnagfdkelbcyrnkgspjmz7fcoy</a>
</span>
more »
... ples 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 minimum. 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 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 proposed system leads to energy savings between 12.19% to 16.51% with respect to the baseline system.
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170810075300/http://www.ee.ucl.ac.uk/~iandreop/Deligiannis_BODYNETS2014.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext">
<button class="ui simple right pointing dropdown compact black labeled icon button serp-button">
<i class="icon ia-icon"></i>
Web Archive
[PDF]
<div class="menu fulltext-thumbnail">
<img src="https://blobs.fatcat.wiki/thumbnail/pdf/94/e4/94e47aacba1390cc804de2ff334f63e1712001e1.180px.jpg" alt="fulltext thumbnail" loading="lazy">
</div>
</button>
</a>
<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4108/icst.bodynets.2014.257111">
<button class="ui left aligned compact blue labeled icon button serp-button">
<i class="external alternate icon"></i>
Publisher / doi.org
</button>
</a>