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Time-Variant Decoding of Convolutional Network Codes
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DOI：10.1109/LCOMM.2012.080312.120789.png)
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Abstract
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In this paper, a time-variant decoding model of a convolutional network code (CNC) is proposed. New necessary and sufficient conditions are established for the decodability of a CNC at a node r with delay L. They only involve the first L + 1 terms in the power series expansion of the global encoding kernel matrix at r. Concomitantly, a time-variant decoding algorithm is proposed with a decoding matrix over the base symbol field. The present time-variant decoding model only deals with partial information of the global encoding kernel matrix, and hence potentially makes CNCs applicable in a decentralized manner.
Keywords:
Network coding
time-variant decoding
convolutional network coding
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