Convolutional Codes with Maximum Column Sum Rank for Network Streaming

Rafid Mahmood; Ahmed Badr; Ashish Khisti

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arXiv · 1506.03792

Convolutional Codes with Maximum Column Sum Rank for Network Streaming

Rafid Mahmood·Ahmed Badr·Ashish Khisti

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Abstract

The column Hamming distance of a convolutional code determines the error correction capability when streaming over a class of packet erasure channels. We introduce a metric known as the column sum rank, that parallels column Hamming distance when streaming over a network with link failures. We prove rank analogues of several known column Hamming distance properties and introduce a new family of convolutional codes that maximize the column sum rank up to the code memory. Our construction involves finding a class of super-regular matrices that preserve this property after multiplication with non-singular block diagonal matrices in the ground field.

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Rafid Mahmood, Ahmed Badr, Ashish Khisti. 2015-06-11. Convolutional Codes with Maximum Column Sum Rank for Network Streaming. https://arxiv.org/abs/1506.03792

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