English

Explicit Information-Debt-Optimal Streaming Codes With Small Memory

Information Theory 2023-05-11 v1 math.IT

Abstract

For a convolutional code in the presence of a symbol erasure channel, the information debt I(t)I(t) at time tt provides a measure of the number of additional code symbols required to recover all message symbols up to time tt. Information-debt-optimal streaming (iiDOS) codes are convolutional codes which allow for the recovery of all message symbols up to tt whenever I(t)I(t) turns zero under the following conditions; (i) information debt can be non-zero for at most τ\tau consecutive time slots and (ii) information debt never increases beyond a particular threshold. The existence of periodically-time-varying iiDOS codes are known for all parameters. In this paper, we address the problem of constructing explicit, time-invariant iiDOS codes. We present an explicit time-invariant construction of iiDOS codes for the unit memory (m=1m=1) case. It is also shown that a construction method for convolutional codes due to Almeida et al. leads to explicit time-invariant iiDOS codes for all parameters. However, this general construction requires a larger field size than the first construction for the m=1m=1 case.

Cite

@article{arxiv.2305.06303,
  title  = {Explicit Information-Debt-Optimal Streaming Codes With Small Memory},
  author = {M. Nikhil Krishnan and Myna Vajha and Vinayak Ramkumar and P. Vijay Kumar},
  journal= {arXiv preprint arXiv:2305.06303},
  year   = {2023}
}

Comments

Accepted to 2023 IEEE International Symposium on Information Theory (ISIT)

R2 v1 2026-06-28T10:31:18.657Z