Achievable Rates for Channels with Deletions and Insertions
Ramji Venkataramanan, Sekhar Tatikonda, Kannan Ramchandran

TL;DR
This paper derives a computable lower bound on the capacity of a binary channel with deletions and insertions, providing the first achievable rate characterization for such channels and improving bounds for deletion probabilities up to 0.3.
Contribution
It introduces a mutual information decomposition approach to establish the first lower bounds for channels with insertions and deletions, enhancing understanding of their capacity.
Findings
Provides the first achievable rate bounds for channels with insertions and deletions.
Improves existing lower bounds for deletion channels with probabilities up to 0.3.
Offers a new method for analyzing synchronization issues in channels with insertions and deletions.
Abstract
This paper considers a binary channel with deletions and insertions, where each input bit is transformed in one of the following ways: it is deleted with probability d, or an extra bit is added after it with probability i, or it is transmitted unmodified with probability 1-d-i. A computable lower bound on the capacity of this channel is derived. The transformation of the input sequence by the channel may be viewed in terms of runs as follows: some runs of the input sequence get shorter/longer, some runs get deleted, and some new runs are added. It is difficult for the decoder to synchronize the channel output sequence to the transmitted codeword mainly due to deleted runs and new inserted runs. The main idea is a mutual information decomposition in terms of the rate achieved by a sub-optimal decoder that determines the positions of the deleted and inserted runs in addition to decoding…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
