Sharp Analytical Capacity Upper Bounds for Sticky and Related Channels. Cheraghchi, M. & Ribeiro, J. In *Proceedings of the 56th Annual Allerton Conference on Communication, Control, and Computing*, pages 1104–1111, 2018. Extended version in IEEE Transactions on Information Theory.

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Link Paper doi abstract bibtex

We study natural examples of binary channels with synchronization errors. These include the duplication channel, which independently outputs a given bit once or twice, and geometric channels that repeat a given bit according to a geometric rule, with or without the possibility of bit deletion. We apply the general framework of Cheraghchi (STOC 2018) to obtain sharp analytical upper bounds on the capacity of these channels. Previously, upper bounds were known via numerical computations involving the computation of finite approximations of the channels by a computer and then using the obtained numerical results to upper bound the actual capacity. While leading to sharp numerical results, further progress on the full understanding of the channel capacity inherently remains elusive using such methods. Our results can be regarded as a major step towards a complete understanding of the capacity curves. Quantitatively, our upper bounds sharply approach, and in some cases surpass, the bounds that were previously only known by purely numerical methods. Among our results, we notably give a completely analytical proof that, when the number of repetitions per bit is geometric (supported on $\{0,1,2,\dots\}$) with mean growing to infinity, the channel capacity remains substantially bounded away from $1$.

@INPROCEEDINGS{ref:conf:CR18, author = {Mahdi Cheraghchi and Jo\~{a}o Ribeiro}, title = {Sharp Analytical Capacity Upper Bounds for Sticky and Related Channels}, year = 2018, booktitle = {Proceedings of the 56th {Annual Allerton Conference on Communication, Control, and Computing}}, pages = {1104--1111}, note = {Extended version in {IEEE Transactions on Information Theory}.}, doi = {10.1109/ALLERTON.2018.8636009}, url_Link = {https://ieeexplore.ieee.org/document/8636009}, url_Paper = {https://arxiv.org/abs/1903.09992}, abstract = {We study natural examples of binary channels with synchronization errors. These include the duplication channel, which independently outputs a given bit once or twice, and geometric channels that repeat a given bit according to a geometric rule, with or without the possibility of bit deletion. We apply the general framework of Cheraghchi (STOC 2018) to obtain sharp analytical upper bounds on the capacity of these channels. Previously, upper bounds were known via numerical computations involving the computation of finite approximations of the channels by a computer and then using the obtained numerical results to upper bound the actual capacity. While leading to sharp numerical results, further progress on the full understanding of the channel capacity inherently remains elusive using such methods. Our results can be regarded as a major step towards a complete understanding of the capacity curves. Quantitatively, our upper bounds sharply approach, and in some cases surpass, the bounds that were previously only known by purely numerical methods. Among our results, we notably give a completely analytical proof that, when the number of repetitions per bit is geometric (supported on $\{0,1,2,\dots\}$) with mean growing to infinity, the channel capacity remains substantially bounded away from $1$. } }

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These include the\n duplication channel, which independently outputs a\n given bit once or twice, and geometric channels that\n repeat a given bit according to a geometric rule,\n with or without the possibility of bit deletion. We\n apply the general framework of Cheraghchi (STOC\n 2018) to obtain sharp analytical upper bounds on the\n capacity of these channels. Previously, upper\n bounds were known via numerical computations\n involving the computation of finite approximations\n of the channels by a computer and then using the\n obtained numerical results to upper bound the actual\n capacity. While leading to sharp numerical results,\n further progress on the full understanding of the\n channel capacity inherently remains elusive using\n such methods. Our results can be regarded as a major\n step towards a complete understanding of the\n capacity curves. 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