Short Blocklength Wiretap Channel Codes via Deep Learning: Design and Performance Evaluation

Rana, Vidhi; Chou, Remi A.

doi:10.48550/arxiv.2206.03477

Cited by 1 publication

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“…Finally, beyond proving the existence of achievability schemes for our models, finding explicit coding schemes largely remains an open problem. We note that [ 34 ] investigates this problem for short communication blocklengths over point-to-point channels via a practical approach that relies on deep learning. Another open problem is to achieve the same regions as that derived in this paper under strong and semantic security guarantees.…”

Section: Concluding Remarksmentioning

confidence: 99%

Gaussian Multiuser Wiretap Channels in the Presence of a Jammer-Aided Eavesdropper

Chou

Yener

2022

Entropy

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This paper considers secure communication in the presence of an eavesdropper and a malicious jammer. The jammer is assumed to be oblivious of the communication signals emitted by the legitimate transmitter(s) but can employ any jamming strategy subject to a given power constraint and shares her jamming signal with the eavesdropper. Four such models are considered: (i) the Gaussian point-to-point wiretap channel; (ii) the Gaussian multiple-access wiretap channel; (iii) the Gaussian broadcast wiretap channel; and (iv) the Gaussian symmetric interference wiretap channel. The use of pre-shared randomness between the legitimate users is not allowed in our models. Inner and outer bounds are derived for these four models. For (i), the secrecy capacity is obtained. For (ii) and (iv) under a degraded setup, the optimal secrecy sum-rate is characterized. Finally, for (iii), ranges of model parameter values for which the inner and outer bounds coincide are identified.

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Section: Concluding Remarksmentioning

confidence: 99%