@inproceedings{1cef1e6c37dc4d7fa4f1d405162d53b6,
title = "Broadcasting Information subject to State Masking over a MIMO State Dependent Gaussian Channel",
abstract = "The problem of channel coding over the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC) with additive independent Gaussian states is considered. The states are known in a noncausal manner to the encoder, and it wishes to minimize the amount of information that the receivers can learn from the channel outputs about the state sequence. The state leakage rate is measured as a normalized blockwise mutual information between the state sequence and the channel outputs' sequences. We employ a new version of a state-dependent extremal inequality and show that Gaussian input maximizes the state-dependent version of Marton's outer bound. Further, we show that our inner bound coincides with the outer bound. Our result generalizes previously studied scalar Gaussian BC with state and MIMO BC without the state.",
keywords = "Broadcast channel, Dirty paper coding, Gelf'and-Pinsker scheme, enhanced channel, entropy power inequality, extremal inequality, noncausal CSI, state masking",
author = "Michael Dikshtein and Anelia Somekh-Baruch and \{Shamai Shitz\}, Shlomo",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Symposium on Information Theory, ISIT 2019 ; Conference date: 07-07-2019 Through 12-07-2019",
year = "2019",
month = jul,
doi = "10.1109/isit.2019.8849488",
language = "الإنجليزيّة",
series = "IEEE International Symposium on Information Theory - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "275--279",
booktitle = "2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings",
address = "الولايات المتّحدة",
}