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On the Capacity Enlargement of Gaussian Broadcast Channels With Passive Noisy Feedback

Abstract : It is well known that the capacity region of an average transmit power constrained Gaussian Broadcast Channel (GBC) with independent noise realizations at the receivers is enlarged by the presence of causal noiseless feedback. When the noise variances at the receivers are identical, even passive feedback via independent memoryless Gaussian links can lead to a capacity region enlargement. The last fact remains true even when the feedback noise variance is very high, and available only from one of the receivers. While such capacity enlargements are feasible for several other feedback models in the Gaussian BC setting, it is also known that feedback does not change the capacity region for physically degraded broadcast channels. In this paper, we consider a two user GBC with independent noise realizations at the receivers, where the feedback links from the receivers are corrupted by independent additive Gaussian noise processes. We investigate the set of four noise variances, two forward and two feedback, for which no capacity enlargement is possible. A sharp characterization of this region is derived, i.e., any quadruple outside the presented region will lead to a capacity enlargement, whereas quadruples inside will leave the capacity region unchanged. Our results lead to the conclusion that when the forward noise variances are different, too noisy a feedback from one of the receivers alone is not always beneficial for enlarging the capacity region, be it from the stronger user or the weaker one, in sharp contrast to the case of equal forward noise variances.
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Submitted on : Tuesday, September 21, 2021 - 11:52:57 AM
Last modification on : Friday, January 28, 2022 - 3:39:18 AM
Long-term archiving on: : Wednesday, December 22, 2021 - 6:50:36 PM


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Aditya Narayan Ravi, Sibi Raj B. Pillai, Vinod Prabhakaran, Michèle Wigger. On the Capacity Enlargement of Gaussian Broadcast Channels With Passive Noisy Feedback. IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers, 2021, 67 (10), pp.6356-6367. ⟨10.1109/TIT.2021.3096639⟩. ⟨hal-03350401⟩



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