Song, Y;
Wan, K;
Liao, Z;
Xu, H;
Caire, G;
Shamai, S;
(2024)
An Achievable and Analytic Solution to Information Bottleneck for Gaussian Mixtures.
In:
IEEE International Symposium on Information Theory - Proceedings.
(pp. pp. 2460-2465).
IEEE: Athens, Greece.
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Abstract
In this paper, we consider a remote source coding problem with binary phase shift keying (BPSK) modulation sources, where observations are corrupted by additive white Gaussian noise (AWGN). An intermediate node, such as a relay, receives these observations and performs further compression to find the optimal trade-off between complexity and relevance. This problem can be formulated as an information bottleneck (IB) problem with Bernoulli sources and Gaussian mixture observations, for which no closed-form solution is known. To address this challenge, we propose a unified achievable scheme that employs three different compression strategies for intermediate node processing, i.e., two-level quantization, multi-level deterministic quantization, and soft quantization with tanh function. Comparative analyses with existing methods, such as the Blahut-Arimoto (BA) algorithm and the Information Dropout approach, are performed through numerical evaluations. The proposed analytic scheme is observed to consistently approach the (numerically) optimal performance over a range of signal-to-noise ratios (SNRs), confirming its effectiveness in the considered setting.
Type: | Proceedings paper |
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Title: | An Achievable and Analytic Solution to Information Bottleneck for Gaussian Mixtures |
Event: | 2024 IEEE International Symposium on Information Theory (ISIT) |
Dates: | 7 Jul 2024 - 12 Jul 2024 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1109/ISIT57864.2024.10619077 |
Publisher version: | https://doi.org/10.1109/ISIT57864.2024.10619077 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Quantization (signal), Closed-form solutions, AWGN, Phase modulation, Source coding, Approximation algorithms, Binary phase shift keying |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
URI: | https://discovery.ucl.ac.uk/id/eprint/10198390 |



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