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- W4312051023 abstract "Type-based multiple access (TBMA) is a semantics-aware multiple access protocol for remote inference. In TBMA, codewords are reused across transmitting sensors, with each codeword being assigned to a different observation value. Existing TBMA protocols are based on fixed shared codebooks and on conventional maximum-likelihood or Bayesian decoders, which require knowledge of the distributions of observations and channels. In this letter, we propose a novel design principle for TBMA based on the information bottleneck (IB). In the proposed IB-TBMA protocol, the shared codebook is jointly optimized with a decoder based on artificial neural networks (ANNs), so as to adapt to source, observations, and channel statistics based on data only. We also introduce the Compressed IB-TBMA (CB-TBMA) protocol, which improves IB-TBMA by enabling a reduction in the number of codewords via an IB-inspired clustering phase. Numerical results demonstrate the importance of a joint design of codebook and neural decoder, and validate the benefits of codebook compression." @default.
- W4312051023 created "2023-01-04" @default.
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- W4312051023 date "2022-12-19" @default.
- W4312051023 modified "2023-10-15" @default.
- W4312051023 title "Semantics-Aware Remote Estimation via Information Bottleneck-Inspired Type Based Multiple Access" @default.
- W4312051023 doi "https://doi.org/10.48550/arxiv.2212.09337" @default.
- W4312051023 hasPublicationYear "2022" @default.
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