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An Achievable Rate-Distortion Region for Joint State and Message Communication over Multiple Access Channels

Xinyang Li, Vlad C. Andrei, Ullrich J. Mönich, Holger Boche

TL;DR

An achievable rate-distortion region is derived for the state-dependent discrete memoryless multiple access channel (SD-DMMAC), where the generalized feedback and causal side information are present at encoders, and the decoder performs the joint task of message decoding and state estimation.

Abstract

This paper derives an achievable rate-distortion (R-D) region for the state-dependent discrete memoryless multiple access channel (SD-DMMAC), where the generalized feedback and causal side information are present at encoders, and the decoder performs the joint task of message decoding and state estimation. The Markov coding and backward-forward two-stage decoding schemes are adopted in the proof. This scenario is shown to be capable of modeling various integrated sensing and communication (ISAC) applications, including the monostatic-uplink system and multi-modal sensor networks, which are then studied as examples.

An Achievable Rate-Distortion Region for Joint State and Message Communication over Multiple Access Channels

TL;DR

An achievable rate-distortion region is derived for the state-dependent discrete memoryless multiple access channel (SD-DMMAC), where the generalized feedback and causal side information are present at encoders, and the decoder performs the joint task of message decoding and state estimation.

Abstract

This paper derives an achievable rate-distortion (R-D) region for the state-dependent discrete memoryless multiple access channel (SD-DMMAC), where the generalized feedback and causal side information are present at encoders, and the decoder performs the joint task of message decoding and state estimation. The Markov coding and backward-forward two-stage decoding schemes are adopted in the proof. This scenario is shown to be capable of modeling various integrated sensing and communication (ISAC) applications, including the monostatic-uplink system and multi-modal sensor networks, which are then studied as examples.
Paper Structure (12 sections, 3 theorems, 30 equations, 2 figures)

This paper contains 12 sections, 3 theorems, 30 equations, 2 figures.

Table of Contents

  1. Introduction
  2. Channel Model
  3. Main Results
  4. Examples and Applications
  5. Monostatic-uplink ISAC
  6. Multi-sensor Network
  7. Proof of Achievability
  8. Codebook Generation
  9. Encoding
  10. Decoding
  11. Analysis
  12. Conclusion

Key Result

Theorem 1

$\mathcal{R}(\mathcal{P}_D)$ is an achievable rd region, i.e.,

Figures (2)

  • Figure 1: The sddmmac with generalized feedback and side information.
  • Figure 2: The equivalent model of monostatic-uplink isac.

Theorems & Definitions (4)

  • Theorem 1
  • Remark 1
  • Lemma 1
  • Lemma 2