A Simultaneous Decoding Approach to Joint State and Message Communications

TL;DR

This paper introduces a novel simultaneous decoding scheme for joint state and message communication, improving capacity-distortion trade-offs and enabling better state estimation and message decoding in multi-user channels.

Contribution

It proposes a backward simultaneous decoding method that surpasses traditional sequential decoding, and applies it to various channels including broadcast and multiple access, with extensions to sensing systems.

Findings

Achieves optimal capacity-distortion function for point-to-point channels.

Larger achievable regions than existing sequential decoding methods.

Enhances communication and state estimation performance in multi-user channels.

Abstract

The capacity-distortion (C-D) trade-offs for joint state and message communications (JSMC) over single- and multi-user channels are investigated, where the transmitters have access to generalized state information and feedback while the receivers jointly decode the messages and estimate the channel state. A coding scheme is proposed based on backward simultaneous decoding of messages and compressed state descriptions without the need for the Wyner-Ziv random binning technique. For the point-to-point channel, the proposed scheme results in the optimal C-D function. For the state-dependent discrete memoryless degraded broadcast channel (SD-DMDBC), the successive refinement method is adopted for designing multi-stage state descriptions. With the simultaneous decoding approach, the derived achievable region is shown to be larger than the region obtained by the sequential decoding approach that is utilized in existing works. As for the state-dependent discrete memoryless multiple access channel (SD-DMMAC), in addition to the proposed method, Willem's coding strategy is applied to enable partial collaboration between transmitters through the feedback links. Moreover, the state descriptions are shown to enhance both communication and state estimation performance. Examples are provided for the derived results to verify the analysis, either numerically or analytically. With particular focus, simple but representative integrated sensing and communications (ISAC) systems are also considered, and their fundamental performance limits are studied.