One-Shot Broadcast Joint Source-Channel Coding with Codebook Diversity

2026-01-15

AI Summary

This work addresses a fundamental reliability challenge in single-shot joint source-channel coding: ensuring that at least one decoder can reconstruct the source within a prescribed maximum distortion constraint over independent channels. To this end, the paper introduces, for the first time, a codebook diversity gain by designing disjoint codebooks for different decoders and synergistically combining it with channel diversity to enhance system robustness. The authors develop an extended multi-decoder framework grounded in the Poisson matching lemma and propose a hybrid encoding and grouping strategy that achieves an optimal trade-off between codebook diversity and channel diversity. Experimental results on binary symmetric channels demonstrate that the proposed hybrid scheme significantly outperforms baseline approaches employing either fully shared or entirely disjoint codebooks.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization

Application Category

• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

We study a one-shot joint source-channel coding setting where the source is encoded once and broadcast to $K$ decoders through independent channels. Success is predicated on at least one decoder recovering the source within a maximum distortion constraint. We find that in the one-shot regime, utilizing disjoint codebooks at each decoder yields a codebook diversity gain, distinct from the channel diversity gain that may be expected when several decoders observe independent realizations of the channel's output but share the same codebook. Coding schemes are introduced that leverage this phenomenon, where first- and second-order achievability bounds are derived via an adaptation of the Poisson matching lemma (Li and Anantharam, 2021) which allows for multiple decoders using disjoint codebooks. We further propose a hybrid coding scheme that partitions decoders into groups to optimally balance codebook and channel diversity. Numerical results on the binary symmetric channel demonstrate that the hybrid approach outperforms strategies where the decoders'codebooks are either fully shared or disjoint.

Problem

• one-shot joint source-channel coding
• broadcast
• codebook diversity
• distortion constraint
• multiple decoders

Innovation

• codebook diversity
• one-shot joint source-channel coding
• Poisson matching lemma
• hybrid coding scheme
• broadcast communication