在对称离散无记忆信道上学习多速率任务导向通信

IF 3.7 3区计算机科学 Q2 TELECOMMUNICATIONS

IEEE Communications Letters Pub Date : 2024-08-27 DOI:10.1109/LCOMM.2024.3450598

Anbang Zhang;Shuaishuai Guo

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引用次数: 0

摘要

这封信介绍了一种面向任务的多速率通信（MR-ToC）框架。该框架可动态适应通信管道内可负担数据速率的变化。它将通信管道概念化为对称、离散、无记忆通道。我们采用渐进式学习策略来训练系统，其中包括用于编码和任务推理的嵌套编码本。这种配置允许根据不断变化的信道条件调整多个速率级别。实验结果表明，该系统不仅支持不同编码级别的边缘推理，而且在适应多变的通信环境方面表现出色。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Learning Multi-Rate Task-Oriented Communications Over Symmetric Discrete Memoryless Channels

This letter introduces a multi-rate task-oriented communication (MR-ToC) framework. This framework dynamically adapts to variations in affordable data rate within the communication pipeline. It conceptualizes communication pipelines as symmetric, discrete, memoryless channels. We employ a progressive learning strategy to train the system, comprising a nested codebook for encoding and task inference. This configuration allows for the adjustment of multiple rate levels in response to evolving channel conditions. The results from our experiments show that this system not only supports edge inference across various coding levels but also excels in adapting to variable communication environments.

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来源期刊

IEEE Communications Letters 工程技术-电信学

CiteScore

8.10

自引率

7.30%

发文量

590

审稿时长

2.8 months

期刊介绍： The IEEE Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of communication over different media and channels including wire, underground, waveguide, optical fiber, and storage channels. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of communication systems.