论文标题
您需要的只是反馈：与块注意反馈代码的通信
All you need is feedback: Communication with block attention feedback codes
论文作者
论文摘要
基于深度学习的渠道代码设计最近引起了人们的兴趣，可以替代传统的编码算法，特别是对于现有代码不提供有效解决方案的渠道。通过反馈渠道进行沟通就是一个问题，最近通过采用各种深度学习架构来获得有希望的结果。在本文中，我们为反馈渠道介绍了一种新颖的学习辅助代码设计，称为广义块注意反馈（GBAF）代码，i）i）采用了一个模块化体系结构，可以使用不同的神经网络体系结构实现； ii）与现有设计相比，错误的可能性提高了错误的可能性； iii）可以以所需的代码速率传输。
Deep learning based channel code designs have recently gained interest as an alternative to conventional coding algorithms, particularly for channels for which existing codes do not provide effective solutions. Communication over a feedback channel is one such problem, for which promising results have recently been obtained by employing various deep learning architectures. In this paper, we introduce a novel learning-aided code design for feedback channels, called generalized block attention feedback (GBAF) codes, which i) employs a modular architecture that can be implemented using different neural network architectures; ii) provides order-of-magnitude improvements in the probability of error compared to existing designs; and iii) can transmit at desired code rates.
