AttentionCode: Ultra-Reliable Feedback Codes for Short-Packet Communications

AttentionCode: Ultra-Reliable Feedback Codes for Short-Packet Communications
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DOI:
10.1109/tcomm.2023.3280563
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发表时间:
2022-05
影响因子:
8.3
通讯作者:
Yulin Shao;Emre Ozfatura;A. Perotti;B. Popović;Deniz Gündüz
Yulin Shao;Emre Ozfatura;A. Perotti;B. Popović;Deniz Gündüz
中科院分区:
计算机科学2区
文献类型:
--
作者:
Yulin Shao;Emre Ozfatura;A. Perotti;B. Popović;Deniz Gündüz

文献摘要

相似文献

超可靠的短分组通信是未来无线网络中具有关键应用的主要挑战。为了实现超过99.999%的超可靠通信,本文设想了一种新的基于交互的通信范式,该范式利用了来自接收器的反馈。我们提出了AttentionCode,这是一类利用深度学习(DL)技术的新反馈代码。AttentionCode的基础是三个架构创新:AttentionNet,输入重组和适应衰落信道,以及几种训练方法,包括大批量训练,分布式学习,前瞻优化器,训练测试信噪比(SNR)失配和课程学习。训练方法可以潜在地推广到具有机器学习的其他无线通信应用。数值实验验证了AttentionCode在加性白色高斯噪声(AWGN)信道和衰落信道中建立了所有基于DL的反馈码中的新技术水平。例如,在具有无噪声反馈的AWGN信道中,对于50位的块大小,当前向信道SNR为0 dB时,AttentionCode实现了10−7的误块率(BLER),证明了AttentionCode提供超可靠短分组通信的潜力。
Ultra-reliable short-packet communication is a major challenge in future wireless networks with critical applications. To achieve ultra-reliable communications beyond 99.999%, this paper envisions a new interaction-based communication paradigm that exploits feedback from the receiver. We present AttentionCode, a new class of feedback codes leveraging deep learning (DL) technologies. The underpinnings of AttentionCode are three architectural innovations: AttentionNet, input restructuring, and adaptation to fading channels, accompanied by several training methods, including large-batch training, distributed learning, look-ahead optimizer, training-test signal-to-noise ratio (SNR) mismatch, and curriculum learning. The training methods can potentially be generalized to other wireless communication applications with machine learning. Numerical experiments verify that AttentionCode establishes a new state of the art among all DL-based feedback codes in both additive white Gaussian noise (AWGN) channels and fading channels. In AWGN channels with noiseless feedback, for example, AttentionCode achieves a block error rate (BLER) of 10−7 when the forward channel SNR is 0 dB for a block size of 50 bits, demonstrating the potential of AttentionCode to provide ultra-reliable short-packet communications.