论文标题
Tinyturbo：边缘有效的涡轮解码器
TinyTurbo: Efficient Turbo Decoders on Edge
论文作者
论文摘要
在本文中，我们介绍了一种名为Tinyturbo的涡轮代码的神经增强的解码器。 Tinyturbo具有与经典的Max-Log-Map算法相当的复杂性，但可靠性比Max-Log-Map基线要好得多，并且可以接近地图算法。我们表明，Tinyturbo在各种现实的感兴趣渠道（例如EPA和EVA通道）上表现出强大的鲁棒性，这些渠道包括在LTE标准中。我们还表明，TinyTurbo在不同速率，区块长度和格子上强烈概括。我们通过无线实验验证Tinyturbo的可靠性和效率。
In this paper, we introduce a neural-augmented decoder for Turbo codes called TINYTURBO . TINYTURBO has complexity comparable to the classical max-log-MAP algorithm but has much better reliability than the max-log-MAP baseline and performs close to the MAP algorithm. We show that TINYTURBO exhibits strong robustness on a variety of practical channels of interest, such as EPA and EVA channels, which are included in the LTE standards. We also show that TINYTURBO strongly generalizes across different rate, blocklengths, and trellises. We verify the reliability and efficiency of TINYTURBO via over-the-air experiments.
