论文标题
学习短包通信的联合检测,均衡和解码
Learning Joint Detection, Equalization and Decoding for Short-Packet Communications
论文作者
论文摘要
我们建议并实际上证明了短包无线通信的联合检测和解码方案,该方案需要在实际解码之前首先检测到消息的存在。为此,我们扩展了最近提出的串行涡轮化学神经网络(NN)体系结构,并训练它以查找短消息,这些消息可以是“一次”,当与内存的非同步通道发送时,可以“一次”,同步,均衡,均衡和解码。所提出的系统的构思优势源于整体消息结构,叠加的飞行员可以进行联合检测和解码,而无需依靠专用的序言。与使用专用序言相比,这不仅以较高的光谱效率而导致较短消息的可能性。我们将检测错误率(DER),位错误率(BER)和块错误率(BER)和块错误率(BLER)使用手工制作的最先进的传统基线进行比较,我们的模拟显示了在每个场景中,基于常规的基线的拟议基于AutoCododer系统的显着优势在输送k = 96信息位的情况下是常规基线。最后,我们实际上评估并确认了使用基于软件定义的无线电(SDR)测量测试台的拟议系统(OTA)的改进性能。
We propose and practically demonstrate a joint detection and decoding scheme for short-packet wireless communications in scenarios that require to first detect the presence of a message before actually decoding it. For this, we extend the recently proposed serial Turbo-autoencoder neural network (NN) architecture and train it to find short messages that can be, all "at once", detected, synchronized, equalized and decoded when sent over an unsynchronized channel with memory. The conceptional advantage of the proposed system stems from a holistic message structure with superimposed pilots for joint detection and decoding without the need of relying on a dedicated preamble. This results not only in higher spectral efficiency, but also translates into the possibility of shorter messages compared to using a dedicated preamble. We compare the detection error rate (DER), bit error rate (BER) and block error rate (BLER) performance of the proposed system with a hand-crafted state-of-the-art conventional baseline and our simulations show a significant advantage of the proposed autoencoder-based system over the conventional baseline in every scenario up to messages conveying k = 96 information bits. Finally, we practically evaluate and confirm the improved performance of the proposed system over-the-air (OTA) using a software-defined radio (SDR)-based measurement testbed.