In this paper, we study grant-free, asynchronous control-to-control (C2C) communications in an indoor scenario with a shared wireless channel. Each communication node transmits command units, each consisting of a variable-length low-density parity-check (LDPC)--coded payload preceded by a start sequence and followed by a tail sequence. Due to the asynchronous nature of the access, transmissions from different nodes are not aligned over time. As a result, each receiving controller observes the superposition of multiple command units transmitted by different nodes over a receiver-defined superframe interval. Each node transmits one or more replicas of the same command unit. We propose a receiver architecture in which the detection of command unit boundaries (start/tail sequences) is carried out by a single convolutional neural network (CNN) operating directly on the received signal. We show that, while start-sequence detection must rely only on the received waveform, tail-sequence detection can additionally exploit the soft information produced by the LDPC decoder, together with channel estimates. Finally, once commands units are successfully decoded, successive interference cancellation (SIC) can be applied. Simulation results demonstrate that the receiver we propose achieves reliable packet-boundary identification and a low end-to-end packet loss rate, even under uncoordinated and high-traffic operating conditions.

翻译：本文研究了室内场景下共享无线信道中的免授权、异步控制至控制(C2C)通信。每个通信节点传输包含可变长度低密度奇偶校验(LDPC)编码载荷的命令单元，该载荷前后分别由起始序列和结束序列引导。由于接入的异步特性，不同节点的传输在时间上未对齐。因此，每个接收控制器可观测到由多个节点在接收器定义的超帧间隔内传输的叠加命令单元。每个节点可发送同一命令单元的一个或多个副本。我们提出一种接收机架构，其中采用单一卷积神经网络(CNN)直接对接收信号进行操作以检测命令单元边界(起始/结束序列)。研究表明，起始序列检测仅能依赖接收波形，而结束序列检测可额外利用LDPC解码器产生的软信息及信道估计。最后，当命令单元成功解码后，可应用连续干扰消除(SIC)。仿真结果表明，即使在无协调、高流量工作条件下，所提接收机也能实现可靠的数据包边界识别与较低的端到端丢包率。