Automation enabled by ultra-reliable and low latency 5G connectivity is expected to transform the industrial landscape over the next decade. Given the spectrum crunch in bands below 6 GHz, there is significant interest in exploring the use of millimeter wave (mmWave) bands for industrial automation. The harsh propagation conditions at high frequencies raise questions about the viability of providing ultra-reliable and low latency connectivity in these bands. Furthermore, the use of analog beamforming with narrow beams implies limited frequency multiplexing opportunity despite the wider bandwidths available, which in turn results in larger waiting times for packet transmission. We study the propagation in a factory floor using ray tracing, which shows that received signal strength is sufficiently large even when the line-of-sight (LoS) signal is blocked. To improve the latency performance, we propose an adaptive beam selection method that chooses the best set of beams across multiple users to reduce the overall latency for all users. We show through simulations that our proposed greedy algorithm performs better than the state-of-the-art algorithm, and that there is more improvement possible.

中文翻译：

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用于工厂车间自动化的超可靠低延迟毫米波通信

由超可靠和低延迟 5G 连接实现的自动化有望在未来十年改变工业格局。鉴于 6 GHz 以下频段的频谱紧缩，人们对探索将毫米波 (mmWave) 频段用于工业自动化非常感兴趣。高频下的恶劣传播条件引发了有关在这些频段提供超可靠和低延迟连接的可行性的问题。此外，尽管可用的带宽更宽，但使用窄波束的模拟波束成形意味着频率复用机会有限，这反过来导致数据包传输的等待时间更长。我们使用光线追踪研究工厂车间的传播，这表明即使视线 (LoS) 信号被阻挡，接收信号强度也足够大。为了提高延迟性能，我们提出了一种自适应波束选择方法，该方法在多个用户之间选择最佳波束集，以减少所有用户的整体延迟。我们通过模拟表明，我们提出的贪婪算法比最先进的算法性能更好，并且可能有更多的改进。