Massive ultra-reliable and low-latency communications (mURLLC) has been developed as a new and dominating 6G-standard services to support statistical quality of service (QoS) provisioning while raising several major design issues, including massive connectivity, ultra-low latency, and super-reliability. Correspondingly, a number of emerging 6G candidate enablers, including statistical delay and error-rate bounded QoS provisioning, finite blocklength coding (FBC), intelligent reflecting surfaces (IRS), unmanned aerial vehicle (UAV), etc., have been developed to support mURLLC. Specifically, due to the potential improvements in coverage capability as well as the spectral efficiency, both IRS and UAV have been widely proposed to reconfigure wireless propagation environments to compensate for blocked line-of-sight (LOS) communication links and create controllable and smart radio environments. In addition, to solve the massive connectivity issues imposed by mURLLC, integrating UAV with IRS provides a promising means to significantly enhance LOS coverage due to the relatively high altitude and 3D mobility of the UAVs. However, although small-packet communications enabled by FBC are usually employed for massive access to reduce access latency and decoding complexity, how to upper-bound both delay and error rate while efficiently supporting mURLLC in IRS-UAV-integrated systems still remains a challenging problem.

中文翻译：

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IRS 和无人机轨迹的联合优化：使用 FBC 支持 mURLLC 驱动的 6G 移动无线网络上的统计延迟和错误率限制 QoS


大规模超可靠和低延迟通信（mURLLC）已被开发为一种新的主​​导 6G 标准服务，以支持统计服务质量（QoS）配置，同时提出了几个主要设计问题，包括大规模连接、超低延迟、和超级可靠性。相应地，已经开发了许多新兴的6G候选使能器，包括统计延迟和错误率有限的QoS配置、有限块长度编码（FBC）、智能反射面（IRS）、无人机（UAV）等，以支持mURLLC。具体来说，由于覆盖能力和频谱效率的潜在改进，IRS和无人机已被广泛提议重新配置无线传播环境，以补偿视线（LOS）通信链路的阻塞并创建可控和智能无线电环境。此外，为了解决 mURLLC 带来的大规模连接问题，由于无人机相对较高的高度和 3D 移动性，将无人机与 IRS 集成提供了一种有前途的方法，可以显着增强 LOS 覆盖范围。然而，尽管FBC支持的小包通信通常用于大规模访问，以减少访问延迟和解码复杂性，但如何在IRS-UAV集成系统中有效支持mURLLC的同时限制延迟和错误率仍然是一个具有挑战性的问题。