Joint Optimization of IRS and UAV-Trajectory: For Supporting Statistical Delay and Error-Rate Bounded QoS Over mURLLC-Driven 6G Mobile Wireless Networks Using FBC

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.

大规模超可靠低延迟通信（mURLLC）已发展成为一种新的主导性6G标准服务，用于支持统计服务质量（QoS）供应，同时引发了几个主要设计问题，包括大规模连接、超低延迟和超高可靠性。相应地，一些新兴的6G候选使能技术，包括统计延迟和有界误码率QoS供应、有限块长编码（FBC）、智能反射面（IRS）、无人机（UAV）等，已被开发用于支持mURLLC。具体而言，由于覆盖能力和频谱效率方面的潜在提升，IRS和UAV都被广泛提议用于重新配置无线传播环境，以补偿受阻的视距（LOS）通信链路并创建可控的智能无线电环境。此外，为了解决mURLLC带来的大规模连接问题，将UAV与IRS集成提供了一种有前景的方法，由于UAV相对较高的高度和三维移动性，可显著增强视距覆盖。然而，尽管由FBC实现的小数据包通信通常用于大规模接入以降低接入延迟和解码复杂度，但如何在IRS - UAV集成系统中有效支持mURLLC的同时对延迟和误码率进行上界约束仍然是一个具有挑战性的问题。