AoI-Driven Statistical Delay and Error-Rate Bounded QoS Provisioning for mURLLC over UAV-Multimedia 6G Mobile Networks Using FBC

Massive ultra-reliable and low latency communications (mURLLC) has emerged as new and dominating 6G-standard services to support statistical quality-of-services (QoS) provisioning for delay-sensitive data transmissions. To measure the freshness of updated information, age of information (AoI) has recently formed as the new dimension of QoS metric. Since status updates usually consist of a small number of information bits but warrant ultra-low latency, integrating AoI with finite blocklength coding (FBC) creates an alternative promising solution for mURLLC. On the other hand, to solve the massive connectivity issues imposed by mURLLC, unmanned aerial vehicle (UAV) has been developed to significantly enhance the line-of-sight (LOS) coverage while guaranteeing various QoS requirements. However, how to efficiently integrate the above new techniques for statistical delay and error-rate bounded QoS provisioning in UAV systems has been neither well understood nor thoroughly studied. To overcome these challenges, we propose FBC based statistical delay and error-rate bounded QoS provisioning schemes which leverage AoI as a key QoS provisioning technique for mURLLC over UAV mobile networks. First, we develop FBC based UAV system models. Second, we build up AoI-metric based modeling frameworks to upper-bound peak AoI violation probability using FBC. Third, we formulate and solve FBC based peak AoI violation probability minimization problem. Forth, we jointly optimize peak AoI violation probability and $\epsilon $ -effective capacity and characterize their tradeoffs. Finally, our simulations validate and evaluate our developed schemes.