Statistical Delay and Error-Rate Bounded QoS Provisioning for 6G mURLLC Over AoI-Driven and UAV-Enabled Wireless Networks

Massive ultra-reliable and low latency communications (mURLLC) has been developed as a new and dominating 6G standard traffic service to support statistical delay and error-rate bounded quality-of-services (QoS) provisioning for real-time data-transmissions. Inspired by mURLLC, finite blocklength coding (FBC) has been proposed to upper-bound both delay and error-rate by using short-packet data communications. On the other hand, to solve the massive connectivity problem imposed by mURLLC, the unmanned aerial vehicle (UAV)-enabled systems are developed by leveraging their deploying flexibility and high probability of establishing line-of-sight (LoS) wireless links while guaranteeing various QoS requirements. In addition, the age of information (AoI) has recently emerged as a new QoS performance metric in terms of information freshness. However, how to efficiently integrate and implement the above new techniques for statistical delay and error-rate bounded QoS provisioning over 6G standards has neither been well understood nor thoroughly studied. To overcome these challenges, we propose the statistical delay and error-rate bounded QoS provisioning schemes which leverage the AoI technique as a key QoS performance metric to efficiently support mURLLC over UAV-enabled 6G wireless networks in the finite blocklength regime. Specifically, first, we develop the UAV-enabled 3D wireless networking models with wireless-link channels using FBC. Second, we build up the AoI-metric based modeling frameworks in the finite blocklength regime. Third, taking into account the peak AoI violation probability, we formulate and solve the AoI-driven epsilon-effective capacity maximization problems to support statistical delay and error-rate bounded QoS provisioning. Finally, we conduct the extensive simulations to validate and evaluate our developed schemes.