Performance Boundary Analyses for Statistical Multi-QoS Framework Over 6G SAGINs
Jingqing Wang, Wenchi Cheng, and Wei Zhang

TL;DR
This paper develops analytical models for 6G SAGINs to support statistical QoS with delay and error-rate constraints in the finite blocklength regime, addressing complex network behaviors for mURLLC.
Contribution
It introduces new statistical performance modeling frameworks for 6G SAGINs, incorporating finite blocklength effects and providing tools for QoS assurance in complex, dynamic environments.
Findings
Models for aggregate interference and error probability are validated via simulations.
The epsilon-effective capacity metric effectively characterizes delay and error-rate constraints.
Analytical frameworks enable better QoS provisioning in 6G SAGINs.
Abstract
To enable the cost-effective universal access and the enhancement of current communication services, the space-air-ground integrated networks (SAGINs) have recently been developed due to its exceptional 3D coverage and the ability to guarantee rigorous and multidimensional demands for quality-of-service (QoS) provisioning, including delay and reliability across vast distances. In response to the complex, heterogeneous, and dynamic serving scenarios and stringent performance expectations for 6G SAGINs, it is crucial to undertake modeling, assurance, and analysis of the key technologies, aligned with the diverse demands for QoS provisioning in the non-asymptotic regime, i.e., when implementing finite blocklength coding (FBC) as a new dimension for error-rate bounded QoS metric. However, how to design new statistical QoS-driven performance modeling approaches that accurately delineate the…
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Taxonomy
TopicsPAPR reduction in OFDM
MethodsSparse Evolutionary Training
