System-Level Metrics for Non-Terrestrial Networks Under Stochastic Geometry Framework

TL;DR

This paper explores the use of stochastic geometry to analyze system-level metrics in non-terrestrial networks, providing insights into performance tradeoffs across different platforms and scenarios for 6G wireless systems.

Contribution

It introduces suitable stochastic geometry models for NTN system analysis and evaluates key metrics across various platforms and application scenarios, filling gaps in existing research.

Findings

Identifies optimal SG models for different NTN platforms

Analyzes system-level metrics for NTN scenarios

Provides performance insights for 6G applications

Abstract

Non-terrestrial networks (NTNs) are considered one of the key enablers in sixth-generation (6G) wireless networks; and with their rapid growth, system-level metrics analysis adds crucial understanding into NTN system performance. Applying stochastic geometry (SG) as a system-level analysis tool in the context of NTN offers novel insights into the network tradeoffs. In this paper, we study and highlight NTN common system-level metrics from three perspectives: NTN platform types, typical communication issues, and application scenarios. In addition to summarizing existing research, we study the best-suited SG models for different platforms and system-level metrics which have not been well studied in the literature. In addition, we showcase NTN-dominated prospective application scenarios. Finally, we carry out a performance analysis of system-level metrics for these applications based on SG models.