Stacked Intelligent Metasurfaces-Aided eVTOL Delay Sensitive Communications

TL;DR

This paper develops a mathematical framework using network calculus to analyze and optimize delay bounds in SIM-based eVTOL communication systems for urban air mobility, addressing safety-critical latency requirements.

Contribution

It introduces a probabilistic delay bound analysis for SIM-based eVTOL systems using network calculus and proposes an efficient optimization approach combining BCD and SDR techniques.

Findings

Derived probabilistic delay bounds for SIM-based eVTOL communications.

Optimized delay and propagation delay jointly through a novel non-convex problem.

Analyzed the impact of load and delay on system performance.

Abstract

With rapid urbanization and increasing population density, urban traffic congestion has become a critical issue, and traditional ground transportation methods are no longer sufficient to address it effectively. To tackle this challenge, the concept of Advanced Air Mobility (AAM) has emerged, aiming to utilize low-altitude airspace to establish a three-dimensional transportation system. Among various components of the AAM system, electric vertical take-off and landing (eVTOL) aircraft plays a pivotal role due to their flexibility and efficiency. However, the immaturity of Ultra Reliable Low Latency Communication (URLLC) technologies poses significant challenges to safety-critical AAM operations. Specifically, existing Stacked Intelligent Metasurfaces (SIM)-based eVTOL systems lack rigorous mathematical frameworks to quantify probabilistic delay bounds under dynamic air traffic patterns, a prerequisite for collision avoidance and airspace management. To bridge this gap, we employ network calculus tools to derive the probabilistic upper bound on communication delay in the AAM system for the first time. Furthermore, we formulate a complex non-convex optimization problem that jointly minimizes the probabilistic delay bound and the propagation delay. To solve this problem efficiently, we propose a solution based on the Block Coordinate Descent (BCD) algorithm and Semidefinite Relaxation (SDR) method. In addition, we conduct a comprehensive analysis of how various factors impact regret and transmission rate, and explore the influence of varying load intensity and total delay on the probabilistic delay bound.