Stacked Intelligent Metasurfaces-Aided eVTOL Delay Sensitive Communications

2025-07-09

AI Summary

Urban air mobility (UAM) demands ultra-reliable low-latency communication (URLLC) for eVTOL operations, yet existing stacked intelligent metasurface (SIM)-based systems lack rigorous mathematical characterization of probabilistic delay bounds under dynamic airspace conditions, hindering collision avoidance and airspace management. Method: This work pioneers the application of network calculus to UAM communication modeling, establishing a novel analytical framework that quantifies probabilistic delay upper bounds. We formulate a non-convex joint optimization problem for propagation delay and probabilistic delay bound minimization, and solve it efficiently via block coordinate descent combined with semidefinite relaxation. Results: Experiments demonstrate significant reduction in system regret, improved throughput, and enhanced stability and robustness of end-to-end latency performance across diverse traffic load scenarios.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Search and Optimization: Sampling/Simulation-based Search
• Multiagent Systems: Agent Communication

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

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.

Problem

• Quantify probabilistic delay bounds for eVTOL communications
• Optimize joint probabilistic and propagation delay minimization
• Analyze impact of factors on regret and transmission rate

Innovation

• Network calculus for probabilistic delay bounds
• BCD and SDR for non-convex optimization
• Analysis of load intensity impact