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Digital Twin-based SIM Communication and Flight Control for Advanced Air Mobility

Kai Xiong, Zhen Chen, Juefei Xie, Supeng Leng, Chau Yuen

TL;DR

This work proposes a Composite Potential Field (CPF) approach that dynamically integrates target, separation, and communication fields to optimize both SIM communication efficiency and flight safety and results validate the effectiveness of this DT-based approach.

Abstract

Electric Vertical Take-off and Landing vehicles (eVTOLs) are driving Advanced Air Mobility (AAM) toward transforming urban transportation by extending travel from congested ground networks to low-altitude airspace. This transition promises to reduce traffic congestion and significantly shorten commute times. To ensure aviation safety, eVTOLs must fly within prescribed flight corridors. These corridors are managed by ground-based Air Traffic Control (ATCo) stations, which oversee air-ground communication and flight scheduling. However, one critical challenge remains: the lack of high rate air-ground communication and safe flight planning within these corridors. The introduction of 6G-oriented Stacked Intelligent Metasurface (SIM) technology presents a high rate communication solution. With advanced phase-shifting capabilities, SIM enables precise wireless signal control and supports beam-tracking communication with eVTOLs. Leveraging this technology, we propose a Composite Potential Field (CPF) approach. This method dynamically integrates target, separation, and communication fields to optimize both SIM communication efficiency and flight safety. Simulation results validate the effectiveness of this DT-based approach. Compared to the potential field flight control benchmark, it improves the transmission rate by 8.3\%. Additionally, it reduces flight distance deviation from the prescribed corridor by 10\% compared to predetermined optimization methods.

Digital Twin-based SIM Communication and Flight Control for Advanced Air Mobility

TL;DR

This work proposes a Composite Potential Field (CPF) approach that dynamically integrates target, separation, and communication fields to optimize both SIM communication efficiency and flight safety and results validate the effectiveness of this DT-based approach.

Abstract

Electric Vertical Take-off and Landing vehicles (eVTOLs) are driving Advanced Air Mobility (AAM) toward transforming urban transportation by extending travel from congested ground networks to low-altitude airspace. This transition promises to reduce traffic congestion and significantly shorten commute times. To ensure aviation safety, eVTOLs must fly within prescribed flight corridors. These corridors are managed by ground-based Air Traffic Control (ATCo) stations, which oversee air-ground communication and flight scheduling. However, one critical challenge remains: the lack of high rate air-ground communication and safe flight planning within these corridors. The introduction of 6G-oriented Stacked Intelligent Metasurface (SIM) technology presents a high rate communication solution. With advanced phase-shifting capabilities, SIM enables precise wireless signal control and supports beam-tracking communication with eVTOLs. Leveraging this technology, we propose a Composite Potential Field (CPF) approach. This method dynamically integrates target, separation, and communication fields to optimize both SIM communication efficiency and flight safety. Simulation results validate the effectiveness of this DT-based approach. Compared to the potential field flight control benchmark, it improves the transmission rate by 8.3\%. Additionally, it reduces flight distance deviation from the prescribed corridor by 10\% compared to predetermined optimization methods.
Paper Structure (18 sections, 47 equations, 11 figures, 1 table, 4 algorithms)

This paper contains 18 sections, 47 equations, 11 figures, 1 table, 4 algorithms.

Table of Contents

  1. Introduction
  2. Related Work
  3. Communication and Flight Control Optimization
  4. Stacked Intelligent Metasurface
  5. Digital Twin
  6. System Architecture
  7. Digital Twin Modeling
  8. Communication and Flight Joint Optimization
  9. Problem Formulation
  10. Model Solution
  11. SIM Communication Optimization
  12. transmission power $\bm{P}$-related block optimization
  13. Phase Shift Matrix $\bm{\Psi}$-related block optimization
  14. Flight Control Optimization
  15. Composite Potential Field
  16. ...and 3 more sections

Figures (11)

  • Figure 1: DT-based SIM communication and eVTOL flight Optimization.
  • Figure 2: Flowchart for joint optimization of communication and flight in DT synchronization.
  • Figure 3: The illustration of the proposed DQN structure
  • Figure 4: Transmission rate comparison of different SIM communication optimizations
  • Figure 5: Mean distance deviation of the eVTOL with the proposed DQN-based flight control
  • ...and 6 more figures