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Distributed Self-allocated Time Slot Reuse: Multi-hop Communication in Rigid UAV Formations

Amelia Samandari, Andreas Willig, Barry Wu, Philippa Martin

TL;DR

This paper introduces D-STR, a distributed TDMA-like MAC for multi-hop, rigid UAV formations that enables spatially reused time-slot allocations to support periodic safety beacons. It combines a self-allocation mechanism with dynamic growth and shrinking of the superframe, ensuring convergence to a collision-free schedule while preserving periodic updates. Through extensive Python-based simulations, the authors demonstrate fast convergence, low overhead, and substantial scalability (e.g., a 3.56× increase in UAVs with only a 1.44× blow-up in the superframe) and show competitiveness against centralized schemes and single-hop protocols. The work offers a practical, scalable MAC solution for safety-critical UAV formations with distributed control and robust performance in large networks.

Abstract

Deployment of Unmanned Aerial Vehicles (UAVs) in autonomous formations necessitates accurate and timely communication of safety information. A communication protocol that supports timely and successful transfer of safety information between UAVs is therefore needed. This paper presents Distributed Self-allocated Time slot Reuse (D-STR). Our D-STR protocol addresses the essential task of communicating safety information in rigid Unmanned Aerial Vehicle (UAV) formations with different network topologies, enabling collision-free deployment of the formation. This is an important step for improving the safety and practicality of UAV formations in application scenarios that span a range of industries.

Distributed Self-allocated Time Slot Reuse: Multi-hop Communication in Rigid UAV Formations

TL;DR

This paper introduces D-STR, a distributed TDMA-like MAC for multi-hop, rigid UAV formations that enables spatially reused time-slot allocations to support periodic safety beacons. It combines a self-allocation mechanism with dynamic growth and shrinking of the superframe, ensuring convergence to a collision-free schedule while preserving periodic updates. Through extensive Python-based simulations, the authors demonstrate fast convergence, low overhead, and substantial scalability (e.g., a 3.56× increase in UAVs with only a 1.44× blow-up in the superframe) and show competitiveness against centralized schemes and single-hop protocols. The work offers a practical, scalable MAC solution for safety-critical UAV formations with distributed control and robust performance in large networks.

Abstract

Deployment of Unmanned Aerial Vehicles (UAVs) in autonomous formations necessitates accurate and timely communication of safety information. A communication protocol that supports timely and successful transfer of safety information between UAVs is therefore needed. This paper presents Distributed Self-allocated Time slot Reuse (D-STR). Our D-STR protocol addresses the essential task of communicating safety information in rigid Unmanned Aerial Vehicle (UAV) formations with different network topologies, enabling collision-free deployment of the formation. This is an important step for improving the safety and practicality of UAV formations in application scenarios that span a range of industries.

Paper Structure

This paper contains 21 sections, 9 figures, 13 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. System Model
  4. Protocol Design
  5. UAV States
  6. Self-allocation and Periodic Beacons
  7. Growing the Superframe
  8. Discussion of the growing mechanism
  9. Shrinking the Superframe
  10. The
  11. Discussion of the shrinking mechanism
  12. Detecting Reception Success
  13. Results
  14. Sensitivity Study
  15. Discussion
  16. ...and 6 more sections

Figures (9)

  • Figure 1: Overview D-STR state diagram
  • Figure 2: An example of the formation structure adopted for the sensitivity study. The circles represent the positions of the . The color and number assigned to a circle indicate the transmission time slot used by the in that position.
  • Figure 3: The final superframe length based on the default superframe size.
  • Figure 4: The level of spatial reuse, captured as the number of per time slot, based on the default superframe size.
  • Figure 5: The normalized convergence time at the upper and lower default superframe size.
  • ...and 4 more figures