Resource Allocation and Sharing for UAV-Assisted Integrated TN-NTN with Multi-Connectivity

2026-01-21

AI Summary

This study addresses the challenges of spectrum and power resource allocation for multi-connected unmanned aerial vehicles (UAVs) in integrated space-air-ground networks. Focusing on three heterogeneous link types—UAV-to-terrestrial base station (UAV-RBS), UAV-to-UAV, and UAV-to-high-altitude platform (UAV-HAP)—the work proposes a joint resource allocation framework under dynamic channel conditions and diverse quality-of-service (QoS) constraints. Two novel algorithms are developed: the first maximizes the aggregate throughput of non-UAV-UAV links while ensuring reliable UAV-UAV communication; the second enhances network-wide fairness by maximizing the minimum link capacity. Simulation results demonstrate that the proposed approach significantly outperforms benchmark schemes in both system throughput and fairness.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Intelligent Robots: Multi-Robot Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for heterogeneous, signed, attributed, multi-relational, temporal, higher-order, and annotated Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Unmanned aerial vehicles (UAVs) with multi-connectivity (MC) capabilities efficiently and reliably transfer data between terrestrial networks (TNs) and non-terrestrial networks (NTNs). However, optimally sharing and allocating spectrum and power resources to maintain MC while ensuring reliable connectivity and optimal performance remains challenging in such networks. Channel variations induced by mobility in UAV networks, coupled with the varying quality of service (QoS) demands of heterogeneous devices, resource sharing, and fairness requirements in capacity distribution pose challenges to optimal resource allocation. Thus, this paper investigates resource allocation for QoS-constrained, MC-enabled, dynamic UAVs in an integrated TN-NTN environment with spectrum sharing and fairness considerations. To this end, we consider three types of links: UAV-to-radio base station (RBS), UAV-to-UAV, and UAV-to-HAP. We also assume two types of UAVs with diverse QoS requirements to reflect a practical scenario. Consequently, we propose two algorithms. The first algorithm maximizes the capacity of UAVs-RBS and UAVs-HAP links while ensuring the reliability of the UAV-UAV link. To achieve this, the algorithm maximizes the collective throughput of the UAVs by optimizing the sum capacity of all the UAV-RBS and UAV-HAP links. Next, to provide constant capacity to all links and ensure fairness, we propose another algorithm that maximizes the minimum capacity across all links. We validate the performance of both algorithms through simulation

Problem

• Resource Allocation
• Multi-Connectivity
• UAV
• Spectrum Sharing
• QoS

Innovation

• Multi-Connectivity
• Resource Allocation
• UAV-Assisted NTN
• Fairness Optimization
• Integrated TN-NTN