Joint User Association and Resource Optimization for Low-Altitude UAV Swarm-Based ILAC Networks

YANG Zhuojia; SU Wei; YANG Bin; MA Yudong; WANG Wendi

doi:10.12263/DZXB.20260403

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Joint User Association and Resource Optimization for Low-Altitude UAV Swarm-Based ILAC Networks

PAPERS | 更新时间：2026-10-16

- Joint User Association and Resource Optimization for Low-Altitude UAV Swarm-Based ILAC Networks
- ACTA ELECTRONICA SINICA Vol. 54, Issue 6, Pages: 2676-2691(2026)
- 作者机构：
  
  1.北京交通大学电子信息工程学院，北京 100044
  2.滁州学院计算机与信息工程学院，安徽滁州 239000
  3.北京航空航天大学人工智能学院，北京 100083
- 作者简介：
- 基金信息：
  
  Science and Technology Innovation Program of Xiong'an New Area(2025XAGG0055);General Program of the National Natural Science Foundation of China(62372076)
- DOI：10.12263/DZXB.20260403
  CLC： TN929.5;
- Received：16 April 2026，
  
  Accepted：05 May 2026，
  
  Published：25 June 2026
- 稿件说明：
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杨卓佳, 苏伟, 杨斌, 等. 面向低空无人机集群的ILAC网络中联合用户关联与资源优化方法[J]. 电子学报, 2026, 54(06): 2676-2691.

YANG Zhuojia, SU Wei, YANG Bin, et al. Joint User Association and Resource Optimization for Low-Altitude UAV Swarm-Based ILAC Networks[J]. Acta Electronica Sinica, 2026, 54(06): 2676-2691.
杨卓佳, 苏伟, 杨斌, 等. 面向低空无人机集群的ILAC网络中联合用户关联与资源优化方法[J]. 电子学报, 2026, 54(06): 2676-2691. DOI：10.12263/DZXB.20260403

YANG Zhuojia, SU Wei, YANG Bin, et al. Joint User Association and Resource Optimization for Low-Altitude UAV Swarm-Based ILAC Networks[J]. Acta Electronica Sinica, 2026, 54(06): 2676-2691. DOI：10.12263/DZXB.20260403

摘要

通信定位一体化（Integrated Localization And Communication，ILAC）网络通过通信与定位的深度融合，能够在提供通信服务的同时实现高精度位置感知，成为未来无线网络发展的重要方向之一。然而，在应急救援场景下，传统依赖地面基站的ILAC网络易受到地面基础设施损毁影响，将面临通信覆盖中断、链路质量恶化和定位精度下降等问题。为此，本文构建了一种低空无人机集群辅助的ILAC网络，为受灾区域用户提供临时与分布式的通信与定位服务，并提出了一种基于分布式架构的无人机关联、频谱与功率联合优化方法，以保障高效的通信与定位服务，支持应急救援等关键任务的顺利执行。首先，本文建立基于双边双向测距的用户定位模型，描述无人机空中锚点与地面用户之间的测距关系及其对定位精度的影响。之后，构建以最大化最小用户吞吐量为目标，定位精度、无人机关联、频谱与功率等为约束的联合优化问题。针对此复杂优化问题，我们将其划分为无人机关联与功率-子信道优化两个子问题。针对第一个子问题，提出三维快速空中锚点选择方法，通过空间划分降低空中锚点搜索空间，实现用户通信接入点与定位锚点的快速关联；针对第二个子问题，提出基于多智能体近端策略优化的联合功率控制与子信道分配算法，利用分布式多智能体学习实现功率与子信道的协同决策。通过与多种基线算法仿真对比，结果表明本文所提出方法能够在保障定位精度约束的同时有效提升最小用户吞吐量，提高用户间通信公平性，并在相同网络场景设置下获得更优的定位性能，从而为应急场景下实现高效通信与可靠定位服务提供有力支持。

Abstract

Integrated localization and communication (ILAC) networks deeply integrate communication and positioning functions

enabling efficient communication transmission services while providing reliable positioning services. Owing to their ability to support both information exchange and positioning perception within a unified wireless network

ILAC networks have emerged as a key direction for the evolution of future wireless systems. However

in emergency rescue scenarios

traditional ILAC networks that rely on terrestrial base stations may become unavailable or severely degraded due to damage to ground infrastructure. Such infrastructure failures can result in communication coverage interruption

link quality deterioration

insufficient localization anchors

and reduced positioning accuracy

making it difficult to continuously support mission-critical services in disaster-affected areas.To address this issue

this paper proposes an unmanned aerial vehicle(UAV)-swarm-enabled ILAC network

in which multiple UAVs are deployed as flexible aerial platforms to provide temporary

distributed

and reconfigurable communication and localization services for ground users in disaster-affected regions. Furthermore

a distributed framework is proposed for the joint optimization method of UAV association

spectrum allocation

and power control to ensure efficient communication and positioning services

thereby supporting the successful execution of critical tasks such as emergency rescue. First

a user positioning model based on double-sided two-way ranging is established to describe the ranging relationship between aerial UAV anchors and ground users

as well as the impact of ranging measurements and anchor selection on positioning accuracy. On this basis

the coupling relationship among communication access

positioning anchor association

spectrum sharing

and transmit power allocation is further characterized. Then

a joint optimization problem is formulated with the objective of maximizing the minimum user throughput

while considering positioning accuracy requirements

UAV association constraints

sub-channel allocation constraints

and power constraints. Since the formulated problem involves both discrete association decisions and continuous resource allocation variables

and the communication and positioning performances are strongly coupled through shared UAV anchor nodes and wireless resources

the problem is highly non-convex and difficult to solve directly by conventional centralized optimization methods. To tackle this complexity

the original problem is decomposed into two subproblems: UAV association

power control

and sub-channel allocation. For the first subproblem

a three-dimensional fast aerial anchor selection method is proposed. By introducing spatial partitioning

the proposed method reduces the search space of candidate aerial anchors and enables rapid association between user communication access points and positioning anchors

thereby lowering the computational complexity of UAV association while preserving positioning performance. For the second subproblem

a multi-agent proximal policy optimization-based joint power control and sub-channel allocation algorithm is proposed. By leveraging distributed multi-agent learning

users can learn coordinated resource allocation policies under local network observations

so as to jointly determine spectrum and power configurations in dynamic multi-user scenarios.Simulation comparisons with multiple baseline algorithms demonstrate that the proposed method can effectively improve the minimum user throughput and enhance communication fairness among users while satisfying positioning accuracy constraints. Moreover

under the same network scenario settings

the proposed method achieves superior positioning performance

indicating its effectiveness in jointly balancing communication efficiency and positioning reliability. These results show that the proposed UAV swarm-enabled ILAC framework provides a feasible and effective solution for supporting efficient communication and reliable positioning services in emergency rescue scenarios.

关键词

Keywords

references

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