面向5G网络的低空频谱地图抗干扰测绘系统设计与实现

Design and Implementation of an Anti-Interference Radio Mapping Platform for Low-Altitude in 5G Networks

  • 摘要: 随着低空经济的迅速发展,利用地面第五代移动通信(5th Generation, 5G)网络为无人机等低空用户提供广域、可靠的无线覆盖的重要性已逐渐凸显。然而,低空覆盖面临着由地面基站天线旁瓣覆盖导致的低空信号盲区,以及开放信道环境带来的复杂空间异构干涉场等诸多难题,传统测量方法难以在复杂的强干扰环境中准确测绘频谱信息。为应对上述问题,本文设计并实现了一套面向5G网络的低空频谱地图抗干扰测绘系统。在算法层面,本文提出了一种基于时域联合建模与估计的多基站信号分析方法。该方法在最大似然估计框架下,利用同一基站多波束共享物理参数的先验,并结合连续干扰消除迭代框架,显著提升了在密集强干扰环境下对微弱信号的检测与参数估计精度。在系统层面,本文研制了一套以无人机和软件无线电为核心的轻量化信号连续采集平台,并设计了基于共享内存的双进程异步处理软件架构。该架构将要求严苛的实时性数据接收任务与非确定性的数据存储任务进行了有效解耦,通过高效的进程间通信,在轻量级机载计算平台上实现了高速同相/正交(In-phase/Quadrature, I/Q)数据的无损、连续采集。最后通过在真实城市环境中的部署与实测验证,结果表明,本文所提出的系统与算法相较于基线方案,在弱信号检测灵敏度、多波束分辨能力以及构建无线电地图的完整性方面均展现出显著优势。本研究为刻画5G低空电磁环境提供了有效的技术方案,其测绘结果可为后续的网络侧三维覆盖优化与终端侧通信感知路径规划提供关键数据支撑。

     

    Abstract: With the rapid development of the low-altitude economy, the importance of leveraging terrestrial 5th Generation (5G) networks to provide wide-area and reliable wireless coverage for low-altitude users, such as Unmanned Aerial Vehicles (UAVs), has become increasingly important. However, this approach faces numerous challenges, including signal blind spots in low-altitude areas caused by the sidelobe coverage of terrestrial base station antennas, and a complex, spatially heterogeneous interference field resulting from the open-channel environment. Consequently, conventional measurement methods struggle to accurately characterize the true channel conditions. To address these issues, this study designed and implemented an anti-interference low-altitude radio mapping system for 5G networks. A multi-base station signal analysis method based on time-domain joint modeling and estimation was developed. This method, under a Maximum Likelihood Estimation (MLE) framework, leverages the prior knowledge of shared physical parameters among multiple beams from the same base station and incorporates an iterative Successive Interference Cancellation (SIC) framework. This significantly enhances the accuracy when detecting weak signals and estimating parameters in dense environments with strong interference. Systematically, a lightweight signal acquisition platform centered around a UAV and a software radio was developed, and a dual-process asynchronous processing software architecture based on shared memory was designed. This architecture effectively decouples the stringent real-time task of data reception from the non-deterministic task of data storage. Through efficient inter-process communication, it achieves the lossless and continuous acquisition of high-speed In-phase/Quadrature (I/Q) data on a lightweight airborne computing platform. Deployment and field measurements in a real urban environment demonstrated that the proposed system and algorithms have significant advantages over baseline solutions in terms of weak signal detection sensitivity, multi-beam resolution capability, and the completeness of the constructed radio map. This research provides an effective technical solution for characterizing the 5G low-altitude electromagnetic environment, and its mapping results can offer crucial data support for subsequent network-side 3D coverage optimization and terminal-side communication-aware path planning.

     

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