Interference Management in Private 5G Networks via Interference Source Localization and Radio Environment Map Construction

Private 5G (P5G) networks are driving large-scale industrial and enterprise internet of things (IoT) deployments. However, uncoordinated P5G deployments can lead to unintended signal leakage and inter-network interference between neighboring P5G systems. Constructing a radio environment map (REM) is a practical way to visualize and manage such interference. It typically relies on spatially regular measurements, but drive-test-based data are often sparse and spatially irregular. Furthermore, since signal strength inherently includes path loss, the spatial distribution becomes non-stationary and unsuitable for direct interpolation under sparse and spatially irregular sampling conditions. Removing the path loss component requires knowledge of the interference source location, but the source location is generally unknown in real-world scenarios. To address these challenges, this paper proposes a measurement-based method to detect, localize, and map interference leakage. A novel localization algorithm is introduced to estimate the leakage source using only sparse and irregular measurements. The estimated source location enables decomposition of path loss and shadow fading, supporting accurate REM construction through spatial interpolation. Field measurements validate the effectiveness of the proposed approach in enabling interference diagnosis and providing spatial evidence aligned with regulatory requirements for safe coexistence between neighboring P5G networks.