RT-based dataset (V2.0) for 3D radio map under dynamic built-up scenario (1.25kmX1.25km)

The radio map, spectrum environment map (SEM), or RSSI map, can visualize the information of invisible electromagnetic spectrum, and is vital for monitoring, management, and security of spectrum
resources in cognitive radio (CR) networks. It is useful for the abnormal spectral activity detection,
radiation source localization, spectrum resource management, etc.

The performance of different 3D SEM construction methods should be compared based on the data under realistic scenarios. However, 3D RSSI data collecting by a spectrum sensing system is quite different and high costing. Moreover, it's unrepeatable and uncontrolable. So we obtained the RSSI by the RT-based calculation method under urban scenario . It includes two datasets as
1) dynamic scenario (radiation sources are moving for 600 seconds): Collecting data at the height of 2m, 25m, 50m and 80m.
2) static scenario (radiation sources are fixed) : Collecting data at the height of 2m, 10m, 20m, 30m, 40m, 50m, 80m.

The dataset has been applied and validated in the following references.
[1]. J. Wang, Q. Zhu, Z. Lin, Q. Wu, Y. Huang, X. Cai, et al., “Sparse Bayesian Learning-Based 3D Radio Environment Map Construction—Sampling Optimization, Scenario-Dependent Dictionary Construction and Sparse Recovery,” IEEE Transactions on Cognitive Communications and Networking, vol.10, pp.80-93, Feb. 2024.
[2]. J. Wang, Q. Zhu, Z. Lin, J. Chen, G. Ding, Q. Wu, G. Gu, Q. Gao, "Sparse Bayesian Learning-Based Hierarchical Construction for 3D Radio Environment Maps Incorporating Channel Shadowing," IEEE Transactions on Wireless Communications, vol.23, no.10, pp.14560-14574, Oct. 2024.
[3]. Q. Gao, Q. Zhu, Z. Lin et al., "Time-variant radio map reconstruction with optimized distributed sensors in dynamic spectrum environments,", IEEE Internet of Things Journal, early access, Feb. 2025, doi: 10.1109/JIOT.2025.3545542.
[4]. Y. Zhao, Q. Zhu, Z. Lin, L. Guo, Q. Wu, J. Wang, W. Zhong. “Temporal prediction for spectrum environment maps with moving radiation sources,” IET Communications, vol. 17, no. 5, pp. 538–548, 2023.

More details and instrucitons can be found in the guidemanual.pdf.

搜集汇总

背景与挑战

背景概述

这是一个基于射线追踪的3D无线电地图数据集，用于动态建筑场景（1.25km×1.25km区域），包含动态和静态两种场景。数据集通过模拟方法生成，避免了实际采集的高成本和不可控性，数据以.mat格式提供，覆盖不同高度，并已应用于多篇学术论文验证。