Dataset for 3D radio (RSSI) map under urban scenario (1.25kmX1.25km)

Published: 9 October 2024| Version 1 | DOI: 10.17632/bn6n2639xh.1
Contributors:
qiuming zhu, jie wang, Kai Mao, zhipeng Lin, yang huang, qihui wu, weizhi zhong

Description

The radio map, radio environment map (REM), 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 REM 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 300 seconds): Collecting data at the height of 2m 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, 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, early access, 2024, doi: 10.1109/TWC.2024.3416447. [2]. 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. [3]. Q. Gao, Q. Zhu, Z. Lin, Y. Zhao, J. Wang, W. Zhong, Y. Huang, Q. Wu. “Spatial Sensor Layout Optimization for Radio Environment Map Construction,” 2024 IEEE Globecom Workshops, 2024, for publication More details and instrucitons can be found in the guidemanual.pdf.

Files

Steps to reproduce

The RT-based simulation data files include two scenarios, dynamic scenario (radiation sources are moving) data at the height of 2m and 80m, and static scenario (radiation sources are fixed) data at the height of 2m, 10m, 20m, 30m, 40m, 50m, 80m. The received signal strength data in the dynamic scenario is a .mat file in the format of a 250*250*300 tensor, where x, y represents the spatial grid dimension, z represents the time dimension, and the numerical value represents the signal strength in dBm. The file size at the height of 2m is 113MB, and the one at the height of 80m is 131MB. The received signal strength data in the static scenario is a .mat file in the format of a 250*250 matrix, where x, y represents the spatial grid dimension, and the numerical value represents the signal strength in dBm. The data file sizes for the heights of 10m, 20m, 30m, 40m, and 50m are 363KB, 385KB, 400KB, 406KB, and 405KB, respectively. The received signal strength data in the dynamic scenario is a .mat file in the format of a 250*250*300 tensor, where x, y represents the spatial grid dimension, z represents the time dimension, and the numerical value represents the signal strength in dBm. The file size at the height of 2m is 113MB, and the one at the height of 80m is 131MB. The received signal strength data in the static scenario is a .mat file in the format of a 250*250 matrix, where x, y represents the spatial grid dimension, and the numerical value represents the signal strength in dBm. The data file sizes for the heights of 10m, 20m, 30m, 40m, and 50m are 363KB, 385KB, 400KB, 406KB, and 405KB, respectively.

Institutions

Nanjing University of Aeronautics and Astronautics

Categories

Channel Modeling, Electromagnetic Spectrum, Heat Map

Funding

National Natural Science Foundation of China

No. 62271250

National Key Scientific Instrument and Equipment Development Project

No. 61827801

Licence