Measurement dataset for radio (RSSI) map under campus scenario (117mX97m)

Published: 14 October 2024| Version 1 | DOI: 10.17632/2vtwn578fn.1
Contributors:
qiuming zhu, jie wang, Zhipeng Lin, qianhao gao, Kai Mao, yang huang, qihui wu

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 REM construction methods should be compared based on the data under realistic scenarios. So we measured the signal strength under campus scenario by a spectrum sensing system. This project includes two datasets as 1) Raw received signal strength: Collecting RSSI data at the sampled positions in the ROI (117mX97m). 2) Constructed REM data: Recovery RSSI data at the unsampled positions and obtain a whole REM The dataset has been applied and validated in the following references. [1]. Q. Zhu et al., DEMO Abstract: An UAV-based 3D Spectrum Real-time Mapping System, 2022 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), New York, NY, USA, 2022, pp. 1-2. [2]. Y. Zhao, et al. Temporal prediction for spectrum environment maps with moving radiation sources, IET Communications, vol. 17, no. 5, pp. 538–548, 2023. [3] J. Wang, 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. [4]. J. Wang, ea al. Sparse Bayesian Learning-Based Hierarchical Construction for 3D Radio Environment Maps Incorporating Channel Shadowing, IEEE Transactions on Wireless Communications, IEEE Transactions on Wireless Communications, 2024, vol.23, no.10, pp.14560-14574, Oct. 2024. [5] Yang Huang, et al. Space-Based Electromagnetic Spectrum Sensing and Situation Awareness. Space Sci Technol. 2024;4:0109. DOI:10.34133/space.0109 [6]. Q. Gao, et al. 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_measuredCompus_117m_97m.pdf.

Files

Steps to reproduce

The mesured data is described by a matrix of 117*97 in a .mat file, where x and y represent the spatial grid index, and the value represents the signal strength or RSSI in dBm. The size of each file is 7KB. The measured data along the sampling trajectory is stored in the corresponding grids, while zero is set to the other grids. The constructed REM data based on measured data is described by a 117*97*5 tensor, where x, y represents the spatial grid index, z represents the time index, and the value represents the signal strength in dBm. The size of each file is 403KB.

Institutions

Nanjing University of Aeronautics and Astronautics

Categories

Channel Modeling, Electromagnetic Spectrum, Electromagnetic Remote Sensing, Heat Map

Funding

National Natural Science Foundation of China

No. 62271250

National Key Scientific Instrument and Equipment Development Projects of China

No. 61827801

Licence