DEMO Abstract: An UAV-based 3D Spectrum Real-time Mapping System

Zhu, Qiuming; Zhao, Yi; Huang, Yang; Lin, Zhipeng; Wang, Lu HanJie; Bai, Yunpeng; Lan, Tianxu; Zhou, Fuhui; Wu, Qihui

doi:10.1109/infocomwkshps54753.2022.9798206

Cited by 12 publications

(9 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The techniques mentioned above solely concentrate on creating two-dimensional (2D) maps using information gathered from the ground or from sources of low-altitude radiation. The inclusion of aerial communication platforms should be given due consideration while examining the expansion of space-air-ground integrated communication networks, as they contribute to the development of a comprehensive 3D spectrum map [20].…”

Section: Optimization For Sampling Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Spectrum map construction optimisation schemes: Sampling and prediction

2024

ACE

View full text Add to dashboard Cite

The proliferation of electromagnetic devices presents a significant challenge in developing effective techniques for spectrum monitoring, management, and security. The utilization of spectrum cartography has been acknowledged as a viable approach to address the aforementioned difficulties. This latter presents a variety of techniques aimed at enhancing the efficiency of the current spectrum mapping methodology. The subject matter can be categorized into two primary components, namely sampling and spectrum prediction. Sampling part includes methods to find the most valuable sampling points and methods of sampling hardware optimization. Spectrum prediction includes algorithms utilizing frequency-spatial reasoning techniques to estimate the target spectrum map by data from the nearby area, and algorithms utilizing ROSMP framework to estimate the spectrum map from past data. The introduction of techniques is divided into the 2 types, together with key algorithms and devices used in each method. Additionally, the letter lists some drawbacks of certain methods and discuss their development prospects.

show abstract

Section: Optimization For Sampling Methodsmentioning

confidence: 99%

“…In [20], a prototype for a spectrum mapping system based on unmanned aerial vehicles (UAVs) is introduced. The system is designed to autonomously navigate along a predetermined path and collect three-dimensional data on the electromagnetic spectrum.…”

Section: Optimization For Sampling Methodsmentioning

confidence: 99%

Spectrum map construction optimisation schemes: Sampling and prediction

2024

ACE

View full text Add to dashboard Cite

show abstract

“…The former methods build a radio map that contains a large number of positions and electromagnetic data in a 3D space [98], while the latter methods build a radio map as a function of geographic locations [99,100]. Data-driven methods require electromagnetic data to be evenly distributed, while model-driven methods need extra channel information [101]. However, it is difficult to build a radio map in an urban area where buildings are irregular and radio propagates complicatedly.…”

Section: Problem Descriptionmentioning

confidence: 99%

Graphic Neural Network based GPS Spoofing Detection for Cellular-Connected UAV swarm

Dang

Karakoç

Jäntti

2023

2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)

View full text Add to dashboard Cite

show abstract

“…In [27], the author constructed a channel shadow map (CSM) based on a spatial correlation approach. The radio map or spectrum map, which is one of the typical applications of CKM [29][30][31][32], can display the spatial distribution of the received signal strength (RSS) of a single frequency point in the measurement scenario in the form of a heat map, so that the electromagnetic radiation of the measurement scenario can be directly observed.…”

Section: Introductionmentioning

confidence: 99%

“…However, it should be noted that the above CKMs and spectrum maps are usually constructed by using the simulated data [23,25,28,30,33], which is quite different from the real situation. Moreover, the measurement system is relatively simple, which can only obtain the channel knowledge of a single transceiver position [29,31]. Second, most of the current research focuses on CGM, and only [18] constructs the CPM of the strongest path, which is not enough for the research on channel characteristics.…”

Section: Introductionmentioning

confidence: 99%

Channel Knowledge Map Construction Based on a UAV-Assisted Channel Measurement System

Qiu,

Chen,

Mao

et al. 2024

Drones

Self Cite

View full text Add to dashboard Cite

With the fast development of unmanned aerial vehicles (UAVs), reliable UAV communication is becoming increasingly vital. The channel knowledge map (CKM) is a crucial bridge connecting the environment and the propagation channel that may visually depict channel characteristics. This paper presents a comprehensive scheme based on a UAV-assisted channel measurement system for constructing the CKM in real-world scenarios. Firstly, a three-dimensional (3D) CKM construction scheme for real-world scenarios is provided, which involves channel knowledge extraction, mapping, and completion. Secondly, an algorithm of channel knowledge extraction and completion is proposed. The sparse channel knowledge is extracted based on the sliding correlation and constant false alarm rate (CFAR) approaches. The 3D Kriging interpolation is used to complete the sparse channel knowledge. Finally, a UAV-assisted channel measurement system is developed and CKM measurement campaigns are conducted in campus and farmland scenarios. The path loss (PL) and root mean square delay spread (RMS-DS) are measured at different heights to determine CKMs. The measured and analyzed results show that the proposed construction scheme can effectively and accurately construct the CKMs in real-world scenarios.

show abstract

DEMO Abstract: An UAV-based 3D Spectrum Real-time Mapping System

Cited by 12 publications

References 4 publications

Spectrum map construction optimisation schemes: Sampling and prediction

Spectrum map construction optimisation schemes: Sampling and prediction

Graphic Neural Network based GPS Spoofing Detection for Cellular-Connected UAV swarm

Channel Knowledge Map Construction Based on a UAV-Assisted Channel Measurement System

Contact Info

Product

Resources

About