Limited Sampling Spatial Interpolation Evaluation for 3D Radio Environment Mapping
The increasing densification and diversification of modern and upcoming wireless networks have become an important motivation for the development of agile spectrum sharing. Radio environment maps (REMs) are a basic tool for spectrum utilisation characterisation and adaptive resource allocation, but...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/22/9110 |
| _version_ | 1797457861658279936 |
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| author | Antoni Ivanov Krasimir Tonchev Vladimir Poulkov Agata Manolova Atanas Vlahov |
| author_facet | Antoni Ivanov Krasimir Tonchev Vladimir Poulkov Agata Manolova Atanas Vlahov |
| author_sort | Antoni Ivanov |
| collection | DOAJ |
| description | The increasing densification and diversification of modern and upcoming wireless networks have become an important motivation for the development of agile spectrum sharing. Radio environment maps (REMs) are a basic tool for spectrum utilisation characterisation and adaptive resource allocation, but they need to be estimated through accurate interpolation methods. This work evaluated the performance of two established algorithms for spatial three-dimensional (3D) data collected in two real-world scenarios: indoors, through a mechanical measuring system, and outdoors, through an unmanned aerial vehicle (UAV) for measurement collection. The investigation was undertaken for the complete dataset on two-dimensional (2D) planes of different altitudes and for a subset of limited samples (representing the regions of interest or RoIs), which were combined together to describe the spatial 3D environment. A minimum error of −9.5 dB was achieved for a sampling ratio of 21%. The methods’ performance and the input data were analysed through the resulting Kriging error standard deviation (STD) and the STD of the distances between the measurement and the estimated points. Based on the results, several challenges for the interpolation performance and the analysis of the spatial RoIs are described. They facilitate the future development of 3D spectrum occupancy characterisation in indoor and UAV-based scenarios. |
| first_indexed | 2024-03-09T16:28:51Z |
| format | Article |
| id | doaj.art-d1ba1b8238664e4791da832c33b4d816 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T16:28:51Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d1ba1b8238664e4791da832c33b4d8162023-11-24T15:05:22ZengMDPI AGSensors1424-82202023-11-012322911010.3390/s23229110Limited Sampling Spatial Interpolation Evaluation for 3D Radio Environment MappingAntoni Ivanov0Krasimir Tonchev1Vladimir Poulkov2Agata Manolova3Atanas Vlahov4Faculty of Telecommunications, Technical University of Sofia, 1000 Sofia, BulgariaFaculty of Telecommunications, Technical University of Sofia, 1000 Sofia, BulgariaFaculty of Telecommunications, Technical University of Sofia, 1000 Sofia, BulgariaFaculty of Telecommunications, Technical University of Sofia, 1000 Sofia, BulgariaIntelligent Communication Infrastructure Laboratory, Sofia Tech Park, 1784 Sofia, BulgariaThe increasing densification and diversification of modern and upcoming wireless networks have become an important motivation for the development of agile spectrum sharing. Radio environment maps (REMs) are a basic tool for spectrum utilisation characterisation and adaptive resource allocation, but they need to be estimated through accurate interpolation methods. This work evaluated the performance of two established algorithms for spatial three-dimensional (3D) data collected in two real-world scenarios: indoors, through a mechanical measuring system, and outdoors, through an unmanned aerial vehicle (UAV) for measurement collection. The investigation was undertaken for the complete dataset on two-dimensional (2D) planes of different altitudes and for a subset of limited samples (representing the regions of interest or RoIs), which were combined together to describe the spatial 3D environment. A minimum error of −9.5 dB was achieved for a sampling ratio of 21%. The methods’ performance and the input data were analysed through the resulting Kriging error standard deviation (STD) and the STD of the distances between the measurement and the estimated points. Based on the results, several challenges for the interpolation performance and the analysis of the spatial RoIs are described. They facilitate the future development of 3D spectrum occupancy characterisation in indoor and UAV-based scenarios.https://www.mdpi.com/1424-8220/23/22/9110interpolationKrigingradio environment mapsregion of interestvolumetric measurements |
| spellingShingle | Antoni Ivanov Krasimir Tonchev Vladimir Poulkov Agata Manolova Atanas Vlahov Limited Sampling Spatial Interpolation Evaluation for 3D Radio Environment Mapping Sensors interpolation Kriging radio environment maps region of interest volumetric measurements |
| title | Limited Sampling Spatial Interpolation Evaluation for 3D Radio Environment Mapping |
| title_full | Limited Sampling Spatial Interpolation Evaluation for 3D Radio Environment Mapping |
| title_fullStr | Limited Sampling Spatial Interpolation Evaluation for 3D Radio Environment Mapping |
| title_full_unstemmed | Limited Sampling Spatial Interpolation Evaluation for 3D Radio Environment Mapping |
| title_short | Limited Sampling Spatial Interpolation Evaluation for 3D Radio Environment Mapping |
| title_sort | limited sampling spatial interpolation evaluation for 3d radio environment mapping |
| topic | interpolation Kriging radio environment maps region of interest volumetric measurements |
| url | https://www.mdpi.com/1424-8220/23/22/9110 |
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