Path loss
Millimeter-wave (mmWave) spectrum with wide bandwidth provides a promising solution to enable high throughput in next-generation wireless agricultural networks, characterized by swarms of autonomous ground vehicles, unmanned aerial vehicles (UAVs), and connected agricultural machinery. However, channel models at mmWave frequencies in agricultural environments remain elusive. Moreover, agricultural field channels bear notable distinctions from urban and rural macrocellular network channels due to the dynamic crop growth behavior.
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5G-NR is beginning to be widely deployed in the mmWave frequencies in urban areas in the US and around the world. Due to the directional nature of mmWave signal propagation, improving performance of such deployments heavily relies on beam management and deployment configurations.
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The experiment is based on the open source RSRP data provided by Huawei Technologies Co., LTD. It measures RSRP of 415,244 signal receiving points in 180 dense urban communication cells.
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All data used for model evaluation and training are from the 16th Chinese Post-Graduate Mathematical Contest in Modeling (CPGMCM). The dataset is measured by HUAWEI TECHNOLOGIES CO., LTD, which includes engineering parameter data, map data and RSRP label data of multiple communities. And the dataset is sponsored by the Ministry of Education's Degree and Graduate Education Development Center.
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Drive testing is a common practice by mobile operators to evaluate the performance and coverage of their deployed mobile communication systems. Drive testing is, however, a very expensive practice. Furthermore, due to the complexity of future 5G mobile networks, accurate and efficient ways of optimizing and evaluating coverage are needed. The dataset contains measurements from a deployed LTE-A mobile communication system and corresponding satellite images.
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