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Cluster-Based Characterization and Modeling for UAV Air-to-Ground Time-Varying Channels.
- Source :
- IEEE Transactions on Vehicular Technology; Jul2022, Vol. 71 Issue 7, p6872-6883, 12p
- Publication Year :
- 2022
-
Abstract
- With the deep integration between the unmanned aerial vehicle (UAV) and wireless communication, UAV-based air-to-ground (AG) propagation channels need more detailed descriptions and accurate models. In this paper, we aim to conduct cluster-based characterization and modeling for AG channels. To our best knowledge, this is the first study that concentrates on the clustering and tracking of multipath components (MPCs) for time-varying AG channels. Based on measurement data at 6.5 GHz with a bandwidth of 500 MHz, we first estimate potential MPCs utilizing the space-alternating generalized expectation-maximization (SAGE) algorithm. Then, we cluster the extracted MPCs by employing K-Power-Means (KPM) algorithm under multipath component distance (MCD) measure. For characterizing time-variant clusters, we exploit a clustering-based tracking (CBT) method, which efficiently quantifies the survival lengths of clusters. Ultimately, we establish a cluster-based channel model, and validations illustrate the accuracy of the proposed model. This work not only promotes a better understanding of AG propagation channels but also provides a general cluster-based AG channel model with certain extensibility. [ABSTRACT FROM AUTHOR]
- Subjects :
- WIRELESS communications
Subjects
Details
- Language :
- English
- ISSN :
- 00189545
- Volume :
- 71
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Vehicular Technology
- Publication Type :
- Academic Journal
- Accession number :
- 158023165
- Full Text :
- https://doi.org/10.1109/TVT.2022.3168073