Rank and Condition Number Analysis for UAV MIMO Channels Using Ray Tracing

Fuente: arXiv
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Hauptverfasser: Lee, Donggu, Guvenc, Ismail
Format: Preprint
Veröffentlicht: 2023
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author Lee, Donggu
Guvenc, Ismail
author_facet Lee, Donggu
Guvenc, Ismail
contents Channel rank and condition number of multi-input multi-output (MIMO) channels can be effective indicators of achievable rates with spatial multiplexing in mobile networks. In this paper, we use extensive ray tracing simulations to investigate channel rank, condition number, and signal coverage distribution for air-to-ground MIMO channels. We consider UAV-based user equipment (UE) at altitudes of 3 m, 30 m, 70 m, and 110 m from the ground. Moreover, we also consider their communication link with a cellular base station in urban and rural areas. In particular, Centennial Campus and Lake Wheeler Road Field Labs of NC State University are considered, and their geographical information extracted from the open street map (OSM) database is incorporated into ray tracing simulations. Our results characterize how the channel rank tends to reduce as a function of UAV altitude, while also providing insights into the effects of geography, building distribution, and threshold parameters on channel rank and condition number.
format Preprint
id arxiv_https___arxiv_org_abs_2303_02779
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Rank and Condition Number Analysis for UAV MIMO Channels Using Ray Tracing
Lee, Donggu
Guvenc, Ismail
Signal Processing
Channel rank and condition number of multi-input multi-output (MIMO) channels can be effective indicators of achievable rates with spatial multiplexing in mobile networks. In this paper, we use extensive ray tracing simulations to investigate channel rank, condition number, and signal coverage distribution for air-to-ground MIMO channels. We consider UAV-based user equipment (UE) at altitudes of 3 m, 30 m, 70 m, and 110 m from the ground. Moreover, we also consider their communication link with a cellular base station in urban and rural areas. In particular, Centennial Campus and Lake Wheeler Road Field Labs of NC State University are considered, and their geographical information extracted from the open street map (OSM) database is incorporated into ray tracing simulations. Our results characterize how the channel rank tends to reduce as a function of UAV altitude, while also providing insights into the effects of geography, building distribution, and threshold parameters on channel rank and condition number.
title Rank and Condition Number Analysis for UAV MIMO Channels Using Ray Tracing
topic Signal Processing
url https://arxiv.org/abs/2303.02779