Matteo Bernabe, David Lopez-Perez, Nicola Piovesan, Giovanni Geraci, David Gesbert
{"title":"Optimal SSB Beam Planning and UAV Cell Selection for 5G Connectivity on Aerial Highways","authors":"Matteo Bernabe, David Lopez-Perez, Nicola Piovesan, Giovanni Geraci, David Gesbert","doi":"arxiv-2409.01812","DOIUrl":null,"url":null,"abstract":"In this article, we introduce a method to optimize 5G massive multiple-input\nmultiple-output (mMIMO) connectivity for unmanned aerial vehicles (UAVs) on\naerial highways through strategic cell association. UAVs operating in 3D space\nencounter distinct channel conditions compared to traditional ground user\nequipment (gUE); under the typical line of sight (LoS) condition, UAVs perceive\nstrong reference signal received power (RSRP) from multiple cells within the\nnetwork, resulting in a large set of suitable serving cell candidates and in\nlow signal-to-interference-plus-noise ratio (SINR) due to high interference\nlevels. Additionally, a downside of aerial highways is to pack possibly many\nUAVs along a small portion of space which, when taking into account typical LoS\npropagation conditions, results in high channel correlation and severely limits\nspatial multiplexing capabilities. In this paper, we propose a solution to both problems based on the suitable\nselection of serving cells based on a new metric which differs from the\nclassical terrestrial approaches based on maximum RSRP. We then introduce an\nalgorithm for optimal planning of synchronization signal block (SSB) beams for\nthis set of cells, ensuring maximum coverage and effective management of UAVs\ncell associations. Simulation results demonstrate that our approach\nsignificantly improves the rates of UAVs on aerial highways, up to four times\nin achievable data rates, without impacting ground user performance.","PeriodicalId":501082,"journal":{"name":"arXiv - MATH - Information Theory","volume":"7 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - MATH - Information Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.01812","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this article, we introduce a method to optimize 5G massive multiple-input
multiple-output (mMIMO) connectivity for unmanned aerial vehicles (UAVs) on
aerial highways through strategic cell association. UAVs operating in 3D space
encounter distinct channel conditions compared to traditional ground user
equipment (gUE); under the typical line of sight (LoS) condition, UAVs perceive
strong reference signal received power (RSRP) from multiple cells within the
network, resulting in a large set of suitable serving cell candidates and in
low signal-to-interference-plus-noise ratio (SINR) due to high interference
levels. Additionally, a downside of aerial highways is to pack possibly many
UAVs along a small portion of space which, when taking into account typical LoS
propagation conditions, results in high channel correlation and severely limits
spatial multiplexing capabilities. In this paper, we propose a solution to both problems based on the suitable
selection of serving cells based on a new metric which differs from the
classical terrestrial approaches based on maximum RSRP. We then introduce an
algorithm for optimal planning of synchronization signal block (SSB) beams for
this set of cells, ensuring maximum coverage and effective management of UAVs
cell associations. Simulation results demonstrate that our approach
significantly improves the rates of UAVs on aerial highways, up to four times
in achievable data rates, without impacting ground user performance.