Evidence map›Paper›PMID 39870648›Full record

ArticleScientific reports2025

UAV selection for high-speed train communication using OTFS modulation.

Ehab Mahmoud Mohamed, Sherief Hashima

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ehab Mahmoud Mohamed *Department of Electrical Engineering, College of Engineering in Wadi Addawasir, Prince Sattam Bin Abdulaziz University, 11991, Wadi Addawasir, Saudi Arabia. ehab_mahmoud@aswu.edu.eg.
Sherief Hashima *Computational Learning Theory Team, RIKEN-Advanced Intelligence Project, Fukuoka, 819-0395, Japan.

Funding

JSPS KAK- ENHI JP21K14162 and JP22H03649Prince Sattam bin Abdulaziz University (PSAU/2024/R/1446)
6 · The paper itself

Abstract

Providing continuous wireless connectivity for high-speed trains (HSTs) is challenging due to their high speeds, making installing numerous ground base stations (BSs) along the HST route an expensive solution, particularly in rural and wilderness areas. This paper proposes using multiple unmanned aerial vehicles (UAVs) to deliver high data rate wireless connectivity for HSTs, taking advantage of their ability to fly, hover, and maneuver at low altitudes. However, autonomously selecting the optimal UAV by the HST is challenging. The chosen UAV should maximize the HST's achievable data rate and provide an extended HST coverage period to minimize frequent UAV handovers constrained by the UAV's limited battery capacity. The optimization challenge arises from accurately estimating each UAV's expected coverage period for the HST, given both are moving at high speeds and the UAV's flying altitude is unknown to the HST. This paper utilizes the estimated HST-UAV channel parameters in the delay-doppler (DD) domain, employing orthogonal time frequency space (OTFS) modulation, to estimate the relative speeds between the HST and UAVs, as well as the UAVs' flying altitudes. Based on these estimates, HST can predict the maximum coverage period each UAV provides, allowing for selecting the best UAV while considering their remaining battery capacities. Numerical analysis demonstrates the effectiveness of the proposed approach compared to other benchmarks in various scenarios.

Identifiers

PMID39870648
PMCPMC11772608

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.