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Record W7130674650 · doi:10.1109/swc65939.2025.00086

Beamforming and Performance Analysis for Interference Systems with UAV and Ground Users

2025· article· W7130674650 on OpenAlexaff
Azar Hakimi, Yindi Jing, Xinwei Yu

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicUAV Applications and Optimization
Canadian institutionsStatistics CanadaUniversity of Alberta
Fundersnot available
KeywordsBeamformingInterference (communication)Telecommunications linkBase stationWSDMAAntenna (radio)

Abstract

fetched live from OpenAlex

In this work, we explore the downlink of an interference system where two base stations (BSs) with uniform linear antenna arrays serve both unmanned aerial vehicle (UAV) and ground users over shared resources. UAV channels are modeled as line-of-sight (LOS) while ground user channels follow Rayleigh fading. We introduce a transmit beamforming design to eliminate interference to UAV users while maximizing signal-to-interference-plus-noise ratios (SINRs) for all users. Analytical expressions for achievable UAV rates and average achievable ground user rates are derived, and the average achievable rate region is studied. Simulation results show the effectiveness of the proposed design and validate analytical accuracy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.657
Threshold uncertainty score0.607

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.205
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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