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Record W2087361247 · doi:10.1109/icc.2012.6364116

MAC performance improvement in UAV ad-hoc networks with full-duplex radios and multi-packet reception capability

2012· article· en· W2087361247 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFull-Duplex Wireless Communications
Canadian institutionsCommunications Research Centre CanadaCarleton University
Fundersnot available
KeywordsComputer scienceComputer networkWireless ad hoc networkNetwork packetControl channelMobile ad hoc networkVehicular ad hoc networkDuplex (building)WirelessTelecommunications linkTelecommunications

Abstract

fetched live from OpenAlex

Recent advances in interference cancellation and signal processing techniques can enable full-duplex radios and multi-packet reception (MPR) capability, which will have significant impacts on the medium access control (MAC) design. In this paper, we study the MAC design in UAV ad-hoc networks with full-duplex radios and MPR. To efficiently handle the highly mobile environment of a UAV ad-hoc network, a token-based technique is used for updating information in the network. The MAC scheme in the presence of perfect and imperfect channel state information are formulated as a combinatorial optimization problem and a discrete stochastic optimization problem, respectively. Simulation results are presented to show the effectiveness of the proposed MAC.

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.

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: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.013
GPT teacher head0.213
Teacher spread0.199 · 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

Quick stats

Citations23
Published2012
Admission routes1
Has abstractyes

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