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Record W2298665881 · doi:10.1049/iet-map.2015.0408

Mm‐waves propagation measurements in underground mine using directional MIMO antennas

2016· article· en· W2298665881 on OpenAlexaff
Mohamad Ghaddar, Larbi Talbi, Mourad Nedil, Ismail Ben Mabrouk, Tayeb A. Denidni

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2016
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité du Québec en OutaouaisUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsMIMOAcousticsGeologyComputer scienceElectronic engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

This study reveals the interests towards the use of directional (D)‐multiple‐input and multiple‐output (MIMO) setup as a potential solution to overcome the severe propagation loss of inherent line of sight (LOS) mm‐waves communications in underground mine. To show the advantages of the proposed D‐MIMO, two separate measurement campaigns are assessed in a comparative way; the first uses a single‐input single‐output (SISO), while the second uses a 2 × 2 D‐MIMO system. Furthermore, due to the unavoidable blockage of direct LOS in underground mines, the miner's shadowing effects (NLOS‐MSE) are investigated. Thus, using both D‐SISO and D‐MIMO setup, the channel propagation characteristics are extracted and investigated with and without the presence of a miner completely blocking LOS. Under LOS, results show that, besides offering a reliable mm‐waves link budget, D‐MIMO restrains the average path loss (PL) by more than 4.7 dB, further suppresses the root mean square delay to 1.85 ns and offers an average capacity of 23.3 bits/s/Hz. As a miner completely blocks LOS, the proposed D‐MIMO system has shown a greater signal ability to overcome the effects of a miner's body; NLOS‐MSE compensation of about 4.3 dB and a capacity gain of 19.6 bits/s/Hz have been achieved over the conventional SISO system.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.034
GPT teacher head0.242
Teacher spread0.208 · 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.

Study designBench or experimental
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

Citations22
Published2016
Admission routes1
Has abstractyes

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