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Record W2914192852 · doi:10.1049/el.2018.8070

Achievable rate of hybrid precoding for hardware impaired MIMO underground mine channel

2019· article· en· W2914192852 on OpenAlexaff
Widad Belaoura, Khalida Ghanem, Muhammad Zeeshan Shakir, Mourad Nedil, Hicham Bousbia-Salah

Bibliographic record

VenueElectronics Letters · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsPrecodingMIMOChannel (broadcasting)Computer scienceElectronic engineeringZero-forcing precodingEngineeringComputer hardwareTelecommunications

Abstract

fetched live from OpenAlex

Hybrid precoding has become a well‐accepted approach to enhance the achievable rate in the adverse millimetre‐wave (mm‐Wave) MIMO channels. Transceiver impairments are inherent to any practical communication system, yet they are generally omitted when investigating the performance of wireless systems. More particularly, for the case of mm‐Wave underground channels, no study has been reported yet. To overcome this limitation, in this Letter, a new architecture encompassing hybrid precoded mm‐Wave MIMO structure, in which the hardware impairments have been incorporated in the transceiver processing, is presented. Furthermore, the geometrical one ring model is applied on the underground mm‐Wave measured channel in which the architecture is tested.

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 score0.582
Threshold uncertainty score0.829

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 head0.007
GPT teacher head0.202
Teacher spread0.194 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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