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Record W3082613602 · doi:10.1109/tvt.2020.3021012

Joint Scheduling and Precoding for mmWave and Sub-6GHz Dual-Mode Networks

2020· article· en· W3082613602 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

VenueIEEE Transactions on Vehicular Technology · 2020
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersChina Scholarship CouncilNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsPrecodingComputer scienceScheduling (production processes)Transmission (telecommunications)Physical layerUpper and lower boundsElectronic engineeringJoint (building)Channel (broadcasting)Computer networkWirelessEngineeringTelecommunicationsMIMOMathematics

Abstract

fetched live from OpenAlex

A millimeter wave (mmWave) and sub-6 GHz (μWave) dual-mode network can take advantages of the signals over both bands. The user scheduling in the medium access layer and the transmit precoding in the physical layer are coupled and should be optimized jointly. This work investigates the joint crosslayer optimization problems for two dual-mode systems: the full dual transmission system in which each user equipment can be scheduled over both frequency bands and the half dual transmission system in which each user equipment can only be scheduled over one band. A concave expression is adopted to lower-bound the achievable rate of each user equipment with perfect and imperfect channel estimation. Based on the lower bound, effective algorithms are proposed to solve the joint cross-layer optimization problems. The proposed algorithms can also be used for other dual-mode networks. Simulations show superiority of joint transmit precoding for the two frequency bands signals. Moreover, the full dual transmission system outperforms the half dual transmission system in terms of the minimum rate. The rate degradation of the half dual transmission system is insignificant while its implementation complexity is much lower than the full dual transmission 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.

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 score0.687
Threshold uncertainty score0.748

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 head0.023
GPT teacher head0.218
Teacher spread0.195 · 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