MétaCan
Menu
Back to cohort
Record W2964050133 · doi:10.1109/lwc.2018.2803825

Channel Diagonalization for Cloud Radio Access

2018· article· en· W2964050133 on OpenAlexafffund
Liang Liu, Pratik Patil, Wei Yu

Bibliographic record

VenueIEEE Wireless Communications Letters · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTelecommunications linkComputer scienceMIMOBasebandMulti-user MIMOPrecodingChannel (broadcasting)Singular value decompositionComputer networkTopology (electrical circuits)Electronic engineeringAlgorithmBandwidth (computing)EngineeringElectrical engineering

Abstract

fetched live from OpenAlex

The diagonalization of a conventional multiple-input multiple-output (MIMO) channel into parallel and independent subchannels via singular value decomposition (SVD) is a fundamental strategy that allows the MIMO channel capacity to be achieved using scalar channel codes. This letter establishes a similar channel diagonalization result for the uplink and the downlink of a cloud radio access network (C-RAN), in which a central processor is connected to a remote radio head (RRH) serving a single user via rate-limit digital fronthaul carrying the compressed baseband signal. Specifically, we show that the diagonalization of the MIMO channel between the RRH and the user via SVD and the subsequent independent and parallel quantization of scalar signals and channel coding in each of the subchannels is optimal. This letter establishes this fact using the majorization theory. Further, an uplink-downlink duality for the multiple-antenna C-RAN is identified for this single-user case.

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 score0.977
Threshold uncertainty score0.774

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 science0.0010.000
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 head0.287
Teacher spread0.253 · 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
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueIEEE Wireless Communications LettersSame topicAdvanced MIMO Systems OptimizationFrench-language works237,207