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Record W3212069388 · doi:10.1109/twc.2022.3211327

Faster-Than-Nyquist Signaling for MIMO Communications

2022· article· en· W3212069388 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Wireless Communications · 2022
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaTürkiye Bilimsel ve Teknolojik Araştırma Kurumu
KeywordsMIMOPrecodingSpectral efficiencyNyquist–Shannon sampling theoremComputer scienceTransmission (telecommunications)Frequency domainChannel capacityMulti-user MIMOTelecommunicationsElectronic engineeringTopology (electrical circuits)MathematicsChannel (broadcasting)Engineering

Abstract

fetched live from OpenAlex

Faster-than-Nyquist (FTN) signaling is a non-orthogonal transmission technique, which has the potential to provide significant spectral efficiency improvement. This paper studies the capacity of FTN signaling for both frequency flat and for frequency selective (FS) multiple-input multiple-output (MIMO) channels. As FTN is another reason of frequency selectivity, we find that precoding in time (or equivalently spectrum shaping in frequency) and waterfilling in spatial domain is capacity achieving for frequency flat MIMO channels with FTN. Meanwhile, waterfilling in both spatial domain and spectrum domain, followed by spectrum shaping, is capacity achieving for FS MIMO channels with FTN.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.961
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 studies0.0030.000
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.281
Teacher spread0.237 · 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