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Record W3116341528 · doi:10.1109/lcomm.2020.3045719

SVD-Based Design for Non-Orthogonal Frequency Division Multiplexing

2020· article· en· W3116341528 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 Communications Letters · 2020
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingOrthogonalitySpectral efficiencyAlgorithmCyclic prefixAdditive white Gaussian noiseComputer scienceSingular value decompositionBandwidth (computing)MultiplexingChannel (broadcasting)MathematicsElectronic engineeringTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Conventional non-orthogonal frequency division multiplexing (NFDM) suffers from inter-channel interference (ICI) due to the loss of orthogonality among subcarriers. The ICI significantly degrades system performance and complicates the design of the receiver. In this letter we propose a novel NFDM design based on singular-value decomposition of the modified Fourier matrix, which is able to completely eliminate ICI over an AWGN channel, while enjoying a simple transceiver structure. We also introduce a novel cyclic prefix extension scheme for the proposed NFDM design which is shown to reduce out-of-band emissions as compared to the traditional method of NFDM cyclic prefix extension. The spectral efficiency of our proposed technique is investigated and carefully compared to that of OFDM. The results show that the proposed scheme achieves up to 23% higher bandwidth efficiency than OFDM while meeting the same target bit error rate performance.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.751
Threshold uncertainty score0.713

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 head0.083
GPT teacher head0.281
Teacher spread0.198 · 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