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Record W4404132952 · doi:10.1109/tmtt.2024.3487823

Frequency-Stitching-Based Ultrawideband Signal Generation for 6G Component/System Testing: Achieving 12-GHz Instantaneous Bandwidth and 96-Gbps Data Rate at D Band

2024· article· en· W4404132952 on OpenAlexafffund
Zi Jun Su, Ahmed Ben Ayed, Nizar Messaoudi, Patrick Mitran, Slim Boumaiza

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2024
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBandwidth (computing)Image stitchingElectronic engineeringComponent (thermodynamics)Computer scienceWidebandSIGNAL (programming language)Electrical engineeringPhysicsEngineeringTelecommunicationsOptics

Abstract

fetched live from OpenAlex

This article introduces a novel method for generating ultrawideband (UWB) modulated signals at millimeter-wave (mmW) and sub-THz frequency bands using readily available high-resolution digital-to-analog converters (DACs) with sampling rates lower than twice the target bandwidth. The method exploits the periodicity of test signals to divide them into frequency subbands, with each subband generated by a dedicated channel consisting of an IQ-DAC followed by an IQ mixer. Phase coherent local oscillators (LOs) drive the IQ mixers, and the final UWB signal is synthesized by combining the outputs of all channels. To address inherent nonidealities in the proposed UWB signal generation method, a novel calibration technique is introduced. This technique uses nonuniformly interleaved tones to correct IQ imbalances, phase and magnitude offsets across channels, and linear distortions in each RF chain. The calibration formulation ensures continuity in the phase and magnitude frequency responses across different channels. For experimental validation, the proposed method was used to generate a 256-QAM orthogonal frequency-division multiplexing (OFDM) signal at D band (149 GHz) with an instantaneous bandwidth of up to 12 GHz, achieving a peak data rate of 96 Gbps. The calibration technique effectively compensates for the nonidealities in the proposed signal generator, improving the measured error vector magnitude (EVM) and normalized mean square error (NMSE) from 82.6% and 23.8% to less than 2% and 1%, respectively, when tested with a 12-GHz bandwidth 256-QAM OFDM UWB signal. Furthermore, the method was applied to linearize a D band power amplifier driven by a 256-QAM OFDM signal with a 4-GHz modulation bandwidth. The adjacent channel power ratio (ACPR) and EVM improved from -27.8/-26 dBc and 8.5% before linearization to -42.8/-43.1 dBc and 1.2% after linearization, ensuring a linearization bandwidth over 12 GHz. These results underscore the suitability of the proposed method for generating high-quality UWB modulated signals for component testing at mmW and sub-THz frequency bands.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.727
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.045
GPT teacher head0.247
Teacher spread0.202 · 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.

Study designBench or experimental
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

Citations2
Published2024
Admission routes2
Has abstractyes

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