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Record W4393352883 · doi:10.3390/electronics13071295

A Highly Flexible Passive/Active Discrete-Time Delta-Sigma Receiver

2024· article· en· W4393352883 on OpenAlexaff
Minh Tien Nguyen, Chadi Jabbour, Karim Ben Kalaia, Hanh‐Phuc Le, Ngoc Nguyen, Van-Tam Nguyen

Bibliographic record

VenueElectronics · 2024
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsDelta-sigma modulationElectronic engineeringLinearityDynamic rangeIntermediate frequencyCMOSRadio frequencyBandwidth (computing)Quantization (signal processing)Noise shapingAmplifierEngineeringElectrical engineeringComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

This paper presents a fourth-order discrete-time direct RF-to-digital Delta-Sigma receiver architecture for flexible receivers with a wide frequency range. The use of a current-driven passive mixer with RF feedback enables high-Q bandpass filtering and relaxes the linearity requirement of the RF amplifier. In addition, the reconfigurable passive/active loop filter offers a good compromise between power consumption, linearity, and dynamic range. The other important feature of the proposed architecture is the use of a sampling frequency that is a divisor of the LO frequency. This solves several problems such as the upmixing of quantization noise, the need to reconfigure the Delta-Sigma loop when changing the LO frequency, and the use of two independent clocks for the LO and the sampling frequency. The circuit was implemented using 65 nm CMOS technology. The I/Q Direct Delta-Sigma receiver has an RF bandwidth of 20 MHz and a sampling frequency of 400 MHz. Measurement results show a very high dynamic range of up to 80 dB with a peak SNDR of 46 dB for a power consumption of 46 mW at 800 MHz.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.894
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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