MétaCan
Menu
Back to cohort
Record W1957952408 · doi:10.1109/iscas.2003.1205528

A technique for DC-offset removal and carrier phase error compensation in integrated wireless receivers

2003· article· en· W1957952408 on OpenAlexafffund
Song Shang, Shahriar Mirabbasi, R. Saleh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsBasebandElectronic engineeringQuadrature amplitude modulationQAMComputer scienceCarrier recoveryFrequency offsetDC biasPhase noiseDirect-conversion receiverCMOSOffset (computer science)Carrier frequency offsetWirelessModulation (music)Electrical engineeringBit error rateEngineeringDemodulationOrthogonal frequency-division multiplexingTelecommunicationsVoltagePhysicsChannel (broadcasting)

Abstract

fetched live from OpenAlex

Integrated wireless receiver architectures such as direct-conversion receivers offer performance advantages over the conventional heterodyne-based receivers in terms of power consumption, size and implementation cost. The use of these monolithic receivers, however, has been limited mainly due to low-frequency disturbances, namely, DC-offset and 1/f noise (particularly in CMOS implementations). AC-coupling is a cost-effective method to minimize these low-frequency disturbances, but results in baseline wander effects, especially in spectrally efficient modulation schemes such as quadrature amplitude modulation (QAM) whose baseband signal spectrum contains a significant amount of energy near DC. In this work, the quantized feedback (QFB) technique is used to mitigate the baseline wander effect. The QFB block is extended to a complex (in mathematical sense) system that also compensates for carrier phase errors in the receiver local oscillator (LO). Simulation results demonstrate the effectiveness of this complex QFB technique.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.742

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 science0.0000.000
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 head0.022
GPT teacher head0.260
Teacher spread0.238 · 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 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

Citations7
Published2003
Admission routes2
Has abstractyes

Explore more

Same topicRadio Frequency Integrated Circuit DesignFrench-language works237,207