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Record W2558425949 · doi:10.1109/tcsii.2017.2736252

Digitally Assisted RF-Analog Self Interference Cancellation for Wideband Full-Duplex Radios

2017· article· en· W2558425949 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 Transactions on Circuits & Systems II Express Briefs · 2017
Typearticle
Languageen
FieldEngineering
TopicFull-Duplex Wireless Communications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBasebandElectronic engineeringFinite impulse responseWidebandComputer scienceSingle antenna interference cancellationBandwidth (computing)EngineeringTelecommunicationsDecoding methods

Abstract

fetched live from OpenAlex

This brief presents a new approach to cancelling self-interference in full-duplex radios. By augmenting minimal-complexity analog cancellation hardware using a radio frequency vector multiplier with the flexibility and effectiveness of a digital baseband rational function finite impulse response (FIR) filter, the proposed approach enables excellent cancellation performance over a wide modulation bandwidth. This algorithm is devised by exploiting a simplified baseband equivalent behavioral model of the front-end of the full-duplex radio. This allows the parameters of the rational function FIR filter to be identified linearly using the least-squares estimation. The hardware proof-of-concept prototype, built using off-the-shelf components, demonstrated minimum self-interference cancellations of 50 and 40 dB for digitally modulated test signals with modulation bandwidths of 20 and 40-120 MHz, respectively.

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 score0.819
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
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 head0.033
GPT teacher head0.251
Teacher spread0.218 · 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