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Record W2149975887 · doi:10.1109/wts.2007.4563300

Finite wordlength design for FFT/IFFT in UWB-OFDM systems

2007· article· en· W2149975887 on OpenAlex
A. Ghassemi, T. Aaron Gulliver

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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDigital Filter Design and Implementation
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingFast Fourier transformComputer scienceTransceiverElectronic engineeringAlgorithmWirelessEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Orthogonal frequency division multiplexing (OFDM) has been proposed for use in ultra-wideband (UWB) communication systems. In a UWB-OFDM transceiver, resource efficient FFT/IFFT hardware is a necessity due to minimal silicon area and low power requirements. Resource requirements can be reduced by using finite precision arithmetic in the FFT/IFFT algorithms. However, this introduces round-off and overflow noise, resulting in a degradation in BER performance. To address this problem, the finite precision arithmetic and wordlengths should be optimally designed at every stage of the FFT/IFFT. In this paper, we first present a mixed-radix FFT/IFFT algorithm for a UWB-OFDM transceiver with low multiplicative complexity. A round-off noise propagation model is derived and used to determine the optimal wordlength of the outputs and twiddle factors at each stage. The performance of the resulting system is compared to that with infinite precision arithmetic.

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)0.001
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 score0.915
Threshold uncertainty score0.372

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 communication0.0000.001
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 head0.080
GPT teacher head0.306
Teacher spread0.226 · 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

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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