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Record W2107252916 · doi:10.1109/dnsr.2004.1344705

An application of multi-wavelet packets in digital communications

2004· article· en· W2107252916 on OpenAlexaff
Minghou You, Jacek Ilow

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsDalhousie University
Fundersnot available
KeywordsComputer scienceSubcarrierElectronic engineeringPhase-shift keyingSpectral efficiencyAlgorithmRayleigh fadingOrthogonal frequency-division multiplexingDemodulationNetwork packetTelecommunicationsFadingBit error rateChannel (broadcasting)EngineeringComputer networkDecoding methods

Abstract

fetched live from OpenAlex

Bandwidth efficiency and the ability to combat the effects of frequency selective channels are critical in the design of digital modulation schemes. To improve bandwidth utilization and to avoid ISI caused by time dispersion in the channel, a new multi-wavelet packet modulation (MWPM) scheme is proposed. The MWPM is based on orthogonal multi-wavelet packets (MWP). In particular, the orthogonality in MWP is exploited to guarantee the demodulation of the overlapped MWP coded signals in time and frequency domains. A practical implementation of the MWPM transceiver is proposed by employing matrix filter banks. For MWP with multiplicity r, the bandwidth efficiency is increased r times compared to scalar wavelet packet modulation or the conventional FFT based OFDM system. Similarly, as these prototype schemes, the MWPM is implementable either as a binary or a multilevel scheme. As a multi-carrier modulation, MWPM can mitigate the time dispersiveness in the channel effectively because the symbol duration can be extended as required by the flexible structure of MWPM. Using two orthogonal MWPs introduced by J. Geronimo et al. (see J. Approx. Theory, vol.78, p.373-401, 1994) and C. Chui and J. Lian (Ctr. for Approximation Theory, 1995), the corresponding MWPM are constructed. The performance for these MWPM in AWGN and flat Rayleigh fading channels is analyzed and simulated using binary phase shift keying (BPSK) in each subcarrier. The simulation results demonstrate the effectiveness of the proposed MWPM scheme.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.276
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations9
Published2004
Admission routes1
Has abstractyes

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