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Record W1868206661 · doi:10.1109/icupc.1993.528466

Multi carrier modulation for indoor wireless communications

2002· article· en· W1868206661 on OpenAlexaff
A. Chini, M. El-Tanany, Soliman A. Mahmoud

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceAdditive white Gaussian noiseBit error rateSpectral efficiencyFadingBandwidth (computing)Coherence bandwidthElectronic engineeringBlock Error RateRayleigh fadingChannel capacityChannel (broadcasting)Orthogonal frequency-division multiplexingTelecommunicationsDelay spreadEngineeringTelecommunications link

Abstract

fetched live from OpenAlex

This paper discusses Multi Carrier Modulation (MCM) with application to broadband Frequency Selective Fading (FSF) channels. The first part of the paper discusses the capacity of such channels subject to the assumption that the channel bandwidth is much larger than the coherence bandwidth. Under this condition, it is shown that for a given spectral efficiency, in terms of C/W (Bits/S/Hz), the FSF channel requires 2.5dB more power by comparison to the ideal AWGN channel in high Signal to Noise Ratio (SNR). The extra power requirement decreases to less than 2dB for SNR below 10dB. The second part of the paper discusses the performance of a differentially detected MCM system. It is shown that the average Bit Error Rate (BER) performance is at best similar to the performance achievable over flat Rayleigh fading channels if no channel coding is used. Block error rate results are also presented and used in predicting the average performance improvement due to linear block codes.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.933
Threshold uncertainty score0.434

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 head0.054
GPT teacher head0.288
Teacher spread0.235 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2002
Admission routes1
Has abstractyes

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