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Record W2122571804 · doi:10.1109/icc.2005.1494904

Simplified Bit Error Rate Analysis of PAPM-UWB with MRC and EGC in Lognormal Fading Channels

2005· article· en· W2122571804 on OpenAlex
F. Rajwani, Norman C. Beaulieu

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
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaximal-ratio combiningLog-normal distributionFadingBit error rateAlgorithmDiversity combiningPulse-position modulationComputer scienceMathematicsModulation (music)Channel (broadcasting)Pulse-amplitude modulationElectronic engineeringPhysicsTelecommunicationsStatisticsPulse (music)EngineeringAcoustics

Abstract

fetched live from OpenAlex

Ultra-wideband (UWB) communications is a new technology being developed for high-speed, short distance wireless communications. One possible modulation scheme is pulse amplitude and position modulation (PAPM), which has a flat power spectral density that is highly suited to UWB. Closed-form expressions for the error rate performance of a PAPM UWB receiver based on maximal ratio combining (MRC) in a lognormal fading channel have been derived using Wilkinson's approximation for lognormal sums. The receiver is analyzed using a more accurate approximation to the lognormal sum distribution. Our approach is extended to obtain accurate closed-form expressions for the performance of equal gain combining (EGC). The performances of MRC and EGC diversity are calculated and compared to the results obtained using Wilkinson's approximation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.220
Teacher spread0.210 · 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

Citations11
Published2005
Admission routes1
Has abstractyes

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