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Record W1977555766 · doi:10.1109/icuwb.2007.4381045

Performance Analysis of IEEE 802.15.4a BPSK/BPPM UWB Transmission

2007· article· en· W1977555766 on OpenAlexaff
Zahra Ahmadian, Lutz Lampe

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer sciencePhase-shift keyingDecoding methodsUltra-widebandPulse-position modulationTime-hoppingBit error rateConvolutional codeAlgorithmRake receiverElectronic engineeringTransmission (telecommunications)TelecommunicationsFadingDetectorPulse-amplitude modulationEngineeringPulse (music)

Abstract

fetched live from OpenAlex

The IEEE 802.15.4a standard uses coded impulse-radio ultra-wideband (UWB) transmission with combined binary phase-shift keying/binary pulse-position modulation (BPSK/BPPM) and direct-sequence spreading with time hopping as physical layer. In this paper, semi-analytical expressions are derived to evaluate the bit-error rate (BER) performance for such a UWB system. Thereby, two different methods for generating reliability information (i.e., decoding metrics) for decoding of the convolutional code at the receiver, the use of time-varying spreading sequences, and suboptimal multipath combining employing a selective RAKE (SRAKE) front-end are included in the analysis. The presented numerical results show that (i) the devised BER approximations are very tight over a wide range of BERs, (ii) symbol-wise metrics are clearly advantageous over bit-wise metrics for decoding, and (iii) SRAKE combining with about 5-10 fingers is sufficient to closely approach the optimal performance for highly dispersive UWB transmission channels.

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)0.005
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.220
Teacher spread0.212 · 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

Citations3
Published2007
Admission routes1
Has abstractyes

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