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Record W2063096652 · doi:10.1109/wicom.2010.5600989

Capacity of Differential Pulse-Position Modulation (DPPM) over Nakagami-m Fading Channels

2010· article· en· W2063096652 on OpenAlexaff
Xiao Wang, Hao Zhang, T. Aaron Gulliver

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAdditive white Gaussian noiseNakagami distributionFadingChannel capacityPulse-position modulationChannel (broadcasting)Modulation (music)MathematicsTopology (electrical circuits)AlgorithmDifferential (mechanical device)Position (finance)TelecommunicationsComputer scienceElectronic engineeringPulse (music)PhysicsPulse-amplitude modulationEngineeringCombinatoricsAcoustics

Abstract

fetched live from OpenAlex

The capacity of differential pulse-position modulation (DPPM) is considered in this paper. Since the formula of Shannon Capacity is effective only in the AWGN channel with continuous-valued inputs and outputs, while the channel employing M-ary DPPM modulation has discrete-valued inputs and continuous-valued outputs, we derive the modified formula which applies to calculate the capacity of a UWB system with DPPM over an AWGN channel. Then the result is extended to Nakagmi-m fading channels. Monte Carlo simulation is employed to analyze the relationship between the capacity and the signal to noise ratio (SNR), and the relationship between reliable communication distance and channel capacity subject to FCC Part 15 rules is also given. The results show that DPPM is superior to PPM in terms of data transfer rate and capacity performance.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.376

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 head0.011
GPT teacher head0.211
Teacher spread0.201 · 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 designBench or experimental
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

Citations2
Published2010
Admission routes1
Has abstractyes

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