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Record W2125378220 · doi:10.1109/tcomm.2008.050310

M-ary orthogonal coded/balanced ultra-wideband transmitted-reference systems in multipath

2008· article· en· W2125378220 on OpenAlexaff
Dong In Kim, Tao Jia

Bibliographic record

VenueIEEE Transactions on Communications · 2008
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsComputer scienceMultipath propagationUltra-widebandInterference (communication)Electronic engineeringMultipath interferenceWidebandCommunications systemSingle antenna interference cancellationAlgorithmDecoding methodsChannel (broadcasting)TelecommunicationsEngineering

Abstract

fetched live from OpenAlex

A new M-ary orthogonal coded signaling is introduced to avoid the inter-frame interference that is especially detrimental to realizing high rate ultra-wideband (UWB) transmitted-reference (TR) systems. To further increase the information rate, the inter-pulse interference by an overlap of multipath-delayed pulses is controlled by integrating the signaling and a pair of balanced matched Alters in a joint manner, so as to permit a shorter time delay between the reference and data pulses in TR systems. To evaluate an achievable information rate increase relative to conventional TR, the symbol error probability (SEP) is theoretically derived for the proposed M-ary orthogonal coded/balanced TR system, considering the realistic IEEE standard UWB channel models. In addition, we consider the issue of receiver complexity and present two alternative low- complexity receiver implementations for the proposed TR system.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.034
GPT teacher head0.244
Teacher spread0.211 · 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

Citations25
Published2008
Admission routes1
Has abstractyes

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