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Record W2622014263 · doi:10.1109/cc.2017.7942325

Integration interval determination and decision threshold optimization for improved TRPC-UWB communication systems

2017· article· en· W2622014263 on OpenAlex
Zhonghua Liang, Junshan Zang, Xiaojun Yang, Xiaodai Dong, Huansheng Song

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

VenueChina Communications · 2017
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer scienceAutocorrelationEnergy (signal processing)Interval (graph theory)Ultra-widebandBit error rateAlgorithmChannel (broadcasting)StatisticsTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

Integration interval and decision threshold issues were investigated for improved transmitted reference pulse cluster (iTRPC-) ultra-wideband (UWB) systems. Our analysis shows that the bit error rate (BER) performance of iTRPC-UWB systems can be significantly improved via integration interval determination (IID) and decision threshold optimization. For this purpose, two modifications can be made at the autocorrelation receiver as follows. Firstly, the IID processing is performed for autocorrelation operation to capture multi-path energy as much as possible. Secondly, adaptive decision threshold (ADT) instead of zero decision threshold (ZDT), is used as estimated optimal decision threshold for symbol detection. Performance of iTRPC-UWB systems using IID and ADT was evaluated in realistic IEEE 802.15.4a UWB channel models and the simulation results demonstrated our theoretical analysis.

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 categoriesScience and technology studies
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 score0.949
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0000.001
Open science0.0030.001
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 head0.022
GPT teacher head0.282
Teacher spread0.260 · 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