MétaCan
Menu
Back to cohort
Record W2105658916 · doi:10.1109/glocom.2008.ecp.1004

Analysis of Delayed Acknowledgment Scheme with Packet Fragmentation of UWB-Based WPAN

2008· article· en· W2105658916 on OpenAlexaff
Ruonan Zhang, Lin Cai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer scienceComputer networkNetwork packetTransmitterQueueing theoryFadingUltra-widebandChannel (broadcasting)Capture effectWirelessMarkov processElectronic engineeringTelecommunicationsEngineeringThroughput

Abstract

fetched live from OpenAlex

Delayed acknowledgment (Dly-ACK) and packet fragmentation are link-layer policies for ultra-wideband (UWB) based wireless personal area networks (WPANs) to improve the channel utilization, defined in both the IEEE 802.15.3a and ECMA-368 standards. On the other hand, the shadowing effect caused by people moving between the transmitter and receiver may severely degrade the received signal power and thus introduce channel variation. In this paper, we develop an analytical framework for studying the performance of the Dly-ACK and fragmentation over UWB fading channels. A Markov model is used to capture the time-variation of the UWB shadowing channel. The distribution of transmission delay of fragmented packets and the queuing behavior of the sender's buffer are derived. The system performance of packet delay and loss are obtained. Validated by simulations, the analytical results provide important insights and guidelines for better supporting high data rate, delay sensitive traffic in UWB-based WPANs.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.214
Teacher spread0.202 · 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

Citations4
Published2008
Admission routes1
Has abstractyes

Explore more

Same topicUltra-Wideband Communications TechnologyFrench-language works237,207