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Record W2171376673 · doi:10.1109/isccsp.2004.1296241

Scan and wait combining (SWC): a switch and examine strategy with a performance-delay tradeoff

2004· article· en· W2171376673 on OpenAlexaff
Mohamed‐Slim Alouini, M.K. Simon, Hong-Chuan Yang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer scienceChannel (broadcasting)Path (computing)Coherence (philosophical gambling strategy)Quality (philosophy)Transmission (telecommunications)Outage probabilityAlgorithmReal-time computingStatisticsTelecommunicationsMathematicsComputer networkFading

Abstract

fetched live from OpenAlex

This paper proposes and analyzes an alternative form of switch and examine combining, namely one that waits for a channel coherence time if all the available diversity paths fail to meet a predetermined minimum quality requirement. This scanning through the available diversity paths followed by waiting is repeated indefinitely until a path with an acceptable quality is found. The performance of the resulting "scan and wait" combining (SWC) scheme is studied in terms of its average probability of error and ergodic capacity. The paper looks also into (i) the delay associated with SWC by deriving the statistics of the waiting time needed before satisfactory transmission occurs and (ii) the underlying complexity by studying the statistics of the number of diversity paths estimated per channel access. Selected numerical examples show that, for a fixed average number of channel estimates per channel access, SWC outperforms traditional diversity combining schemes at the expense of a negligible time delay.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.731
Threshold uncertainty score0.355

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 head0.030
GPT teacher head0.238
Teacher spread0.208 · 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 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

Citations6
Published2004
Admission routes1
Has abstractyes

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