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Record W2121882162 · doi:10.1109/wcnc.2005.1424632

Adaptive modulation and coding with multicodes over nakagami fading channels

2005· article· en· W2121882162 on OpenAlex

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFadingLink adaptationComputer scienceNakagami distributionChannel state informationBit error rateChannel (broadcasting)Electronic engineeringCoding (social sciences)Channel codeGranularitySpectral efficiencyTransmission (telecommunications)AlgorithmModulation (music)TelecommunicationsDecoding methodsStatisticsMathematicsWirelessEngineeringPhysics

Abstract

fetched live from OpenAlex

Adaptive modulation and coding (AMC) has been adopted in the 3GPP standard in order to improve spectral efficiency. In order to increase the granularity of the adaptation and to provide higher bit rates, multicode transmission is employed. Since the use of AMC requires knowledge of the channel state, the accuracy of this information is important. In practice, errors in estimating the channel state are inevitable, resulting in performance degradation. The average bit rate performance of AMC with multicodes is studied for a CDMA system experiencing Nakagami fading and channel estimation errors. The results are obtained in terms of the generalized Marcum Q-function. Numerical results are provided to illustrate the performance degradations due to inaccuracies in estimating the channel.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.754
Threshold uncertainty score0.377

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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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

Quick stats

Citations6
Published2005
Admission routes1
Has abstractyes

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