MétaCan
Menu
Back to cohort
Record W2149017262 · doi:10.1109/icc.2004.1312519

Performance analysis of bandlimited DS-CDMA systems in Nakagami fading

2004· article· en· W2149017262 on OpenAlexaff
Kathiravetpillai Sivanesan, Norman C. Beaulieu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNakagami distributionFadingBandlimitingAlgorithmGaussianComputer scienceBit error rateMathematicsElectronic engineeringPhysicsDecoding methodsEngineering

Abstract

fetched live from OpenAlex

Accurate performance analysis of asynchronous bandlimited binary DS-CDMA systems in Nakagami-m fading is considered. The fading is assumed to be flat and slow. The spectrum raised-cosine and Beaulieu-Tan-Damen pulse shapes are employed. A new accurate approximation for computing the bit error rate of bandlimited DS-CDMA systems employing random spreading sequences is proposed. A substantial computational complexity reduction is achieved. The well-known standard Gaussian approximation, Holtzman's simplified improved Gaussian approximation, and the improved Holtzman's Gaussian approximation are also considered. The accuracies of the approximations are assessed using Monte-Carlo simulation. For a system employing a deterministic sequence for the desired user and random sequences for the active interfering users, a characteristic function method is employed to derive exact BER results. The new Beaulieu-Tan-Damen pulse outperforms the spectrum raised-cosine pulse in all situations examined.

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)0.005
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.282
Teacher spread0.250 · 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

Citations10
Published2004
Admission routes1
Has abstractyes

Explore more

Same topicWireless Communication Networks ResearchFrench-language works237,207