MétaCan
Menu
Back to cohort
Record W2163927657 · doi:10.1109/pacrim.1995.519562

4-phase DS-CDMA performance over LEOS/MEOS channels

2002· article· en· W2163927657 on OpenAlexaff
R. Kerr, V.K. Bhargava

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsFadingPhase-shift keyingRician fadingComputer scienceCode division multiple accessChannel (broadcasting)Communications satelliteGeostationary orbitTelecommunicationsTelecommunications linkGold codeBit error rateAlgorithmElectronic engineeringSpread spectrumSatellitePhysicsEngineering

Abstract

fetched live from OpenAlex

In this paper, we investigate the downlink performance of DS-CDMA using QPSK modulation and 4-phase spreading sequence in a fading satellite channel. Two different types of spreading sequences will be evaluated. One type of sequence construction will be to use two binary sequences; one for the in-phase channel and the other for the quadrature channel. The binary sequences will be binary Gold sequences. The other type of sequence will utilize sequences from GF(4) which have near optimum correlation properties. The 4-phase sequences have been shown to increase the number of users of a multiple access system by 50% in a Gaussian environment. We investigate the performance of the above sequences in a non-geostationary satellite channel. This channel model for non-geostationary satellites is characterized by Rician fading and lognormal shadowing where the fading/shadowing characteristics depend on the elevation angle of the satellite. The upper bound on the symbol error rate (SER) is derived and is computed for both a LEO and MEO system.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.950
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.062
GPT teacher head0.313
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; both teacher heads agree on what is shown here.

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

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicWireless Communication Networks ResearchFrench-language works237,207