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Record W2123653183 · doi:10.1109/glocom.1993.318365

Direct sequence CDMA employing combined modulation schemes

2002· article· en· W2123653183 on OpenAlexaff
Jun Wang, Abbas Yongaçoğlu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCode division multiple accessModulation (music)Phase-shift keyingComputer scienceSpectral efficiencyElectronic engineeringSpread spectrumBit error rateBandwidth (computing)Direct-sequence spread spectrumQuadrature amplitude modulationAlgorithmTelecommunicationsEngineeringChannel (broadcasting)Physics

Abstract

fetched live from OpenAlex

In most direct sequence code division multiple access (DS-CDMA) systems, the modulation scheme used is a simple one. In this paper, employing a combined modulation scheme in DS-CDMA is proposed. By combining two or more modulation schemes, the resultant symbol energy can be increased, and thus a better symbol error rate performance can be achieved. For the combined modulation scheme, the symbol error rate is determined by the less powerful one of the basic modulation schemes. So a proper selection of modulation combination is essential for power efficiency. In a DS-CDMA system, unlike a narrow-band system, the bandwidth efficiency is closely related to its power efficiency. Thus a combined modulation concept may result in a bandwidth efficient DS-CDMA system. In this paper, we present two DS-CDMA schemes by combining MFSK and coherent MPSK and differential BPSK. These two schemes are respectively denoted as (1) MFSK-MPSK/DS-CDMA, and (2) MFSK-DPSK/DS-CDMA. The proposed schemes have better performance than the conventional CDMA schemes.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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: none
Teacher disagreement score0.981
Threshold uncertainty score0.386

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 science0.0010.001
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 head0.106
GPT teacher head0.310
Teacher spread0.205 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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