MétaCan
Menu
Back to cohort
Record W1500392844 · doi:10.1109/icupc.1993.528530

Delay and throughput characteristics of TH, CDMA, TDMA, and hybrids for multipath faded data transmission channels

2002· article· en· W1500392844 on OpenAlexaff
A.K. Elhakeem, Rocco Di Girolamo, I.B. Bdira, Malleswara Talla

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsTime division multiple accessCode division multiple accessComputer scienceComputer networkNear-far problemCDMA spectral efficiencyMultipath propagationFrequency-division multiple accessFrame (networking)ThroughputFadingCellular networkNetwork packetElectronic engineeringChannel (broadcasting)TelecommunicationsWirelessEngineeringOrthogonal frequency-division multiplexing

Abstract

fetched live from OpenAlex

This work introduces the new concepts of adaptive time hopping and variable frame Code Division (CDMA) Multiple Access, and evaluates by a unified analysis the probabilities of bit and packet errors in multipath fading environment of five Time Division (TDMA), Code Division, and Time Hopping (TH) related multiaccess networks, namely: TDMA, CDMA, CDMA/TDMA, Adaptive CDMA/TH, and variable frame CDMA/TDMA networks. The delay and useful throughputs of the five systems are also evaluated for data and voice traffics. All systems use the same channel power and bandwidth, and support the same traffic. Though implementation issues are not covered, CDMA systems are put at a disadvantage by ignoring such inherent advantages as voice silence utilizations and automatic frequency reuse (compared to cellular-type FDMA networks for example). Not surprisingly, CDMA systems 4 and 5 outperform TDMA systems at low and medium input traffics.

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: Methods · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score0.417

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 communication0.0000.001
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 head0.114
GPT teacher head0.313
Teacher spread0.199 · 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
GenreMethods

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

Citations2
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicWireless Communication Networks ResearchFrench-language works237,207