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Record W2267311386

Rapid Prototyping and Performance Evaluation of a MIMO CDMA System Using an FPGA-Based Hardware Platform

2015· article· en· W2267311386 on OpenAlexaff
Mostafa Hefnawi

Bibliographic record

VenueJournal of Telecommunication Electronic and Computer Engineering (JTEC) · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsField-programmable gate arrayStratixComputer hardwareEmbedded systemComputer scienceMATLABFPGA prototypeDigital signal processingMIMOChannel (broadcasting)Operating system
DOInot available

Abstract

fetched live from OpenAlex

This paper investigates the rapid prototyping of a multiple input-multiple-output direct sequence-code division multiple access (MIMO DS-CDMA) system with rake receiver, implemented on a field programmable gate array (FPGA) based hardware platform. The hardware implementation is created using the Altera DSP builder– a MATLAB/Simulink based system-level design tool and the Stratix EP1S80 DSP development board from Altera. The hardware-in-the-loop (HIL) co-simulation and the Logic Analyzer are used with the physical FPGA board implementing the design to evaluate the system performance and to verify the functionality of the hardware implementation in the MATLAB/Simulink environment. Results show that, in general, the bit error rate (BER) of the hardware implementation fell within the confidence intervals of the simulated BER

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.039
GPT teacher head0.260
Teacher spread0.221 · 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 designBench or experimental
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
Published2015
Admission routes1
Has abstractyes

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