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Record W1544878175 · doi:10.1002/jnm.2051

Rapid prototyping of MIMO‐OFDM based on parity bit selected and permutation spreading

2015· article· en· W1544878175 on OpenAlexaff
Sherif Moussa, Ahmed M. Abdel Razik, Adel Omar Dahmane, Claude D’Amours, Habib Hamam

Bibliographic record

VenueInternational Journal of Numerical Modelling Electronic Networks Devices and Fields · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversité de MonctonUniversity of OttawaUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingComputer scienceMIMO-OFDMMIMOTransmitterGate arrayField-programmable gate arrayElectronic engineeringAlgorithmFast Fourier transformComputer engineeringComputer hardwareEngineeringTelecommunicationsBeamforming

Abstract

fetched live from OpenAlex

Summary In this paper, a novel MIMO‐OFDM transmission scheme is developed to effectively enable multi‐access by joint code design across multiple antennas, subcarriers, OFDM frames, and users. It achieves better spectrum efficiency while improving bit error rate performance. The proposed scheme uses either parity bit selected or permutation techniques to assign spreading codes at the transmitter side. As a result, the detection at the receiver is greatly improved because of the fact that identifying the spreading code(s) directly yields the transmitted data symbols. The paper also investigates the field‐programmable gate array implementation of the proposed algorithms; optimization techniques are proposed to reduce area, power, and time. These techniques include a pipelined architecture for inverse FFT/FFT blocks, an efficient low complexity algorithm for despreading based on counters and comparators and an optimized architecture for complex matrix inversion using Gauss–Jordan elimination (GJ‐elimination). Finally, the fixed‐point optimized field‐programmable gate array architecture for MIMO‐OFDM transceiver is developed, where the maximum allowed performance loss because of quantization is defined, the tradeoffs between BER performance and area reduction are investigated. Copyright © 2015 John Wiley & Sons, Ltd.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.387

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 communication0.0000.000
Open science0.0000.000
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 head0.019
GPT teacher head0.257
Teacher spread0.239 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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