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Record W2152408207 · doi:10.1109/glocom.2006.570

SPC07-3: An Iterative QR-SIC Receiver for Concatenated Space Frequency Coding Schemes in Severe Multipath Channels

2006· article· en· W2152408207 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGlobecom · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMultipath propagationComputer scienceSingle antenna interference cancellationOrthogonal frequency-division multiplexingAlgorithmFadingMIMOTurbo codeDiversity schemeQR decompositionElectronic engineeringMIMO-OFDMChannel (broadcasting)Decoding methodsTelecommunicationsEngineeringPhysics

Abstract

fetched live from OpenAlex

This paper studies an efficient receiver design for concatenated space-frequency coded orthogonal frequency division multiplexing (OFDM) systems under severe multipath channels. The proposed receiver utilizes a turbo-like iterative QR decomposition based successive interference cancellation (QR-SIC) algorithm that exploits both spatial and frequency diversity inherent in the multipath multiple-input multiple output (MIMO) channel. Performance of the proposed receiver is evaluated via Monte Carlo simulations. Our results show that the proposed iterative QR-SIC scheme attains excellent performance improvements in severe multipath fading channels. In addition, the proposed scheme attains manageable receiver complexity since we only consider a maximum of 2-3 iterations.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.939

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 science0.0000.000
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 head0.017
GPT teacher head0.263
Teacher spread0.247 · 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