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Record W2055680027 · doi:10.1109/sips.2006.352598

Fault Tolerance of Quantized Unitary Precoders

2006· article· en· W2055680027 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

VenueSiPS ... design and implementation - IEEE Workshop on Signal Processing Systems · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPrecodingSingular value decompositionUnitary matrixControl theory (sociology)TransmitterChannel (broadcasting)Singular valueComputer scienceAlgorithmChannel state informationMathematicsTopology (electrical circuits)Unitary stateMIMOTelecommunicationsWirelessArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

Precoding based on channel state information (CSI) can help improve the performance of orthogonal space-time block codes (OSTBCs). Optimum precoders require a fairly detailed description of the channel singular vectors motivating the use of limited feedback communications to send some quantized form of the precoder to the transmitter. To this end, the singular value decomposition (SVD) is the fundamental step in extracting the singular vectors of the channel. In this paper we revisit a limited feedback technique based on the quantization of the dominant right singular vector of the channel matrix. Lifting the assumption of perfect channel estimation at the receiver, we investigate channels affected by Gaussian noise, line of sight component, and phase uncertainty. We also assume a more general channel model that incorporates channel correlations. Our simulations show that the quantized nature of the precoders provides the system with resiliency to such impairments.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score0.994

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 head0.033
GPT teacher head0.305
Teacher spread0.272 · 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