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Record W2162937330 · doi:10.1109/icc.2006.255749

Explicit Bounds for the Outage Probability for Multiple Antenna Systems in the Presence of Spatial Correlation

2006· article· en· W2162937330 on OpenAlexaff
Hao Shen, Ali Ghrayeb

Bibliographic record

Venue2006 IEEE International Conference on Communications · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsConcordia University
Fundersnot available
KeywordsSpatial correlationRayleigh fadingMIMOFadingChannel state informationTransmitterComputer scienceAlgorithmRank (graph theory)Signal-to-noise ratio (imaging)Channel (broadcasting)CorrelationCovariance matrixMathematicsWirelessTelecommunicationsCombinatorics

Abstract

fetched live from OpenAlex

In this paper, we present a comprehensive analysis of the outage probability for multiple-input multiple-output (MIMO) systems over spatially correlated Rayleigh fading chan-nels. In our analysis, we assume that 1) the channel state information (CSI) is perfectly known at the receiver but not at the transmitter, 2) the spatial correlation is present at both ends of the wireless communications link, 3) the transmit and receive correlation matrices may or may not be full rank, and 4) the underlying channel is quasi-static fading. With these assumptions, we derive explicit bounds for the outage probability and show that the diversity order is simply the product of the rank of the transmit correlation matrix and the rank of the receive correlation matrix. We also derive an expression that accurately quantifies the degradation in the signal-to-noise ratio (SNR) due to the presence of correlation. We present several numerical examples that validate our analysis.

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)0.005
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.027
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.079
GPT teacher head0.310
Teacher spread0.231 · 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 designTheoretical or conceptual
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".

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Citations1
Published2006
Admission routes1
Has abstractyes

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Same venue2006 IEEE International Conference on CommunicationsSame topicAdvanced MIMO Systems OptimizationFrench-language works237,207