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Record W1971056209 · doi:10.1109/pimrc.2011.6139877

Modelling, measurement and analysis of narrowband fast fading on relay channels

2011· article· en· W1971056209 on OpenAlexaffabout
Georgy Levin, R.J.C. Bultitude, Hong Zhu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsRician fadingFadingRelayFading distributionRelay channelNarrowbandComputer scienceChannel state informationBase stationElectronic engineeringChannel (broadcasting)TelecommunicationsComputer networkRayleigh fadingPower (physics)EngineeringPhysicsWireless

Abstract

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A procedure for the analysis of narrowband fast fading data with statistically non-stationary characteristics is proposed and applied to data obtained from wideband radio propagation experiments involving two-hop relay channels at 2.25 GHz. The reported experiments were conducted from two channel sounder base station sites in Ottawa to enable a study of the characteristics of relay links in urban microcell environments and of vehicle-to-vehicle communications in relay-based cellular networks. It is shown that empirically-derived cumulative probability distributions for narrowband fast fading on relay links during time intervals when such fading exhibits quasi-stationary characteristics conform closely to a Double-Rician model, the derivation of which is detailed. Analysis of the Double-Rician distribution shows that Double-Rician fading is deeper than Rician fading, unless the K-ratios of the Rician links comprising the relay link are highly dissimilar (having 10 dB difference or more). In such cases, fading on the relay link has a distribution that is very similar to that of the constituent link with the smallest K-ratio. While, in general, relaying is meant to increase average received SNR, it is shown that when the fast fading on the links constituting a relay channel is i.i.d., N-hop relaying reduces the specular-to-random power ratio on the relay link by N times, or significantly increases the depth of fading. This result indicates a need for significant gains at relay stations in some cases.

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 score0.956
Threshold uncertainty score0.320

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 head0.050
GPT teacher head0.212
Teacher spread0.162 · 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

Citations2
Published2011
Admission routes2
Has abstractyes

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