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Selective Cooperative Relaying over Time-Varying Channels

2010· article· en· W2040483094 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

VenueIEEE Transactions on Communications · 2010
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRelayRelay channelFadingBandwidth (computing)Computer scienceComputer networkElectronic engineeringPower (physics)Channel (broadcasting)EngineeringPhysics

Abstract

fetched live from OpenAlex

In selective cooperative relaying only a single relay out of the set of available relays is activated, hence the available power and bandwidth resources are efficiently utilized. However, implementing selective cooperative relaying in time-varying channels may cause frequent relay switchings that deteriorate the overall performance. In this paper, we study the rate at which a relay switching occurs in selective cooperative relaying applications in time-varying fading channels. In particular, we derive closed-form expressions for the relay switching rate (measured in Hz) for opportunistic relaying (OR) and distributed switch and stay combining (DSSC). Additionally, expressions for the average relay activation time for both of the considered schemes are also provided, reflecting the average time that a selected relay remains active until a switching occurs. Numerical results manifest that DSSC yields considerably lower relay switching rates than OR, along with larger average relay activation times, rendering it a better candidate for implementation of relay selection in fast fading environments.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.296
Teacher spread0.259 · 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