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Record W2103408667 · doi:10.1109/twc.2008.05421

Broadcasting energy efficiency limits in wireless networks

2008· article· en· W2103408667 on OpenAlexaff
Liang Song, Dimitrios Hatzinakos

Bibliographic record

VenueIEEE Transactions on Wireless Communications · 2008
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBroadcasting (networking)Computer scienceRelayComputer networkWirelessWireless networkWireless sensor networkEfficient energy useNode (physics)TelecommunicationsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

Broadcasting allows efficient information sharing and fusion in wireless networks. In this paper, the energy efficiency limits in wireless broadcasting, defined as the minimal achievable broadcast energy consumption per bit (BEB), are studied. Specifically, we consider that a source node broadcasts information bits in a planar disk region A. And n relay nodes, which assist the broadcasting, are also placed in A. The limits are studied for both arbitrary and random wireless networks, under both non-cooperative and cooperative relay transmissions models. Closed form expressions are obtained. The results show that the minimal BEB, in general, decreases polynomially with n, and increases polynomially with the area of A. Cooperative relay transmissions offer at most a constant gain, in terms of the minimal BEB, over noncooperative transmissions, except for the free space propagation. As an example of application, our results are utilized in the study of wireless sensor networks, where the broadcast information fusion strategy is described and analyzed.

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 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: Empirical · Consensus signal: none
Teacher disagreement score0.974
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
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0040.000
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 head0.056
GPT teacher head0.276
Teacher spread0.220 · 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.

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

Citations10
Published2008
Admission routes1
Has abstractyes

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