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Record W2121489931 · doi:10.1109/icc.2006.255664

An Improved Busy-Tone Solution for Collision Avoidance in Wireless Ad Hoc Networks

2006· article· en· W2121489931 on OpenAlexaff
Ping Wang, Weihua Zhuang

Bibliographic record

Venue2006 IEEE International Conference on Communications · 2006
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer networkComputer scienceTransmitterWireless ad hoc networkNetwork packetChannel (broadcasting)Tone (literature)ThroughputCarrier sense multiple access with collision avoidanceMultiple Access with Collision Avoidance for WirelessHidden node problemWirelessTerminal (telecommunication)Real-time computingVehicular ad hoc networkWireless networkTelecommunicationsWi-Fi array

Abstract

fetched live from OpenAlex

In a single-channel wireless ad hoc network, the collisions caused by hidden terminals can severely reduce the network capacity. In this paper, a new busy-tone based scheme is proposed, which can completely avoid collisions (including DATA packet and RTS packet collisions) caused by hidden terminals. This is achieved by adding dual busy-tone channels, and setting a larger carrier sense range of the transmitter busy-tone channel than those of the information and receiver busy-tone channels. The proposed scheme also resolves the exposed terminal problem incurred by the increased carrier sense range of the transmitter busy-tone channel. The simulation results demonstrate that the proposed scheme has an improved performance in terms of throughput in the hidden terminal scenario as compared with the traditional busy-tone solution, and also achieves a high channel utilization in the exposed terminal scenario.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.942
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0040.000
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 head0.046
GPT teacher head0.334
Teacher spread0.288 · 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
GenreMethods

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

Citations16
Published2006
Admission routes1
Has abstractyes

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