Data-driven link quality prediction using link features

ACM Transactions on Sensor Networks

Volumn 10, Issue 2, 2014, Pages

  Liu, Tao ^a   Cerpa, Alberto E ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Link quality estimation; Link quality prediction

Indexed keywords

LINK QUALITY ESTIMATIONS; LINK QUALITY INDICATORS; LINK QUALITY PREDICTIONS; MACHINE LEARNING METHODS; NAIVE BAYES CLASSIFIERS; RECEIVED SIGNAL STRENGTH INDICATORS; RELIABLE COMMUNICATION; SIGNALTONOISE RATIO (SNR);

COST BENEFIT ANALYSIS; DATA ACQUISITION; ESTIMATION; EXPERIMENTS; FORECASTING; LEARNING SYSTEMS; MATHEMATICAL MODELS; MODELS; NEURAL NETWORKS; REGRESSION ANALYSIS; SIGNAL TO NOISE RATIO;

QUALITY CONTROL;

EID: 84893367596     PISSN: 15504859     EISSN: 15504867     Source Type: Journal    
DOI: 10.1145/2530535     Document Type: Conference Paper

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