"On Max-Min Complete Targets Sampling in Backscatter-Aided R

"On Max-Min Complete Targets Sampling in Backscatter-Aided RF Powered I" by Rui Yang, Changlin Yang et al.

This paper considers a Radio Frequency (RF) powered Internet of Things (IoT) network that exploits ambient backscatter communications to maximize the minimum number of samples of targets. We propose a Maximum Backscatter Opportunity Search (MBOS) heuristic algorithm to construct set covers to ensure complete targets coverage. Our results demonstrate that the performance of MBOS is within 91% of the optimal number of samples and it is 25% higher as compared to not using backscattering.

Related Keywords

, Radio Frequency , Maximum Backscatter Opportunity Search , Backscatter , Costs , Heuristic , Interference , Nternet Of Things , Mathematical Programming , Monitoring , Sensors , Targets Monitoring , Wireless Power ,

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