On Max-Min Complete Targets Sampling in Backscater-Aided RF Powered IoT Networks

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 backscattring.