QuadScatter: Computational Efficiency in Simultaneous Transmissions for Large-Scale IoT Backscatter Networks

Abstract

Backscatter communication has attracted attention owing to its ultra-low-power consumption ability, which is expected to enhance internet of things (IoT) technology that aims to enable many novel applications for object-to-object communication. Such a network with a large and continuously increasing number of connected objects will benefit significantly from resource-saving. This work introduces a system named QuadScatter, which is a set of algorithms that select and associate transmitters, tags and readers to enable simultaneous backscatter transmissions and increase network capacity. Consequently, the energy consumption in the network is considerably lessened. Intensive simulations have been conducted to demonstrate the effectiveness of backscatter simultaneous transmissions. QuadScatter shows promising results compared to the exhaustive search algorithm. The simulation results highlight computational time and simultaneous transmission improvements of at least $ 250\rm \times$ and $ 2\rm \times$, respectively. Furthermore, while the exhaustive search is limited to a few nodes ($ < 20$), our proposal uses numerous nodes. Additionally, an implementation of limited simultaneous backscatter transmissions is conducted to show its feasibility in the real world.

Keywords

• Computational cost
• simultaneous backscatter transmissions
• quadtree
• quadtree quadrant
• nearest neighbor search
• exhaustive search