Analysis of the Game-Theoretic Modeling of Backscatter Wireless Sensor Networks under Smart Interference

TL;DR

This paper models and optimizes backscatter wireless sensor networks under smart interference using game theory, proposing algorithms that improve utility and robustness against interference.

Contribution

It introduces a Stackelberg game-based framework for interference avoidance in backscatter WSNs, with algorithms to optimize power, time-switching, and sub-channel allocation.

Findings

Algorithms effectively maximize utility against smart interference.

Stackelberg equilibrium existence is proven.

Proposed methods outperform Nash game-based algorithms.

Abstract

In this paper, we study an interference avoidance scenario in the presence of a smart interferer which can rapidly observe the transmit power of a backscatter wireless sensor network (WSN) and effectively interrupt backscatter signals. We consider a power control with a sub-channel allocation to avoid interference attacks and a time-switching ratio for backscattering and RF energy harvesting in backscatter WSNs. We formulate the problem based on a Stackelberg game theory and compute the optimal transmit power, time-switching ratio, and sub-channel allocation parameter to maximize a utility function against the smart interference. We propose two algorithms for the utility maximization using Lagrangian dual decomposition for the backscatter WSN and the smart interference to prove the existence of the Stackelberg equilibrium. Numerical results show that the proposed algorithms effectively maximize the utility, compared to that of the algorithm based on the Nash game, so as to overcome smart interference in backscatter communications.