Analysis of the Game-Theoretic Modeling of Backscatter Wireless Sensor Networks under Smart Interference
Seung Gwan Hong, Yu Min Hwang, Sun Yui Lee, Yoan Shin, Dong In Kim,, and Jin Young Kim

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…
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Taxonomy
TopicsEnergy Harvesting in Wireless Networks · Full-Duplex Wireless Communications · Advanced MIMO Systems Optimization
