Decentralized, Game-Theoretic Reflection Control in Battery-Free Ambient Backscatter Communication Internet of Things Networks

The Internet of Things is constrained by energy consumption and battery limitations, leading to high network maintenance costs and environmental impact. Battery-free ambient backscatter communication (AmBC) provides a sustainable alternative by enabling passive tags to harvest RF energy for continuous data transmission. The inherently low power of AmBC signals increases signal outage probability and bit error rates (BER), requiring effective adaptation mechanisms. This paper proposes a new reflection coefficient adjustment approach that enables both energy harvesting and reliable data transmission at each passive tag. In our decentralized multi-agent framework, tags compete to achieve higher transmit powers for reliable communication. To mitigate interference between tags, we model the interaction among tags as a non-cooperative Cournot game, where each tag acts as a rational agent adjusting its reflection coefficient to maximize its own utility—defined as a trade-off between transmission reliability and interference mitigation. Our game-theoretic approach eliminates the need for explicit coordination or information exchange, promoting scalability and robustness. Numerical results show that our approach significantly outperforms existing methods by reducing BER and improving energy efficiency, making it a viable solution for sustainable, battery-free IoT communications.