Energy-Efficient Multi-Hop Routing Protocol for Tag-to-Tag Communication in Passive RFID Networks Using Reinforcement Learning

With recent advancements in Radio Frequency Identification (RFID) technology, tag-to-tag communication among passive RFID tags using backscattering has emerged as a breakthrough development. Unlike traditional RFID systems where tags only communicate with a reader, this innovation enables tags to interact directly when RF signals are present in the environment. However, due to the absence of internal power sources, the communication range of these tags is significantly limited, necessitating multi-hop communication to connect distant tags. In this paper, we propose a novel multi-hop routing protocol tailored for passive RFID tag-to-tag networks utilizing a reinforcement learning method. Our design features a circular sector-based area with a central controller that acts as the RF signal source. The area is divided into sectors based on the communication range of both the controller and the tags. To evaluate the performance of our protocol, we developed a simulation environment where passive tags are uniformly distributed within the circular area. Through multi-hop communication facilitated by the controller, energy-efficient tag-to-tag communication is achieved. The results demonstrate that our proposed protocol effectively minimizes energy consumption while ensuring reliable multi-hop communication among passive tags.