Joint design of symbiotic communication with AmBC and RIS in an IoT environment

For wireless systems, ambient backscatter communication (AmBC) is considered a revolutionary energy-efficient technology. Many approaches have been developed, but owing to single communication, these existing approaches lead to interference problems, power consumption, and lower performance. Thus, to overcome these problems, a symbiotic communication system is proposed for the Internet of Things with AmBC and RIS using a channel estimation (CE) approach and signal controller approach. Primarily, the access point (AP) is initialized, and then the signal is transmitted from the AP to the receiver in a two-way process. By utilizing the RIS approach, the signal is controlled, and the signal is monitored as stable or transition by the tag approach. The parameters are optimized by using adjustable population-based Egret swarm optimization in the RIS approach; also, the tag approach was done by using carrier multiplied M-phase-shift keying. Then, the receiver will send the acknowledgment message to the AP if the receiver does not receive the signal in a particular time interval. In the end, after transmitting the signal to the receiver, by deploying Kendall rank correlated deep radial basis function neural network techniques, the CE is carried out. Finally, the experimental analysis was validated, which shows the proposed model's efficiency.