Energy-Efficiency Maximization for Active Reconfigurable Intelligent Surface-Assisted Clustered Cognitive Radio Sensor Networks

Clustering protocols are potential solutions to address the severe energy constraints faced by cognitive radio sensor networks (CRSNs). To further exploit the potential of clustering protocols in reducing node energy consumption, active reconfigurable intelligent surface (RIS) is for the first time incorporated into clustered CRSNs to assist the uplink data transmission toward the sink. To minimize the total node energy consumed by uplink data transmission, we formulate the problem of maximizing the normalized energy efficiency improvement ratio for all nodes in active RIS-assisted clustered CRSNs compared to conventional clustered CRSNs and solve it by jointly optimizing the active RIS beamforming and transmit power of CRSNs nodes. Specifically, by considering the physical and electromagnetic properties of the active RIS, we redefine the conditions for successful information transmission under deterministic channels. Analytical expressions for the optimal reflection coefficients of the active reflecting elements (REs), as well as semiclosed-form solutions for the transmit power of CRSNs nodes are derived. Moreover, the optimal configurations of key parameters, such as the number of active REs, total power budget for the active RIS, wavelength of transmitted signal, and physical dimensions of REs are theoretically derived and validated through numerical simulations, thereby offering design guidance for future active RIS-assisted clustered CRSNs. Simulation results indicate that the proposed mechanism significantly outperforms its baseline counterparts and is suitable for CRSNs nodes with severe computational and energy constraints.