The content presents an active RIS-assisted spectrum sensing system for cognitive radio networks. The key highlights are:
In opportunistic cognitive radio networks, when the primary signal is very weak compared to the background noise, the secondary user requires long sensing time to achieve reliable spectrum sensing performance, leading to little remaining time for secondary transmission.
To address this issue, the authors propose an active RIS-assisted spectrum sensing system, where the received signal strength from the primary user can be enhanced and the underlying interference within the background noise can be mitigated.
Compared to passive RIS, the active RIS can not only adapt the phase shift of each reflecting element but also amplify the incident signals.
The authors formulate an optimization problem to maximize the detection probability given a maximum tolerable false alarm probability and limited sensing time. This problem is transformed into an equivalent weighted mean square error minimization problem using the WMMSE algorithm.
An iterative optimization approach is proposed to obtain the optimal reflecting coefficient matrix (RCM) for the active RIS.
The authors also study a special case where the direct links are neglected and the RIS-related channels are line-of-sight. The required power budget of the active RIS and passive RIS to achieve a target detection probability are compared.
Simulation results demonstrate the effectiveness of the WMMSE-based RCM optimization approach. The active RIS can outperform the passive RIS when the underlying interference is relatively weak, while the passive RIS performs better in strong interference scenarios.
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by Jungang Ge,Y... a las arxiv.org 04-29-2024
https://arxiv.org/pdf/2311.16568.pdfConsultas más profundas