Abstract
In this paper, we evaluate and optimize the throughput of STAR-RIS for underlay cognitive radio networks (CRN) with energy harvesting from radio frequency (RF) signals. The secondary source \(S_\textrm{S}\) harvests power from node A RF signal. Then, \(S_\textrm{S}\) adapts its power to control the interference at primary destination \(P_\textrm{D}\). The broadcasted signal will be delivered to two users \(U_\textrm{t}\) and \(U_\textrm{r}\) located in the space of transmission and reflection of STAR-RIS in the secondary network. When STAR-RIS is used, the signal to interference plus noise ratio (SINR) at users \(U_\textrm{t}\) and \(U_\textrm{r}\) is maximized by a wise optimization of STAR-RIS phases. STAR-RIS offers a diversity equal to the number of its elements N. Therefore, when the number of STAR-RIS elements N is doubled, we get up to 15 dB gain.
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Alhamad, R., Boujemâa, H. Simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) with energy harvesting and adaptive power. SIViP 18, 1155–1160 (2024). https://doi.org/10.1007/s11760-023-02822-6
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DOI: https://doi.org/10.1007/s11760-023-02822-6