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This paper explores reconfigurable intelligent surfaces (RIS) for mitigating cross-system interference in spectrum sharing applications. Unlike conventional reflect-only RIS that can only adjust the phase of the incoming signal, a hybrid RIS is considered that can configure the phase and modulus of the impinging signal by absorbing part of the signal energy. We investigate two spectrum sharing scenarios: (1) Spectral coexistence of radar and communication systems, where a convex optimization problem is formulated to minimize the Frobenius norm of the channel matrix from the communication base station to the radar receiver, and (2) Spectrum sharing in device-to-device (D2D) communications, where a max-min scheme that optimizes the worst-case signal-to-interference-plus-noise ratio (SINR) among the D2D links is formulated, and then solved through fractional programming. Numerical results show that with a sufficient number of elements, the hybrid RIS can in many cases completely eliminate the interference, unlike a conventional non-absorptive RIS. 

Reconfigurable intelligent surface (RIS) technology is a promising approach being considered for future wireless communications due to its ability to control signal propagation with low-cost elements. This paper explores the use of an RIS for clutter mitigation and target detection in radar systems. Unlike conventional reflect-only RIS, which can only adjust the phase of the reflected signal, or active RIS, which can also amplify the reflected signal at the cost of significantly higher complexity, noise, and power consumption, we exploit hybrid RIS that can configure both the phase and modulus of the impinging signal by absorbing part of the signal energy. Such RIS can be considered as a compromise solution between conventional reflect-only and active RIS in terms of complexity, power consumption, and degrees of freedoms (DoFs). We consider two clutter suppression scenarios: with and without knowledge of the target range cell. The RIS design is formulated by minimizing the received clutter echo energy when there is no information regarding the potential target range cell. This turns out to be a convex problem and can be efficiently solved. On the other hand, when target range cell information is available, we maximize the received signal-to-noise-plus-interference ratio (SINR). The resulting non-convex optimization problem is solved through fractional programming algorithms. Numerical results are presented to demonstrate the performance of the proposed hybrid RIS in comparison with conventional RIS in clutter suppression for target detection.