In this paper, we propose a robust transmission design for multi-user systems assisted by a fluid active reconfigurable intelligent surface (FARIS), which enables both active reflection and dynamic port selection and thereby offers enhanced flexibility, under imperfect channel state information (CSI). We formulate a robust minimum sum-rate maximization problem by jointly optimizing the base station beamformer, the utilized FARIS coefficients, and the active element selection, while explicitly accounting for CSI errors and practical power constraints. The resulting problem is inherently nonconvex due to the coupled optimization variables and discrete port-selection structure. To tackle this challenge, we first reformulate the original problem via a weighted minimum mean square error (WMMSE) approach and then devise an alternating optimization (AO) framework, where each resulting subproblem admits efficient solutions and the overall algorithm converges to a stationary point. Simulation results demonstrate that the proposed robust FARIS scheme consistently outperforms conventional designs, highlighting the effectiveness of jointly leveraging degree-of-freedom (DoF) enhancement and active signal amplification under CSI uncertainty.
Hong-Bae Jeon, Yonghwi Kim, Hyung-Joo Moon et al.· 0 citations
This paper investigates a fluid active reconfigurable intelligent surface (FARIS)-aided downlink non-orthogonal multiple access (NOMA) system. We formulate a network sum-rate maximization problem that jointly optimizes user clustering, NOMA power allocation, FARIS amplification gains, discrete phase shifts, and fluid element selection under quality-of-service, reflected-power, and hardware constraints. To address the resulting nonconvex mixed-integer problem, we develop a two-stage framework comprising distance-based interleaved clustering for constructing successive-interference-cancellation (SIC)-friendly user groups and per-cluster alternating optimization. The resulting subproblems are handled using geometric programming (GP), fractional programming (FP), majorization-minimization (MM) with mixed-integer phase optimization, and the cross-entropy method (CEM). Numerical results demonstrate rapid convergence, near-optimal performance relative to brute-force search (BFS)-based optimum, and consistently outperforms the benchmarks. These results verify the effectiveness of jointly integrating FARIS and NOMA for high-rate downlink transmission.
A tailored alternating optimization framework is developed that decomposes the original joint design into tractable subproblems, where each admits an efficient solution while preserving the system constraints, enabling an effective joint optimization of beamforming and FARIS reconfiguration.
Hong-Bae Jeon, Yonghwi Kim, Hyung-Joo Moon et al.· 0 citations
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