Fractional Programming and Manifold Optimization for Reciprocal BD-RIS Scattering Matrix Design
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We investigate the problem of maximizing the sum-rate performance of a beyond-diagonal reconfigurable intelligent surface (BD-RIS)-aided multi-user (MU)-multiple-input single-output (MISO) system using fractional programming (FP) techniques. More specifically, we leverage the Lagrangian Dual Transform (LDT) and Quadratic Transform (QT) to derive an equivalent objective function which is then solved iteratively via a manifold optimization framework. It is shown that these techniques reduce the complexity of the optimization problem for the scattering matrix solution, while also providing notable performance gains compared to state-of-the-art (SotA) methods under the same system conditions. Simulation results confirm the effectiveness of the proposed method in improving sum-rate performance.
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Cited by 2 Pith papers
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Reciprocal Beyond Diagonal Reconfigurable Intelligent Surface: Distributed Scattering Matrix Design and MIMO Beamforming via Fractional Programming and Manifold Optimization
FP-based distributed MIMO beamforming for RBD-RIS in CF-mMIMO outperforms SotA when paired with prior reciprocal scattering matrix designs.
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Tree Search Algorithms Applied to the BD-RIS Configuration in MU-MISO Communication Systems
A depth-first tree search algorithm is proposed for BD-RIS configuration in MU-MISO systems to achieve a performance-complexity trade-off in channel strength maximization.
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