arXiv subjects

Marko Fidanovski

Publications and source records attributed to Marko Fidanovski.

5 recordsLinked to original sources

arXiv2026

Group-Connected Riemannian Manifold Optimization for Reciprocal BD-RIS

Reconfigurable intelligent surfaces (RISs) provide a flexible means of engineering wireless propagation channels through configurable multiport scattering networks. Among their architectures, group-connected beyond-diagonal RISs (BD-RISs) offer a practical tradeoff between scattering flexibility and hardware complexity by partitioning the surface into inter-connected groups. In reciprocal and lossless implementations, each group scattering block must be symmetric and unitary. In this paper, we investigate sum-rate maximization for reciprocal group-connected BD-RIS-assisted multiple-input multiple-output (MIMO) systems under such structural constraints. In particular, we build on a recent result where the feasible space determined by the symmetry and unitary constraints was characterized as a Riemannian manifold, extending it into a product manifold of symmetric-unitary block manifolds, thus expanding the approach to manifold phase optimization in the group-connected setting. As a consequence, the proposed group-extended framework performs tangent-space projections and Takagi retractions block-wise, while preserving the coupling among all groups through the common MIMO equivalent channel. The formulation naturally includes single-connected and fully connected reciprocal BD-RIS architectures as special cases and enables a flexible performance-complexity tradeoff through the group size.

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arXiv2026

Reciprocal Beyond Diagonal Reconfigurable Intelligent Surface: Distributed Scattering Matrix Design and MIMO Beamforming via Fractional Programming and Manifold Optimization

We consider the optimization of beyond diagonal reconfigurable intelligent surface (BD-RIS)-aided multi-user (MU) cell-free (CF)-massive multiple-input multiple-output (mMIMO) systems, where the propagation environment design achieved scattering matrix optimization is complemented by developing an efficient base station (BS) beamforming (BF) scheme that effectively exploits the latter ``engineered'' channel. In particular, we describe a fractional programming (FP) method, which based on the equivalent channel incorporating a reciprocal BD-RIS (RBD-RIS) parameterized by existing scattering matrix design methods, yielding the correspondingly optimized multiple-input multiple-output (MIMO) BF weights. The proposed approach decomposes the transmit (TX) beamformer into multiple sum-rate maximization (SRM) sub-beamformers, each satisfying an independent power-constraint, such that distributed MIMO-BF scenarios can be optimally handled. Although the proposed SRM-MIMO-BF framework is independent of the specific scattering matrix design, extending the BD-RIS-aided system model to the CF-mMIMO setting requires the design of a corresponding beamforming matrix. In this context, this work investigates the impact of beamforming in reconfigurable intelligent surface (RIS)-aided systems. Simulation results demonstrate that the proposed method for designing the MIMO-BF weights, when combined with the previously developed design of reciprocal BD-RIS (RBD-RIS) scattering matrices, outperforms existing BD-RIS-aided state-of-the-art (SotA) schemes employing existing MIMO-BF techniques, indicating that the whole contribution is more than the sum of the parts.

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arXiv2025

Fractional Programming and Manifold Optimization for Reciprocal BD-RIS Scattering Matrix Design

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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arXiv2025

Reciprocal Beyond-Diagonal Reconfigurable Intelligent Surface (BD-RIS): Scattering Matrix Design via Manifold Optimization

Beyond-diagonal reconfigurable intelligent surfaces (BD-RISs) are emerging as a transformative technology in wireless communications, enabling enhanced performance and quality of service (QoS) of wireless systems in harsh urban environments due to their relatively low cost and advanced signal processing capabilities. Generally, BD-RIS systems are employed to improve robustness, increase achievable rates, and enhance energy efficiency of wireless systems in both direct and indirect ways. The direct way is to produce a favorable propagation environment via the design of optimized scattering matrices, while the indirect way is to reap additional improvements via the design of multiple-input multiple-output (MIMO) beamformers that further exploit the latter "engineered" medium. In this article, the problem of sum-rate maximization via BD-RIS is examined, with a focus on feasibility, namely low-complexity physical implementation, by enforcing reciprocity in the BD-RIS design in a manner that adheres to the geometry of the manifold of symmetric matrices. To that end, the sum-rate objective is transformed into a quadratic function via fractional programming (FP), augmented via the also quadratic reciprocity constraint in the form of a regularization term, while the unitary constraint is dealt with via a manifold optimization framework. Simulation results demonstrate the effectiveness of the proposed method in outperforming current state-of-the-art (SotA) approaches in terms of sum-rate maximization.

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arXiv2025

Low-complexity Leakage Minimization Beamforming for Large-scale Multi-user Cell-Free Massive MIMO

We propose a low-complexity beamforming (BF) scheme for secrecy-rate maximization in multi-user (MU) cell-free massive multiple-input multiple-output (CF-mMIMO) systems, where legitimate users may act as non-colluding eavesdroppers of one another. To this end, we formulate an information leakage minimization problem and cast it into a tractable difference-of-convex algorithmic (DCA) form by leveraging fractional programming (FP). The resulting non-convex problem is solved through a concave-convex procedure (CCP)-based beamformer update, and an additional row-wise coordinate descent method (CDM) implementation is introduced to avoid explicit matrix inversion in the dominant linear-solve step. Additionally, we consider both direct transmit (TX)-BF and beyond-diagonal reconfigurable intelligent surface (BD-RIS)-assisted operation by defining an equivalent channel between each access point and user that combines the direct and reflective intelligent surface (RIS)-assisted propagation components. Simulation results show that the proposed secrecy-enhancement via leakage minimization (SecLM)-BF framework achieves secrecy and sum-rate performance close to state-of-the-art (SotA) semidefinite programming (SDP)-based benchmarks, as well as FP-based benchmarks, while providing a scalable inversion-free implementation for large-scale secure CF-mMIMO deployments.

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