arXiv subjects

Zhu Shoujin

Publications and source records attributed to Zhu Shoujin.

4 recordsLinked to original sources

arXiv2026

Exploiting Movable-Element STARS for Rate Splitting Multiple Access

This paper investigates a movable-element simultaneously transmitting and reflecting reconfigurable intelligent surface (ME-STARS) assisted rate-splitting multiple access (RSMA) system under imperfect channel state information (CSI). Unlike conventional STARS with fixed element positions, the elements of ME-STARS can be repositioned within a predefined region, providing additional spatial degrees of freedom for improving the cascaded transmitter--STARS--user channels. To exploit this flexibility while accounting for CSI uncertainty, we formulate a robust sum-rate maximization problem that jointly optimizes the transmit beamforming, common-rate allocation, reflection and transmission coefficients, and ME-STARS element positions, subject to transmit-power, user-rate, minimum inter-element spacing, and movement-region constraints. The resulting problem is highly non-convex due to the strong coupling among the design variables and the position-dependent channels. To address this challenge, an iterative optimization framework is developed in which the transmit beamforming, STARS coefficients, and element positions are successively optimized through tractable convex reformulations. In particular, the element positions are updated sequentially using a majorization--minimization (MM) framework, where quadratic surrogate functions are constructed from the first- and second-order derivatives of the position-dependent channels while preserving the minimum inter-element spacing constraint. Simulation results demonstrate that the proposed ME-STARS design consistently outperforms the considered benchmark schemes. Moreover, the performance gains remain significant under increasing CSI uncertainty, highlighting the effectiveness of element repositioning for robust RSMA transmission.

eess.SP↗

arXiv2026

Robust Transmission Design for RIS-Assisted RSMA-SWIPT Systems With Movable Antennas Under Hardware Distortions

This paper investigates a robust transmission design for a multi-user rate-splitting multiple access (RSMA)-based simultaneous wireless information and power transfer (SWIPT) system empowered by movable antennas (MAs) and a reconfigurable intelligent surface (RIS) under channel state information (CSI) uncertainty and residual hardware impairments (HIs). The effective channels in MAs-enabled systems depend on antenna positions, causing CSI uncertainty to affect not only active and passive beamforming but also antenna position optimization. Furthermore, residual HIs distort the effective SINRs, creating additional coupling among beamforming, RIS reflection control, common-rate allocation, power-splitting ratio optimization, and antenna position optimization. Consequently, the joint impact of CSI uncertainty and HIs leads to a highly coupled and challenging resource allocation problem. To address this challenge, we propose a robust resource allocation framework that jointly optimizes common-rate allocation, transmit beamforming, RIS reflection coefficients, power-splitting ratios, and MAs positions to maximize the achievable sum-rate while satisfying practical system constraints. To obtain an efficient solution, the original problem is decomposed into active beamforming, RIS reflection design, power-splitting ratio optimization, and MAs position optimization subproblems, where tractable convex surrogate functions are constructed to handle the non-convex objective and constraints. Simulation results verify the effectiveness of the proposed framework and demonstrate substantial improvements in achievable sum-rate, robustness against CSI uncertainty and hardware impairments, and convergence performance compared with benchmark schemes.

eess.SP↗

arXiv2025

Robust Beamforming Optimization for STAR-RIS Empowered Multi-User RSMA Under Hardware Imperfections and Channel Uncertainty

This study explores the synergy between rate-splitting multiple access (RSMA) and simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) as a unified framework to enable ubiquitous, intelligent, and resilient connectivity in future sixth-generation networks, while improving spectral and energy efficiency. Specifically, we investigate a STAR-RIS-assisted multi-user RSMA system and develop an intelligent optimization strategy that jointly designs the transmitter's active beamforming, the common stream rate allocation, and the passive beamforming vectors for the STAR-RIS transmission and reflection regions, considering transceiver hardware impairments and imperfect channel state information (CSI). In addition, system robustness is ensured via a bounded channel estimation error model that captures CSI imperfections and guarantees resilience against worst-case errors. To address the highly non-convex problem, we propose an iterative optimization algorithm that decomposes it into two sub-problems. Firstly, active beamforming vectors for the common and private signals are determined by reformulating the original problem into a convex semi-definite programming (SDP) form using successive convex approximation (SCA) and semi-definite relaxation (SDR). Secondly, passive beamforming vectors are optimized through a convex SDP reformulation by exploiting SCA and SDR techniques. Moreover, when higher-rank solutions arise, Gaussian randomization is applied to obtain rank-one solutions. Numerical simulations demonstrate that the proposed strategy achieves significant performance gains over benchmark schemes and exhibits fast convergence.

eess.SP↗

arXiv2025

Robust Design of Beyond-Diagonal Reconfigurable Intelligent Surface Empowered RSMA-SWIPT System Under Channel Estimation Errors

This work explores the integration of rate-splitting multiple access (RSMA), simultaneous wireless information and power transfer (SWIPT), and beyond-diagonal reconfigurable intelligent surface (BD-RIS) to enhance the spectral-efficiency, energy-efficiency, coverage, and connectivity of future sixth-generation (6G) communication networks. Specifically, with a multiuser BD-RIS-empowered RSMA-SWIPT system, we jointly optimize the transmit precoding vectors, the common rate proportion of users, the power-splitting ratios, and scattering matrix of BD-RIS node, under the assumption of imperfect channel state information (CSI). Additionally, to better capture practical hardware behavior, we incorporate a nonlinear energy harvesting model under energy harvesting constraints. We design a robust optimization framework to maximize the system sum-rate, while explicitly accounting for the worst-case impact of CSI uncertainties. Further, we introduce an alternating optimization framework that partitions the problem into several blocks, which are optimized iteratively. More specifically, the transmit precoding vectors are optimized by reformulating the problem as a convex semidefinite programming through successive-convex approximation (SCA), whereas the power-splitting problem is solved using the MOSEK-enabled CVX toolbox. Subsequently, to optimize the scattering matrix of the BD-RIS, we first employ SCA to reformulate the problem into a convex form, and then design a manifold optimization strategy based on the Conjugate-Gradient method. Finally, numerical simulation results reveal that the proposed scheme provides significant performance improvements over existing benchmarks and demonstrates rapid convergence within a reasonable number of iterations.

eess.SP↗