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RIS-Assisted Generalized Receive Quadrature Spatial Modulation with Extension to Multicast Communications

2023/11/30 by Mohamad H. Dinan, Dinan, Mohamad H., Nadali, Khatereh +1
Engineering · #Advanced Antenna and Metasurface Technologies #Advanced Wireless Communication Technologies #FOS: Computer and information sciences #FOS: Electrical engineering #Information Theory (cs.IT) #Satellite Communication Systems #Signal Processing (eess.SP) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2311.18542

openalex publication_date 2023/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper proposes a novel reconfigurable intelligent surface (RIS)-assisted generalized receive quadrature spatial modulation (RIS-GRQSM) scheme to enhance the spectral efficiency (SE) of RIS-aided quadrature spatial modulation (QSM) systems. By leveraging the principle of generalized spatial modulation (GSM), multiple receive antennas are independently activated for both the in-phase and quadrature components of spatial symbols. To fully exploit the potential of RIS, we formulate a max-min optimization problem to adjust the phase shifts of all RIS elements, thereby maximizing the effective signal-to-noise ratios (SNRs) at the activated antennas. Using Lagrange duality, the original high-dimensional non-convex problem is reduced to a tractable problem with a smaller number of real variables, and a closed-form suboptimal solution is also proposed, which achieves near-optimal performance with a sufficiently large RIS. At the receiver, a low-complexity non-coherent energy-based greedy detector (GD) is introduced for efficient symbol detection. We further extend the RIS-GRQSM framework to a multicast communication system, where all users receive identical information with equal SNR levels, and provide a detailed performance analysis of both systems. In particular, we derive the average bit error probability (ABEP) for the proposed RIS-GRQSM and multicast systems under optimal and suboptimal optimization strategies. Numerical results show that RIS-GRQSM significantly improves the SE and error rate performance compared with benchmark schemes, while the multicast extension achieves performance close to benchmark methods at substantially lower complexity.

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