Channel modeling and capacity optimization for optical RIS aided NOMA in indoor multiuser visible light communication IoT systems

Abstract

This work explores solutions for addressing challenges in visible light communication (VLC) within 5G networks, particularly for indoor environments and green Internet of Things (IoT) applications, while considering the evolving demands of 6G networks. These demands include higher spectral efficiency (SE), enhanced data rates, reduced complexity, and reliable quality of service (QoS) for users with varying mobility. The proposed solution integrates optical reconfigurable intelligent surfaces (ORIS)-aided multiple-input multiple-output (MIMO) technology with a novel non-orthogonal multiple access (NOMA) transmission system employing discrete Fourier transform spread orthogonal time-frequency space (DFT-s-OTFS) modulation. This framework enhances spatial diversity, optimizes bandwidth, minimizes Peak-to-Average Power Ratio (PAPR), and improves power allocation. By leveraging OTFS modulation, the system supports delay-Doppler (DD) channels and ensures better control over VLC-IoT environments with physical layer security (PLS). A VLC channel model incorporating MIMO technologies for ORIS-aided NOMA-OTFS systems is developed, addressing a capacity maximization problem that considers transceiver parameters, RIS reflections, transmit power, and DD channels. An optimal solution is achieved using a relaxation algorithm. Numerical results show that the proposed ORIS-aided DFT-s-OTFS-based NOMA-MIMO VLC system outperforms the ORIS-assisted OFDM regarding bit error rate (BER), significantly improving channel capacity, SE, and security rates. These findings provide valuable insights for advancing optical RIS-assisted MIMO-VLC technologies.