An Intelligent Quantum-Supported Resource Allocation Framework for Advanced Indoor Non-Orthogonal Multiple Access Optical Wireless Networks

Abstract

At present, non-orthogonal multiple access (NOMA) has become the most efficient technique to solve data rate (DR) requirements in visible light communication (VLC) systems. However, present NOMA systems show high interference and increase the peak-to-average power ratio (PAPR), especially in wider applications. To overcome this issue, several techniques have been undertaken in the past and provento better communication performance. However, the existing studies fail to provide a better quality of services (QoS) for the recent multi-carrier optical communication system (OCS). Hence, this study put forth a novel Generalized Frequency Division Multiplexing (GFDM) scheme to minimize the PAPR inan indoor-based NOMA-VLC system. To enhance the performance of the GFDM system, a novel offset-based quadrature amplitude modulation (OQAM) technique is introduced that enhances the signal quality and prevents the co-channel interference (CCI) problems effectively. Moreover, the proposed study introduces a novel quantum-enabled rabbit optimization (QRO) technique for solving resource allocation (RA) problems in the NOMA-VLC system. The proposed method is processed via the MATLAB platform and various performance measures like sum rate (SR), signal-to-interference noise ratio (SINR), and symbol error rate (SER) are analyzed and distinguished with various existing studies. In the simulation scenario, the proposed method achieves the SR of 178Mbps, SINR of 16dB, and SER of 10^-8 compared to conventional techniques.