Optimal Resource Allocation and Interference Management for Multi-User Uplink Light Communication Systems With Angular Diversity Technology

• Published in: IEEE access 2020-01, Vol.8, p.203224-203236
• Main Authors: Eldeeb, Hossien B., Hosney, Mona, Elsayed, Hany M., Badr, Ragia I., Uysal, Murat, Selmy, Hossam A. I.
• Format: Article
• Language: English
• Subjects: angular diversity; Communications systems; Engineering Sciences; Genetic algorithms; inter-symbol-interference; inter-user-interference; Interference; Light communications; multi-user light communication networks; Near infrared radiation; Optical communication; Optics; Optimization; Performance degradation; Photonic; Resource allocation; Resource management; Signal to noise ratio; Simulation; Transmitters; Uplink; visible light communication; Wireless networks
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3036616

Light communication (LC) technology has been regarded as a promising candidate for future indoor wireless networks by providing safe, power-efficient, and high data rate communications needed for tomorrow's applications. Both visible light (VL) and infrared (IR) wavelengths can be utilized to design LC systems. It is often proposed that VL can be used to offload downlink traffic while near-IR is typically used in the uplink. In this paper, the uplink multi-user LC system is considered where the system performance is degraded by both inter-symbol interference (ISI) resulting from multipath reflections and inter-user interference (IUI) coming from neighboring users. To mitigate these limitations, an optimal fair resource allocation (OFRA) scheme is proposed which aims to improve the fairness among the users in terms of their received signal to interference plus noise ratios (SINRs) by implementing the angle diversity technology. Precisely, by assigning an ON/OFF state for each LED of the angle diversity transmitter (ADT), used by each user, the IUI can be significantly reduced. Also, the angle diversity receiver (ADR) is used to effectively mitigate the effects of ISI. The allocation matrix which achieves the highest fairness between different users is obtained for different scenarios of user distribution. Toward this, the exhaustive search (ES) method is used to obtain the optimal solution for the optimization problem under consideration. However, to reduce the time complexity of ES method, a quasi-optimal solution called sub-optimal fair resource allocation scheme SFRA is proposed. The sub-optimal solution is based on the genetic algorithm (GA) scheme. The simulation results reveal that both the OFRA and SFRA achieve almost the same performance. Moreover, the simulation results indicate the superior performance of the proposed OFRA scheme over the conventional single transmitter (ST) one.