DC-Bias and Power Allocation for Energy and Information Transfer in VLC Networks

The growing demand for high data rate and licence-free spectrum applications has stimulated recently researchers to investigate the visible light communication (VLC) as a promising technique for indoor communication. This is especially the case because RF communications suffer from the scarcity of the available spectrum. As a solution, VLC is introduced in indoor environments to overcome the RF limitations as it provides better services to the users. In order to meet the new escalating demand for high data rate services and applications, visible light communication (VLC) has emerged as a promising solution for the fifth-generation (5G) wireless networks and beyond. Consider a VLC network, where multiple access points (APs) serve both energy-harvesting users (EHUs), i.e., users which harvest energy from light intensity, and information-users (IUs), i.e., users which gather data information. The performance of the system becomes a function of the direct current (DC) bias values allocated to each AP and the messages power. In this system, two utility functions needed to be maximized with considering fairness, illumination requirements, and LEDs ringe linear operational limits. These functions are the sum-rate function of the IUs and the total harvested energy of the EHUs. In this project, we aim at maximize both functions with a predefined weighting under a quality of service (QoS) requirements by allocating the DC-bias and messages power jointly. We also targeting formulate the optimization problem for each function with guaranteeing the predefined QoS constraints. The project then proposes solving such a difficult non-convex optimization problem using iterative approaches. The proposed algorithms use well-chosen approximations of the objective and constraints functions, and compensates for the approximations using proper outer-loop updates. The project further proposes sub-optimal heuristic algorithms which provide feasible, yet simple, solutions to the problem. Numerical results illustrate the convergence of the proposed algorithms, and highlight the significant performance improvement of the proposed algorithms as compared to the proposed baseline approach. The proposed research work is expected to result in several journal and conference papers.