Research On Resource Allocation Technology For Heterogeneous Networks Of Visible Optical Communication And Wireless Communication

The booming development of smart cities,Smart Business,and smart industries urgently requires advanced technologies that enable high-speed multi-user communication networks.In particular,the rapid expansion and development of the Internet of things industry has triggered an emerging demand for spectrum resources.Therefore,visible light communication is considered as a promising technology to solve the above problems.In recent years,visible light communication has received attention from many aspects because it is green and environmentally friendly.Specifically,VLC uses a free and abundant visible spectrum resource that does not require licensing.It does not generate excess electromagnetic radiation and allows for high data rate communication while meeting normal lighting requirements.On the other hand,heterogeneous wireless networks have been proposed to enable wireless networks of different technologies to work together and be able to compensate for their respective disadvantages in order to improve the overall system performance.In this paper,we focus on heterogeneous networks with VLC/RF and address the problem of resource allocation in single-user and multi-user states.The main work is as follows.Firstly,the single-user VLC/RF heterogeneous network is studied,and the channel capacity formula for the single-user case is derived considering the characteristics of visible light communication,and the proposed energy efficiency optimization problem is solved.This resource optimization problem is a typical fractional programming nonconvex problem,and we use the Dinkelbach method to transform it into a convex problem.The analytical solution of the transformed convex problem is then solved,and the optimal solution of the original problem is solved iteratively.In addition,the convergence properties of the iterative algorithm are demonstrated,and the corresponding simulation results show that the proposed algorithm eventually converges to an exact value within the error tolerance range at a fast rate.Secondly,for the multi-user VLC/RF heterogeneous network,the model of MISO is used in both systems.Considering the practical situation and adapting to the characteristics of visible light communication,the channel capacity formula of this heterogeneous network is firstly derived,and the problem of optimizing the total transmission rate of the system and the allocation of power is presented.In order to solve the two basic resource optimization problems,a combination of the semidefinite relaxation and successive convex approximation is proposed to gradually transform the problem into a convex one.To approximate the optimal results,iterative optimization is also performed to achieve the desired results within the error range.Finally,simulations are performed to verify the convergence properties of the proposed algorithm and to analyze the impact of each variable as well as the user location on the system as a whole.Thirdly,the problem of energy transmission in a multi-user VLC/RF heterogeneous network is investigated,where the VLC system transmits both energy and information to the users,who use the collected energy for federal learning to update the gradient data and transmit the data on the uplink.In this scenario,the power optimization problem is presented.The time required for federal learning and uplink transmission of data,as well as the beamforming vectors of the VLC and RF systems,are optimized within the constraints of the data rate and the transmission energy of the downlink VLC system.To solve the problem,the optimization problem was split according to the analysis,and the variables were solved using methods such as golden section search and semi-positive definite relaxation.Finally,simulation analysis was conducted to verify the feasibility of the system and to analyze the impact of each variable on the overall system.