Research On Joint Resource Allocation In LTE-Advanced Based Internet Of Vehicles Network And Building Of Application Platform

As a kind of service-based network, Internet of Vehicles (IoV) realizes the real-time information exchange between vehicles, vehicle and roadside infrastructure, vehicle and people, greatly facilitates the daily life of people. At the beginning, the widely accepted network architecture of IoV is based on Institute of Electrical and Electronics Engineers (IEEE) 802.11p, which exists many disadvantages, such as large investment costs, bandwidth limited and easy to cause broadcast storms. With the rapid development of mobile communication technology, researchers propose the LTE-Advanced (such as high transmission rate and low transmission delay, etc)-based IoV, which has many advantages, such as small investment costs, low operating costs and higher transmission rate, etc. It has become one of the effective solutions for future IoV implementation.Although mobile communication based-IoV has a lot of advantages, it still faces a number of challenges. From the aspect of access layer, the fast-moving of users, harsh environment and time-varying wireless channel conditions in IoV make wireless resource allocation difficult. There is a need to guarantee the quality of service (QoS) of business in complex communication environment. From the aspect of application layer, IoV based application platform can provide users with safe driving, intelligent navigation as well as Internet access services, which is also the hot area in the industry now. This paper will study the above two aspects respectively. The main work of this paper is as follows:Firstly, this paper designs an energy efficient and distributed joint resource allocation algorithm in the LTE-Advanced-based IoV. The wireless channel environment of heterogeneous network in LTE-Advanced and the challenges of resource allocation brought by the IoV environment are analyzed. Then, in order to maximize the energy efficiency, the resource allocation problem is modeled based on Q-learning. A bisection-based power adaptation algorithm is proposed to obtain the optimal power allocation based on the resource block allocation, The power allocation result is returned back as the immediate reward. And eventually the optimal joint resource allocation policy is presented. The simulation results show that the proposed algorithm can better adapt to the fast time-varying wireless channel of IoV, improve the system energy efficiency and ensure the spectrum efficiency.Secondly, a location-based IoV application platform is constructed. It is based on Client/Server (C/S) architecture, by using the development tools:MyEclipse and MySQL, relying on the JSON data communication principle. At first, this paper carries out detailed requirement analysis and summarized the existing IoV application platforms. Then, from the perspective of traffic scheduling and user-friendly travel, this paper establishes the related application platform to realize two basic functions, the release and query of traffic information, obtain and recommend of surrounding information. The application platform designed by this paper is based on the location information, by the interaction between vehicle and vehicle, vehicle and roadside infrastructure, vehicle and people, can achieve two basic functions of IoV. The proposed platform has good portability and scalability at the same time and can also provide some reference for future development of IoV application platform.