| With the increasing demand for data traffic and the number of access devices,the existing wireless networks have been unable to meet the growing demand for services.Therefore,in the future dense wireless network scenarios such as smart cities and intelligent transportation,the increasing network demand can be met by increasing the density of base stations.Dense base stations can leverage their advantages in system capacity,spectrum efficiency,and data transmission rates,but they also bring new challenges.With the increasing density of base stations,the handvoer frequency of mobile users and devices will increase,resulting in problems such as lower data transmission rate,higher handover delay,ping-pong effect and increased demand for network resources.Therefore,it is necessary to introduce new technologies that can improve the network service quality of mobile users and devices,including Multiple Input Multiple Output(MIMO),millimeter wave communication,etc.Additionally,a reasonable resource allocation scheme is needed to improve the utilization efficiency of network resources such as backhaul link resources,caching resources,and computing resources.Different mobile users and devices exhibit distinct characteristics during their movement within the coverage range of wireless networks,mainly dependent on whether their movement tracks are regular in time or space.Therefore,this dissertation studies the regular and random moving trajectories to solve the quality of service problems caused by frequent handover.In this dissertation,an intelligent handover and resource allocation scheme based on mobility prediction is proposed for the heterogeneous network scenario composed of macro base stations and small base stations;A mobility resource allocation strategy based on fuzzy logic handover is proposed for the single-layer small base station scenario;and a mobility resource management optimization scheme for vehicle video services in vehicular network scenarios.Lastly,the performance of the proposed algorithms and mechanisms are validated through simulations.The main contributions and innovations of this dissertation are summarized as follows:1.An intelligent handover and resource allocation scheme based on mobility prediction is proposed.Firstly,the whole network space is divided into wireless areas covered by multiple access points,and the coverage of these macro base stations and small base stations has certain overlap.Then,the regularity of the historical moving trajectory data of mobile users is analyzed,and the evolving semi Markov model is used to predict the next possible location of users.Finally,the demand of users for network resources is obtained,and the most appropriate access base station is selected for mobile users at the desired location according to the proposed optimization model.This dissertation proposes an intelligent handover and resource allocation scheme based on mobility prediction to solve the problem of increased handover frequency caused by user mobility in heterogeneous networks.Its purpose is to minimize the number of handover for users with the same path length,thus reducing the overall handover delay and improving the utilization efficiency of network resources.Simulation results show that compared with the existing schemes,this scheme has better performance in improving the prediction accuracy and reducing the handover frequency.2.A mobility resource allocation strategy based on fuzzy logic theory for handover is proposedFirst,the Internet of things(IoT)device converts the mobile speed,the distance from the device to the MIMO base station providing services,and the transmission power of the base station into Boolean values according to the scene requirements,which serve as input values to the fuzzy logic controller.Second,a fuzzy logic controller model is established and a fuzzy logic-based handover algorithm is executed to obtain a handover threshold,thus effectively reducing the handover frequency of mobile IoT devices and improving the data transmission rate.Finally,according to the theoretical results of average throughput derived in this dissertation,the number of antennas of the corresponding MIMO base station is flexibly allocated for IoT devices with different data rate requirements,different mobile speeds and different numbers of receiving antennas.Aiming at the problems of frequent handover and data rate optimization of mobile IoT users in MIMO base stations,this dissertation proposes a mobility resource allocation strategy based on fuzzy logic theory to improve the data transmission rate of IoT devices.The simulation results show that the scheme has good performance in reducing the overall handover delay and improving the data transmission rate.3.A mobility resource management optimization scheme for vehicle video service is proposed.Firstly,based on the fact that high-definition video segments can be converted to low-definition video segments,a caching update algorithm is proposed,which takes into account the energy consumption of video transcoding when caching video segments in the base station.Then,according to the different usage of caching resources,computing resources and backhaul links of roadside base stations by vehicle users,a flexible network resource pricing algorithm is proposed,which can optimize the way for vehicle users to obtain the required video segments by adjusting the unit prices of backhaul links,transcoding and caching,so as to improve the flexibility of network resource allocation.Finally,the caching update algorithm and network resource pricing algorithm are applied to the process of providing video segments for vehicle users to improve the utilization efficiency of caching resources and the economic benefits of backhaul links,transcoding and caching.Aiming at the problem of inefficient utilization of network resources in the process of video acquisition by vehicle users,this dissertation proposes a mobile resource management optimization scheme for vehicle video services.Simulation results show that the total gain,caching gain and transcoding gain of the proposed scheme are significantly improved. |
