Design And Implementation Of A Radio Resource Management Simulator For 5G Supporting IoT Applications

With the rapid expansion of network scale and the significant increment of users'demand for network resources,the network testing cost and total system resource demand are obviously improved.If the actual test method is still used to verify the network performance,there will be some problems such as limited system resources and unstable experimental results.Therefore,the simulation platform is often used for simulation.Through a simulation platform,we can not only study various network core issues,such as radio resource allocation,link congestion control and network protocol improve,but also to evaluate and improve network performance.However,existing platforms seldomly focus on the simulations of traffic of massive Internet of Things(IoT)devices over 5G mobile communication networks.In this dissertation,we design a new platform specifically focusing on radio resource management(RRM)simulations for the traffic of massive IoT devices over 5G networks.Referring to the existing platform design schemes,this platform completed the basic architecture with the event scheduler as the core,and designed various key modules.Meanwhile,combined with the serial processing of multiple RRM technologies,the platform designed a multi-resource management joint efficient simulation scheme,and a variety of RRM components such as cell selection and interference coordination are implemented.In addition,to improve the integrity of the whole design,two typical scenarios of indoor office and outdoor city road,and various IoT applications obeying specific distribution characteristics are also implemented.Considering the number of terminals is large and the volume of traffic is intensive in hyper density scenarios,.if the packets are still processed by event scheduling,there will be too many events and too long processing time.Thus,a matrix operation based mass processing framework is designed.This mass processing framework divides the time axis into virtual time slots and maps the packets to the slots.Then,the strength of effective signal and interference signal can be calculated for each slot,hence system capacity,throughput and other performance metrics can be obtained.Simulation results show that the platform based on this scheme will be significantly faster than the traditional platforms,which can be a valid tool for researchers to evaluate the performance of RRM schemes for massive IoT devices over 5G networks.