Research On Access And Load Balancing Technology For IoT Ultra-dense Scenarios

Mobile communication technologies are widely used in many related fields of our daily life and brought tremendous changes and innovations to various industries,bringing people into the era of intelligence.With the rapid development of new IoT services such as intelligent transportation,smart homes,and smart manufacturing,it is expected that future Machine to Machine(M2M)devices that communicate over LTE-A networks will explode.However,LTE-A is designed to handle communication between Human to Human(H2H)and its current capacity is limited to handle large-scale M2 M communications.The large number of M2 M devices,the variety of business types,Moreover,the large number of M2 M devices,extremely rich service types,and irregular distribution are different from the traditional H2 H communication features.This is going to have A huge impact on the existing LTE-A,which is the process of the M2 M device based on the random access to the race,and the load-balancing of the boundary of the neighborhood.Therefore,integrating the future 5G to solve the massive M2 M device access problem has always been the direction that the industry is exploring.Based on the current research status of M2 M communication in the future 5G network,this thesis solves the problems of congestion and boundary load balancing caused by random access of large-scale M2 M devices.The research work of this thesis is as follows:Considering that the current LTE system is mainly for H2 H communications,the characteristics of the random access process based on the slotted ALOHA protocol determine that massive M2 M devices cannot initiate access at the same time.When the number of M2 M device reaches a certain,threshold,a serious collision occurs in the system,which results in a serious decline in the connection throughput of the system.Therefore,this thesis proposes an adaptive random access optimization strategy based on load estimation for the above problems.to maximize the system throughput and reduce the access delay.As the future 5G cellular communication network will adopt the UDN approach,the environment in the overlapped area of different cells will be more complicated,so a large number of M2 M devices will stay in this area for a long time,causing serious interference between each other and reducing the throughput of the system.To increase the throughput of overlapped area users through system resource schedule,and ensure the highest utilization rate of system resources.,we proposes a genetic algorithm based cell load balancing strategy.The whole throughput of the cross coverage area is significantly optimized thought joint access control for the devices in this cross coverage area conducted by multi-cells.