| With the maturity of the fifth-generation mobile communication technology(5G)and the rapid development of massive the Internet of Things devices,the applications in industries enabled by 5G have been being important study orientations of mobile internet now and in the future.The applications motivate the advancement of vertical industries,aiming to provide more real-time and reliable connections for any type of device in any scenario to realize the target of supporting and leading the society to be with wider network coverage and more intelligent.Among them,the development of 5G-enabled medical scenarios has received great attention in recent years as one of the four aspects.On the one hand,it can enhance the penetration rate of medical services,and on the other hand,it can improve medical efficiency.In 5 G-enabled medical scenarios,wireless body area network technology is an important supporting technology.However,due to factors such as the vulnerability of the patient’s wireless body area network,the limited resources of equipment,and the uncertainty of individual patient conditions,there are many challenges in application.Therefore,this thesis focuses on in-depth research on the privacy and security of patient physiological data in 5G-based remote health monitoring applications,and inaccurate description and prediction of elderly patients’ vital signs in smart elderly care applications in large health scenarios,and proposes solutions.The main contents of the program are as follows:First,this thesis proposes a hybrid relay-forwarding-friendly interference security transmission strategy to solve the security threat of the transmission system by intelligent eavesdroppers in 5G-based remote health monitoring applications.Make full use of the medical sensors used to monitor physiological data.After adaptively selecting the relay and forwarding node,the remaining medical sensors serve as friendly interference nodes,and send friendly interference signals known to the personal medical server in both transmission stages.In order to achieve safe and secure transmission.Theoretical analysis and simulation verify that the proposed hybrid cooperative transmission strategy can resist the attacks of intelligent eavesdroppers and significantly enhance the security in the transmission process.Furthermore,this thesis proposes a physical layer authentication scheme process based on long short-term memory network to solve the problem of resource-constrained devices being illegally accessed by malicious nodes in remote health monitoring applications.Based on the difference in received signal strength,legal medical sensors and illegal malicious nodes are distinguished,and the long-short-term memory network model is iteratively trained.The experimental results show that the authentication accuracy rate of more than 93%can be achieved at different transmit powers of medical sensors,and the comparison with other algorithms shows the superiority of this scheme.Finally,this thesis proposes a mathematical model representing individual natural mortality based on affine jump diffusion process,to solve the problem that the uncertainty of individual natural death is difficult to describe in the application of smart elderly care in large health scenarios.The natural mortality model is obtained by combining the existing survival model with a random process.The mean and non-mean recovery processes were studied separately,and the jump process with exponential distribution,with gamma distribution and with affine jump intensity exponential distribution was applied to the non-mean recovery process to characterize the uncertainty of individual patient mortality.Through experimental verification and comparative analysis,the differences of each model are obtained,and the optimized model and its coefficient values within the research range are given,which verifies the robustness of the proposed model,and discussed the new model of future 5G-enabled medical and health monitoring scenarios based on big health scenarios. |
