Research On Energy Consumption Optimization Of Narrowband Internet Of Things Terminal For Power Monitoring

With the advent of the Internet of Everything,the technology of Internet of things has been developed unprecedentedly.The LPWA(Low Power Wide Area,LPWA)technology represented by NB-IoT(Narrow Band Internet of Things,NB-IoT)emerges as the times require,which provides a strong driving force for the development of smart grid.However,when it comes to power monitoring in application scenarios such as power manhole covers and power pipe corridors,how to extend the service life of the terminal is still a difficult problem.Although the amount of data obtained by this kind of monitoring is small,the distribution of power monitoring terminals is wide and the geographical environment is complex and diverse.It is often difficult to replace the battery of the monitoring terminal,which limits the life of the terminal.Therefore,it is of great significance to research the energy consumption optimization of NB-IoT terminals for power monitoring.The main work of this dissertation is as follows:(1)Aiming at the energy consumption optimization of NB-IoT terminal for power monitoring,in this dissertation,the periodic active reporting service with the largest number and the most basic carried by the power monitoring terminal is selected as an example,and constructs a terminal state transition model based on Markov.The advantage of this model is that the terminal offline state is added for the first time,and the terminal connection state and sleep state are further divided into random access state,data receiving state,short period sleep state and long period sleep state,so as to further refine the energy dissipation source of the terminal.And then the corresponding energy consumption and time delay analysis model is proposed.Through the systematic analysis,the energy consumption distribution of NB-IoT terminal state is obtained,which provides a targeted optimization direction for the research on the optimization of energy consumption of NB-IoT terminal.At the same time,a brief optimal configuration scheme is given according to the analysis results.(2)Serious network congestion in random access will consume a lot of energy of NB-IoT terminal.In order to reduce the energy consumption of NB-IoT terminal in the state of random access,this dissertation proposes a random access algorithm mACB based on dynamic priority and adaptive parameter update.Firstly,through analyzing the working process of ACB strategy in the process of random access,the mathematical model of network load monitoring is established,and the change of network load is predicted and estimated.Then,according to the network load prediction results,an adaptive parameter updating function is constructed to adaptively update the random access restriction factor p to maximize the system throughput.Furthermore,combined with the task priority requirements of different terminals in NB-IoT power monitoring terminal,a delay oriented terminal access priority classification scheme is proposed.Finally,mACB algorithm is proposed based on the above analysis.Simulation results show that compared with ACB algorithm and EAB algorithm,the mACB algorithm can maintain higher access success rate and lower access average delay in the case of large-scale NB-IoT terminal random access,and can effectively avoid NB-IoT terminal consuming a lot of energy due to network congestion in the process of random access.(3)Taking the power well cover monitoring task as an example,a low-energy NB-IoT terminal system for power well cover monitoring is designed.In this dissertation,the low-energy consumption system is designed from the aspects of hardware chip selection,program control and hardware circuit combination,data transmission protocol and platform algorithm combination,etc.At the same time,the network attached scheme and data transmission scheme are designed for the terminal,so as to achieve the purpose of reducing the terminal energy consumption.