Research On Low Power Techniques For IoT Based On 3GPP R13 Standard

In recent years,there are wide application about Internet of Things(Io T)with huge amount of users and many terminals use battery power supply.A long-term replacement of battery will waste much labor and material resources,so it is urgent to reduce energy consumption of Io T terminal equipment.The low power techniques can be studied based on the relevant provisions of the Standard R13 in 3GPP.This thesis firstly proposes a grouping-based self-adaptive period adjustment strategy,aiming at problem of channel congestion and wasting energy for responding simultaneously.Each terminal is automatically classified according to its own application and system configures corresponding parameters according to the classified category.Then,devices select a more suitable cycle using machine learning and only work within the selected cycle in accordance with specific rules.Therefore,this strategy can reduce channel congestion and energy wasting.Secondly,in view of the waste of energy consumption for unreasonable working time,it is proposed to reduce power consumption by controlling working time of equipment.Focusing on the Power Saving Mode(PSM)and the extended Discontinuous Reception(e DRX)technology,the related parameters are controlled to control the working time of terminals.Finally,system simulation is performed on the data transmission.Combined with the specific transmission process,the low power techniques are studied on the NS3 platform.Simulation results show that energy consumption and delay are mutually restrictive.The low power techniques involved in this subject are mainly based on the Standard 13 in 3GPP,which mainly reduces the power consumption by controlling the working time of the terminals.In actual application,terminals are grouped first and then working hours are controlled to reduce system power consumption.This research can provide a basis for the subsequent work to reduce energy consumption of the Internet of Things system.