Research On Resource Management Based On Two-level Hierarchical In Massive Machine-Type Communications

With the rapid development of Internet of Things(IoT),traditional Human-to-Human Communications(HTC)will not be able to meet the growing communication demands.On the characteristics of huge connections and low power consumption,massive Machine-Type Communications(mMTC)has become an important application in the Fifth Generation Mobile Communication System(5G).This thesis focuses on the resource management strategy in mMTC.Firstly,based on the characteristic of massive connections in mMTC and a two-level hierarchical model of mMTC in LTE network,a MTCG power control scheme based on the the number of users served by MTCG is proposed.A general expression of the MTCG transmit power is given.After that,the burst scenario is taken into consideration to give the excat expression of the transmit power.Secondly,under the condition of MTCGs coexisting with LTE users,the interference problems between them are studied.Based on the proposed power control strategegy,the interference models of LTE users and MTCGs are carefully discussed.The exact expressions described by outage probability between LTE users and MTCGs are given.Finally,the resource allocation problem in the coexistence between mMTC and traditional LTE network is studied.In order to maximize the total MTCG sum rate,a resource allocation model between them is established,and a resource allocation algorithm based on mMTC service classification is proposed.Some conclusion can be obtained by the simulation results:(1)The power control scheme and interference analysis models proposed in this paper are effective and can be referenced by user grouping among Machine-Type Communications Devices and flexible networking;(2)The algorithm based on service classification proposed in this thesis can improve the reliability of network systems as well as ensure the system capacity.