EFFICIENT TRACKING AREA MANAGEMENT FRAMEWORK FOR 5G NERWORK

Abstract

To accommodate a various growing number of user equipment (UEs) on 5g networks. Managing with the huge signaling overhead expected from UEs is a main problem to tackle hence as to achieve this objective. In this thesis, they develop an efï¬cient tracking area list management (ETAM) system for 5G cloud-based mobile networks. The proposed system contains of two parts. The ï¬rst part is executed offline. The executed offline is responsible of assigning tracking areas (TAs) to TA lists (TALs). The second one is executed online. The executed online is responsible of the distribution of TALs on user equipment (UEs) during their movements across TA. For the ï¬rst part, they propose three keys, which are: (a) F-PAGING favoring the paging overhead over tracking area update (TAU), (b) F- TAU favoring TAU over paging, and (c) FOTA (i.e., Fair and Optimal Assignment of TALs to TAs) for a solution that uses bargaining game to ensure a fair tradeoff between TAU and paging overhead. For the second part, two solutions are proposed to assign in real time, TALs to different UEs. The computation load is kept lightweight in both solutions not to reduce the network performance. Also, both solutions do not need any additional new messages when assigning TALs to UEs. The ï¬rst solution takes into account only the priority between TALs. As for the second one, in addition to the priority between TALs, it takes into account the UEs activities (i.e., in terms of incoming communication frequency and mobility patterns) to improve further the network performance. The presentation of ETAM is estimated through investigation and imitations, and the achieved results validate its feasibility and ability in achieving its thesis goals, improving the network performance by minimizing the cost related with paging and TAU.