臺灣博碩士論文加值系統

To accommodate the large PCS user populations expected in the future, designing of an efficiently algorithm in managing the location information of mobile users is necessary. Location information of mobile users was stored in the database of HLR. Mobile users have to inform HLR of its current location from time to time to make sure the communication network can have the knowledge of mobile user’s current location. Too many update times of HLR will cause an inefficient performance of communication network. How to reduce the update times of informing HLR has become a specialized domain that the scholars are interesting in. Some paper proposed by using prediction of mobile user’s location to reduce the update times of HLR. But it spends too much time to collect mobile user’s moving patterns and the analysis of the data is complicated. We wish to propose an efficient way to reduce the update times of HLR improving the performance of communication network.
The tree structure was adopted because of its structure which parent and son can represent a relationship of the location areas that mobile users traveled from the past to the present time. We designed the algorithm that built the tree when mobile user traveled around the location areas. The tree represents the user profile of its moving patterns can reduce the update times of HLR. The applicability of the scheme and the performance of the HLR are demonstrated through a number of experiments for a range of mobile users and for a variety of mobile user’s moving behavior

1. INTRODUCTION 7
1.1 THE HISTORY OF MOBILE PHONE 7
1.2 OVERVIEW OF MOBILE SYSTEMS 8
1.3 INTRODUCTION TO LOCATION MANAGEMENT IN MOBILE SYSTEMS 10
1.4 THE STANDARDS OF LOCATION MANAGEMENT 11
1.5 MOTIVATION 12
1.6 OBJECTIVES AND CONTRIBUTIONS 13
2. LITERATURES REVIEW 14
2.1 OVERVIEW OF IS-41 14
2.1.1 Location Update and Call Setup 15
2.1.2 Handoff 19
2.2 REVIEW OF LOCATION UPDATE 20
2.2.1 Classical Strategy 20
2.2.2 Selective Location Area Update 22
2.2.3 Profile-based 22
2.2.4 Movement-based 23
2.2.5 Time-based 24
2.2.6 Distance-based 24
2.2.7 Predictive Distance-Based 25
3. A NEW SYSTEM ARCHITECTURE WE PROPOSED 25
3.1 NETWORK TOPOLOGY 26
3.2 USER MOBILITY OF PROFILE-BASED STRATEGY WITH LOOKUP TREE 27
3.3 PRELIMINARIES 28
3.3.1 Lookup Tree 28
3.3.2 Location Update Algorithm 29
4. ANALYSIS AND COMPARISION 34
4.1 SIMULATION MODEL 34
4.2 SIMULATION RESULT 36
5. CONCLUSION 43
6. REFERENCE 44

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