Transcript Experiment
國立雲林科技大學 National Yunlin University of Science and Technology Analysis of Soft Handover Measurements in 3G Network Advisor : Dr. Hsu Student :Jing Wei Lin 2006.8.ACM.MSWiM November 22, 2006 1 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Outline Motivation Objective Introduction Method Experiments Conclusions 2 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Motivation Mobility management is a great challenge in current and future radio access networks. 3 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Objective We propose a method to find groups of similar mobile cell pairs in the sense of soft handover measurements(SHO). 4 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Introduction-SHO SHO-軟式訊號換手，當使用者在做訊號換手動作時，系統連線是先建立新的 連線後才將原來的連線中斷，使訊號進行轉換時不易被使用者察覺。 In 3G system, Mobile Station (MS) is moving towards another Base Station (BS), the MS should have a connection at least on one BS all the time by SHO. When MS is in SHO, several BSs listen the same uplink channel, but all BSs have their own downlink channel. There is a tradeoff between better QoS in mobility management and consumption of resources. Cell 5 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Method Finding groups of similarly behaving cell pairs in SHO situations. 1. 2. 3. Data vectors are at first used to train a Self-Organizing Map. The codebook vectors are further clustered using hierarchical clustering method. The number of clusters can be selected manually. (Here use DBI to do) 6 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Variable selection 7 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Preprocessing The method was selected on basis of histograms Logarithms of some of the variables were taken, but finally only scaled EcnoDiffNum was preprocessed with logarithmic function. Sample vectors with 15 or more missing values in 20 variables are canceled. 8 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiment 9 Intelligent Database Systems Lab Experiment N.Y.U.S.T. I. M. 10 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiment 11 Intelligent Database Systems Lab lower higher N.Y.U.S.T. I. M. 9 5 lower higher 12 Intelligent Database Systems Lab N.Y.U.S.T. I. M. 13 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Conclusions The benefits of the proposed method are the decrease in computational complexity due to used two-phase clustering algorithm and the visualization capability of the method. The histograms are used both when preprocessing methods are decided and when an interpretation for the found clusters are looked for. 14 Intelligent Database Systems Lab