此文章中提出利用人的移動性為基礎的理論，來降低無線通訊上的位置更新。我們知道在系統中記錄了一些用戶的行為，例如用戶撥通電話後的行為及撥通電話前位置更新的行為。其中位置更新的行為是以交換機做為記錄單位的，所以無法提供每個基地站的用戶移動行為。故本文章所提出的方法是將撥通電話後以基地站做為記錄的行為，溶入以交換機為記錄的位置更新行為，利用數理統計得到每個基地站的用戶移動行為。而撥通電話後的行為，本文章取用了發話、受話及交遞的行為。從這些行為記錄中，可以預測用戶的數量及方向性的移動量，而且這些都以基地站為單位記錄，所以就可以得到基地站撥通電話後的移動量。接著將這些訊息套進邊界上的基地站，再與交換機為單位的位置更新之數值做數理統計的分析，如此一來就可以得到發話、受話、及交遞對位置更新的貢獻係數，再將這些係數套入其它的基地站，那麼全網每個基地站的用戶移動行為就可以預測出來。接著利用此用戶移動行為的資訊找出全網中移動量較少的基地站，最後將這些基地站設為邊界，如此一來，因移動量比較少，所以位置更新的次數也因此減少。

The proposed approach is to reduce the location update (LU) attempts in wireless networks by the prediction of idle movement of people. As we know there are active movement and idle movement of people recorded in the hardware of wireless networks. Active movement is recorded by cell level, but idle movement is recorded by Mobile Switching Center (MSC)/ Visitor Location Register (VLR) level. Thus there is no relationship between them. The proposed approach creates the relationship between them to generate the formula of idle movement of each cell. It uses the Mobile Originating Call (MOC), Mobile Terminated Call (MTC), and Handover (HO) form the active movement. Meanwhile it takes the LU attempts from idle movement into account. With the active movement information, we can get the directional idle movement of people of each cell on its corresponding direction. From the above information, we can get the contribution to the LU attempt for the MOCs, MTCs, and HO respectively. By the contribution, we can get the coefficients of the MOCs, MTCs, and HO. Applying the coefficients to each cell in the wireless networks, and we can get the idle movement of each cell. Since we get the idle movement of people of each cell, we can use it to find out the cells with relatively low idle movement. The best borders are set on those cells because of the relatively low idle movement. Thus the LU attempts are reduced to the minimum value. This can bring the benefits to hardware of wireless networks and free up more resource to work on the necessary services.

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