The challenge of supporting rapidly growing numbers of
mobile users, while constrained by limited radio spectrum is
being faced by cellular network operators worldwide. The standard
technique for cellular networks is to decrease radio cell size, thereby maintaining
a supportable subscriber density. However, smaller size result in increased
signaling for location management procedures, which reduces the bandwidth
available for user traffic.
Several location management schemes have been proposed to improve the performance of such networks, but a fair assessment and comparison of their performance is difficult without a realistic mobility model, since the performance of location management schemes depends considerably on subscriber mobility patterns. Some of the methods used in the literature are reviewed and commented upon. The strategies are then classified in several categories on the basis of their functionality. Finally, some proposals are selected that concentrate on the location updating and paging overhead.
To analyze the performance of the selected proposals, two mobility models were used in this thesis. The first was a realistic, measurement-based, place and time-dependent individual mobility model to simulate the mobility behavior of actual people. The second was a random mobility model based on simplified assumption, such as a uniform distribution of the direction of travel for each mobile subscriber, as being used in a number of proposed schemes. From the results it is clear that the mobility model has a significant impact and the results described in various schemes using a random mobility model may not reflect the relative performance when deploying schemes in actual systems.