Location Area Planning And Optimization Algorithms In Wireless Communication Networks

Mobility management is crucial for the mobile communication network, the system must always identify the mobile terminal's location to meet its mobility. From which location area(LA) is developed. The whole service area is partitioned into several location areas and a location area contains many different cells. When the mobile terminal crosses a location area boundary, that's to say, it enter a new location area, it will report the system and register the new location to start a location update (LU), and it should also periodically perform LUs to inform the system about its newest location in standby state. When a call arrives, the network will search the target MS in all the cells under the same LA to set up communication, which is called Paging. So location and Paging process are based on LA. Whether location update or Paging consumes the network resources, and they both relate to the size of an LA. Too large the size of an LA will cause higher Paging cost, since there are more cells to be paged, but the registration cost will be lower. Conversely, it will cause more frequent location updates and lower Paging cost. Therefore, registration and Paging is an antinomy, and the number of cells in an LA is important. But in actual application, we expect both minimum. How to find the reasonable location area partitioning and make the optimal mobile location management cost in wireless system becomes the key to our study.This paper proposes different location area planning(LAP) with corresponding models for different network problems, using simulated annealing algorithm and genetic algorithm. First, we propose an algorithm based on simulated annealing (SA), to regulate the number of location areas for LAP, using an adaptive strategy and with designing effective simulated annealing operator, overcome the local optimum, avoid invalid search of the usual algorithms and improve the searching efficiency of algorithm. Then we minimizes the location management cost in three different network conditions, the experimental results show the effectiveness of the algorithm. This article attempts to create location area optimization model based on road statistics and handover statistics correlation realistically. The usual mathematical models of location area planning just always consider the cells'data model in theory, while ignoring the influence of the actual geographical environment factors, such as mountains, rivers, roads and so on. The LAP model considering actual geographical environment factors has more authenticity, compared with description of cells correlation with single mobility date. The paper establishes mobile management model through the classified statistics of roads, and the objective is to minimize the LUs under the Paging capacity constraints, aiming to find a balance between registration and Paging and achieve the optimum location management costs for the given system. Location area planning is usually regarded as a complex optimization problem, and the solution space of the algorithm is very huge, in order to effectively compress the search space, the paper adds the constraint that the adjacent but not connected cells belong to different LAs, proposes evolutionary algorithm (EA) and takes new coding method for its solution. Evolutionary algorithm has the group search advantage to solve the LAP and for effective initial solution and lower location update cost, the fuzzy clustering method is used to initialize the LAs combined with the connectivity between cells. Finally, computer simulation based on practical road distribution shows the effectiveness of the proposed algorithm.