On a Strategy of Mobile Networks Synthesis

Effective design of mobile communication network includes optimization of two bounded together processes: the network base stations placement and the channel assignment. In real environments the well-known cellular concept fails due to not uniformly spaced traffic and not isotropic wave propagation. We find a rather universal method for synthesis of a close to optimal network structure. The proposed design approach is based on the idea of adaptive vector quantization for a map with random traffic. As a result, the service zone of the network becomes discrete and is being transformed to a map with not equal cells and approximately equal number of requests in every one. This fact allows to apply the simplest periodic reuse pattern. The algorithm finds a point with minimal average Euclidean distance from all its requests. This point defines optimal placement of the corresponding base station. The approach guarantees maximum coverage

Mobile network synthesis strategy

Introduction:Effective synthesis of а mobile communication network includes joint optimisation of two processes: placement of base stations and frequency assignment. In real environments, the well-known cellular concept fails due to some reasons, such as not homogeneous traffic and non-isotropic wave propagation in the service area.Purpose:Looking for the universal method of finding a network structure close to the optimal.Results:The proposed approach is based on the idea of adaptive vector quantization of the network service area. As a result, it is reduced to a 2D discrete map split into zones with approximately equal number of service requests. In each zone, the algorithm finds such coordinates of its base station that provide the shortest average distance to all subscribers. This method takes into account the shortage of the a priory information about the current traffic, ensures maximum coverage of the service area, and what is not less important, significantly simplifies the process of frequency assignment.