Wireless LAN planning using the multi-resolution "FDPF" propagation model

Wireless LAN (WLAN) technologies such as WiFi or Bluetooth have become popular in many countries. The need for an efficient design of them becomes a central problem. Automatic transmitter placement provides cost savings when compared to the traditional human process of site planning. The performance of a LAN is strongly influenced by the access point's characteristics. That's why the amount of them, their location and their emission power have to be determined with care during the planning stage of the network. The planning problem can be exposed in different ways according to the optimisation goals that have been chosen. The traditional approach is to compute a coverage map that satisfies a simple constraint on the signal level based on a minimum threshold. Some more elaborated models introduce constraints of quality of service (as throughput or interference level) on the receiver locations. The evaluation of a solution (an access point configuration) relies on a propagation simulation that computes a coverage map. This simulation is often an expensive computational operation. The goal of the optimisation algorithm is to determine a solution that satisfies to the coverage constraints with a minimum number of propagation simulations. We propose a deterministic algorithm that relies on the multi-resolution Fourier domain parflow (FDPF) propagation model proposed by Gorce and Ubeda (2001). The originality of this algorithm is to exploit the multiresolution specificity of the FDPF method in order to reduce the computation cost of propagation simulations. Its aim is to find out an access point distribution that provides homogeneous coverage. We work on a two dimensional building floor representation and the variables are the x-axis and y-axis coordinates of the transmitters (access points). We consider that the number of sources to plan and their emission power is fixed. In the next part of this paper, a short overview of the planning problem is provided. In the third part, we define the problem we work on and the characteristics of the FDPF propagation model. In the fourth part, details about our deterministic algorithm are provided and in the fifth part, results are given. We end this paper by a short discussion and enlargement on our work.