Planning system for indoor wireless network

A novel wireless LAN prediction tool using the genetic algorithm and neural network has been proposed. We establish a site survey tool system to predict the received signal strength index (RSSI) in an indoor environment. The system includes six items. (1) The fading function: it corrects the functional characteristics of the RSSI for different types of wireless LAN cards in free space. (2) The setting of the attributes of obstacles in the indoor environment: the idea of a “single attribute of local area” is proposed. If there are the same obstacles in one area, we set the area as one attribute. (3) The genetic algorithm: where we use reproduction, crossover and mutation to obtain the propagation loss through the different obstacles (Li). (4) The neural network: we use neural network concept to correct the prediction error arising from the multipath effect in the indoor environment. (5) The auxiliary judgment for the sampling points: the method is helpful to users in establishing the best sampling points. (6) The calibration of prediction results: we use calibration to correct the prediction error arisen from Li