Optimized indoor wireless propagation model in WiFi-RoF network architecture for RSS-based localization in the Internet of Things

This paper innovatively proposes an indoor wireless propagation model in WiFi radio-over-fiber network architecture for received signal strength (RSS) based localization in the Internet of Things. The proposed model adds attenuation terms of obstacles in each sub-space by dividing the room into several sub-spaces according to the obstacles´ distribution. The influence of obstacles in sub-space on the indoor wireless propagation model is theoretically analyzed and the optimized model has been experimentally demonstrated to give exactly prediction of real-world RSS values in 62.5% of the testing points, which shows that the proposed model outperforms the original one.