文摘
Wireless positioning systems have become very popular in recent years. One of the reasons is the fact that the use of a new paradigm named Internet of Things has been increasing in the scenario of wireless communications. Since a high demand for accurate positioning in wireless networks has become more intensive, especially for location-based services, the investigation of mobile positioning using radiolocalization techniques is an open research problem. Based on this context, we propose a fingerprinting approach using support vector regression to estimate the position of a mobile terminal in cellular networks. Simulation results indicate the proposed technique has a lower error distance prediction and is less sensitive to a Rayleigh distributed noise than the fingerprinting techniques based on COST-231 and ECC-33 propagation models.