NLOS Identification and Mitigation for Geolocation Using Least-Squares Support Vector Machines

This paper examines the problem of non-line-of- sight (NLOS) identification and mitigation for geolocation signals in mobile networks. A ray tracing tool is used to simulate a mobile radio network with fixed base stations and thousands of mobile stations. The channel data between these mobile stations and base stations is used to extract parameters or features that are used for classification. Techniques for NLOS identification using a Least-Squares Support Vector Machine (LSSVM), are devised, producing greater than 98 percent accuracy for the proposed location specific approach, and 87 percent for the location independent approach. Respective LSSVM NLOS mitigation techniques are also proposed and evaluated. A usage context for the location specific approach is suggested, where the approach can help in addressing some of the challenges of next-generation wireless systems like massive MIMO.