5G NR downlink AOD-based localization

Abstract

Large antenna arrays, millimeter-wave signals, large bandwidth and dense deployment are the characteristics of 5G networks. These technologies not only enable high-data rate communications but also have the potential superiority of accurate positioning. This dissertation aims to study the millimeter-wave positioning properties and existing angle of departure (AoD) based localization algorithms for 5G communication networks and integrate existing methods and add new contents to realize three-dimensional non-line-of-sight (NLOS) based localization with the assumption that received NLOS path signals only reflect once.

To achieve the objective, the SAGE algorithm is applied to estimate channel parameters due to its faster convergence and lower complexity. The position of a mobile station (MS) is recovered using the estimated channel parameters through the geometrical relationship between base station (BS) and MS in three-dimensional scenario. The method can achieve sub-meter localization error with probability of 0.9 in NLOS scenario.