Uplink positioning architecture and algorithm for femtocell networks

This paper proposed an uplink positioning algorithm of adaptive extended Kalman filter (AEKF) aided with time difference of arrival (TDOA) measurements between the pairs of four eNBs for estimating the position of moving user equipment (MUE). The concept of cloud-assisted femtocell network to determine the optimally distributed four eNode Bs (eNBs) is provided in order to guarantee the accuracy of UE position estimations. In addition, t he location accuracy of the AEKF using 4-eNB TDOA is compared with hybrid TDOA and direction of arrival (DOA).