Adaptive NLOS Mitigation Location Algorithm in Wireless Cellular Network

In a cellular network, a location scenario is considered in this paper, which the home base station (BS) measures the range and angle while neighboring BSs measure the ranges. Based on the range and angle measurements, two adaptive non-line-of-sight (NLOS) identification and mitigation location algorithms with low complexity are proposed. The main idea of our proposed algorithms is to search the optimal subset of range and angle measurements by utilizing the hybrid lines of position algorithm and comparing the normalized residual error to perform the NLOS identification and location. Compared with the existing algorithms, the proposed algorithms have three advantages: one is different to the existing algorithms that require at least three BSs, the proposed algorithms can be suitable for two BSs scenario. Second is the low complexity of our proposed algorithms compared with the existing algorithms. The last is simulation results show that the proposed algorithms outperform the existing algorithms in bad urban and urban environments.