A Novel Iterative Positioning Method Based on Difference RSS Model With 5G Field Experiments

In the 5th Generation (5G) positioning, the accurate values of environmental parameters such as Pathloss exponent (PLE) and transmit power are difficult to obtain accurately. Methods based on the difference of received signal strength (DRSS) can be utilized to solve the problems. An estimation method to obtain the distance ratio is given, and a distance ratio positioning model is proposed. The initial positioning results are calculated with linear least squares (LLS) algorithm. A Levenberg-Marquardt (LM) based maximum a posteriori (MAP) algorithm is proposed to obtain the final result by performing a series of iterations. We have completed the 5G field data collection in urban environments and preprocessed the raw data in 5G field experiments. We also propose a judgment method for 5G positioning based on horizontal dilution of precision (HDOP). Compared to the state-of-art DRSS-based algorithms, the proposed method has the best positioning accuracy and achieves a positioning error of 43.8 meters for 80% of samples with six base stations.