Improvement of the robustness and performance of time of arrival algorithms

Abstract: 5G offers several new improvements compared to its predecessors, such as higher speeds, lower latency and larger capacity. In order to ensure this, time of arrival algorithms are used in the Radio Access Networks for several purposes. Some of them are 3D positioning of User Equipment and synchronization. A big challenge for Time of Arrival algorithms are environments with multi-path propagation, especially when they use two-way measurements, as the algorithm may pick different propagation paths depending on the direction. This will result in a measurement error caused by asymmetry which leads to a degraded algorithm performance. This thesis investigates how time of arrival algorithms can be improved when facing asymmetry. Two different improvements are tested, the first is how using the same beamforming weights in the transmitter and the receiver impacts the assumption of channel reciprocity and the other is how the selection of the crosscorrelation peak can be altered. The simulations were performed using different Tapped Delay Line channel models in order to mimic a multipath propagation environment. The results show that the suggested peak search criterion could reduce measurement errors originating from asymmetry but also that the simulator was not equipped to test and verify that using the same beamforming weights would reduce asymmetry errors.