Sparse array synthesis for the estimation of high-resolution arrival and departure angles in MU-MIMO

Abstract

This thesis deals with the estimation of arrival and departure angles with low complexity and high resolution. Estimating angular information helps location and tracking of users. Use of the angular information of the user, provides the base station the ability to transmit its signal directly to the corresponding user, increasing the security, thus lowering the interference and noise, the error rate gets decreased. In 5G propagation, a large path loss takes place due to the use of higher frequency, which requires compensation for lowering the error rate and increasing the data rate. This compensation can be achieved by sophisticated beamforming which requires knowledge of the propagation medium that involves the angular information. Thus, the signal from the transmitter can be steered towards the receiver in the desired direction. newlineArrival and departure angle estimation has been an active research area. Different methods are applied on the signal received for estimating angular information. Subspace-based techniques are most popular that use the subspaces found from the covariance of the received signal to estimate the angles. The number of elements and the coherent nature in the transmitter and receiver play an important role in resolving the estimated angle. With increase in the number of array elements, the angular resolution increases. However, the computational complexity also gets increased. Depending on the array geometry design azimuth, elevation or both the angles can be estimated. The leakage of spatial power that occurs between the signal and noise subspaces increases when the received signal is coherent. This causes false detection and can be traded off by the choice of the number of array elements. newline