Model-based MIMO Angle of Arrival Estimation for Next Generation Wireless Communication Systems

Multiple-Input Multiple-Output (MIMO) mode selection is essential for modern wireless communication systems. Usually channel state information (CSI) feedback is necessary for such operation. In fast-changing channels CSI becomes nearly infeasible due to limited coherence time and large volume of information required. To address this challenge, utilization of the channel spatial correlation matrix (SCM) is an effective solution. SCM is a function of mean angle of arrival (AoA) and variance of AoA. Our work estimates the mean AoA and its variance based on the power angular spectrum (PAS), in accordance with the 3rd Generation Partnership Project (3GPP) TR 38.901. Our approach employs the 3GPP clustered delay line (CDL) channel model, while using Orthogonal Frequency Division Multiplexing (OFDM) based channel estimation as in 4G LTE, 5G NR, and emerging 6G standards. We have achieved mean AoA and variance of AoA estimation accuracy on the order of 0.01, and our proposed AoA estimation method can be used across the microwave and mm Wave frequency range.