On the Common AOA Error in CKM-Based Integrated Sensing and Communications

In integrated sensing and communications (ISAC), the channel information can be acquired via the channel knowledge map (CKM). However, due to the lack of the precise knowledge of the user equipment's heading, angle of arrival (AOA) estimations of all paths share an identical error, which is defined as the common AOA error (CAE). In this letter, we prove that the CAE imposes rotational effects on the unitary matrices of the singular value decomposition (SVD) of the channel matrix, leading to non-orthogonality among data layers for the SVD-based precoding. Then we develop two algorithms utilizing the rotational effect to estimate and eliminate the CAE. The two algorithms are suitable for scenarios with low and high Rician K-factors, respectively. By applying the proposed algorithms, accurate wideband channel information can be attained based on narrowband reference signals. Simulation results show that the proposed algorithms obtain higher precoding performance than the baseline method.

Automated summary

In integrated sensing and communications (ISAC), channel information is obtained through the channel knowledge map (CKM). However, a common angle of arrival error (CAE) occurs due to the lack of precise user equipment heading knowledge, causing non-orthogonality among data layers for SVD-based precoding. This study develops two algorithms utilizing rotational effects to estimate and eliminate the CAE, suitable for low and high Rician K-factor scenarios. The proposed algorithms achieve higher precoding performance compared to the baseline method, providing accurate wideband channel information based on narrowband reference signals.