Linear Array Motion-Based Time-Varying Channel Estimation for Three-Dimensional Millimeter-Wave Systems

Using linear arrays for compressive sensing-based (CS) three-dimensional (3D) millimeter-wave (mmWave) channel estimation presents significant challenges due to the dimensional limitations of the array aperture, which prevents direct sparse 3D channel representation. Fortunately, the emergence of array motion provides a chance for that. In this paper, by exploring the motion of linear arrays in time-varying channels and identifying their similarities to planar arrays, we propose a method for sparse representation of 3D channels based on linear arrays. Utilizing the sparsity, a two-step sparse channel recovery algorithm is presented. Initially, the on-grid and off-grid approaches are employed to efficiently and accurately obtain the angles of arrival (AoAs). Subsequently, path gains are estimated based on these AoAs. Simulation results show that the proposed method can effectively estimate 3D time-varying mmWave channels using a linear array with only a small number of pilots.