Channel Reconstruction-Aided MUSIC Algorithms for Joint AoA&AoD Estimation in MIMO Systems

This letter discusses the issue of joint angle-of-arrival (AoA) and angle-of-departure (AoD) estimation for multi-input multi-output (MIMO) arrays, so as to conceive a novel one-snapshot multiple signal classification (MUSIC)-derived algorithm based on channel reconstruction therein. Compared to conventional two-dimensional MUSIC (2D-MUSIC), not only does the proposed algorithm avoid the problem of matrix rank deficit, but it also brings a prominent complexity reduction yet achieving satisfactory accuracy. Simulation results verify the utility and advancement of our algorithm, especially in the scheme with high real-time requirements.

Automated summary

This letter discusses a novel one-snapshot multiple signal classification (MUSIC)-derived algorithm based on channel reconstruction for joint angle-of-arrival (AoA) and angle-of-departure (AoD) estimation in multi-input multi-output (MIMO) arrays. Compared to conventional two-dimensional MUSIC (2D-MUSIC), the proposed algorithm not only avoids the problem of matrix rank deficit but also achieves significant complexity reduction while maintaining satisfactory accuracy. Simulation results confirm the utility and advancement of the algorithm, particularly in scenarios with high real-time requirements.