Abstract
Sparse channel estimation is investigated for millimeter wave massive MIMO systems, where a base station equipped with a uniform planar array serves several single-antenna users. At first, the 2-D multiuser channel estimation is formulated as several sparse recovery problems. Then a regularized multipath matching pursuit (RMMP) algorithm is proposed for sparse channel estimation. Compared to the existing multipath matching pursuit (MMP) algorithm, a regularization step is introduced in RMMP to screen the candidate paths, which can reduce the computational complexity as well as the storage overhead. Simulation results show that the proposed RMMP algorithm outperforms the existing orthogonal matching pursuit and orthogonal least squares algorithms. In particular, RMMP has the same sparse channel estimation performance as MMP while the computational complexity of the former is much lower than the latter.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
