Open AccessA low‐computational‐cost alternating switches algorithm for real‐valued spatial covariance matrix reconstruction
Author(s) -
Liu Changzan,
Zhou Yan,
Dang Bo
Publication year - 2022
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/ell2.12521
Subject(s) - covariance matrix , computer science , algorithm , signal subspace , multiplication (music) , direction of arrival , power (physics) , covariance , matrix (chemical analysis) , antenna (radio) , set (abstract data type) , electronic engineering , mathematics , telecommunications , artificial intelligence , engineering , noise (video) , statistics , physics , materials science , combinatorics , quantum mechanics , composite material , image (mathematics) , programming language
The application of the emerging hybrid analog–digital architecture for future millimeter‐wave communications has attracted significant attention. Although this architecture can reduce the hardware cost and power consumption considerably, the high‐resolution direction of arrival (DOA) estimation in the architecture based on switches is still a challenge. As a solution, an alternating switches algorithm (ASA) is proposed in this paper. By appropriately adjusting the switch connected to each antenna, the real‐valued spatial covariance matrix (SCM) is reconstructed with low‐dimensional vector‐to‐vector multiplication. Subsequently, the DOA angle of each signal is estimated based on a split subspace extracted from the real‐valued SCM. Finally, a set of simulation experiments are performed to verify the performance of the proposed algorithm. The results indicate that the ASA can reconstruct the real‐valued SCM and realize high‐resolution DOA estimation with a substantially low computational cost.