Abstract
Channel estimation is crucial in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, especially with a few training sequences. To solve the problem of uplink channel estimation in mmWave massive MIMO systems, a PARAFAC-based algorithm is proposed for joint estimation of multiuser channels. The orthogonal frequency divisional multiplexing (OFDM) technique is exploited to combat the frequency selective fading channels. In this paper, the received signal at the base station (BS) is formulated as a third-order parallel factor (PARAFAC) tensor, and then a low-complexity algorithm is designed for fast estimation of the factor matrices related to channel parameters, thus leading to joint estimation of multiuser channel parameters via one-dimensional search. Moreover, the Cramér–Rao Bound (CRB) results for multiuser channel parameters are derived for evaluation. Theorical analysis and numerical results reveal that the algorithm performs well with a few training sequences. Compared with existing algorithms, the proposed algorithm has clear advantages both in estimation accuracy and computational complexity.
Funder
the National Key Research and Development Program of China under Grant
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Cited by
1 articles.
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