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Angular-Domain Channel Estimation for One-Bit Massive MIMO Systems: Performance Bounds and Algorithms

delete2020-03-01
delete16
PRE
AI
F
Fangqing Liu
H
Heng Zhu
C
Changheng Li
李建 封面图
李建 (Jian Li) *
P
Pu Wang
P
Philip V. Orlik
DOI:10.1109/TVT.2020.2966003delete
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摘要

摘要

En 中文
We consider angular-domain channel estimation in massive MIMO systems using one-bit analog-to-digital converters (ADCs) with various thresholding schemes at the receivers. We first derive the performance bounds for estimating angular-domain channel parameters, including the angles-of-arrival (AoA), angles-of-departure (AoD) and the associated path gains. Specifically, we derive 1) the deterministic Cramer-Rao bound (CRB) when all of the angular-domain channel parameters are treated as deterministic unknowns; 2) the hybrid CRB when some parameters have known prior probability density functions (pdfs) while the rest are assumed to be deterministic unknowns; 3) the Bayesian CRB when all of them have known prior pdfs. We also consider using the maximum likelihood (ML) method for channel estimation and a computationally efficient relaxation based cyclic algorithm (referred to as 1bRELAX) to obtain the ML estimates. When the prior information is available, the maximum a posteriori (MAP) and joint ML-MAP (JML-MAP) estimators are derived. We also use the one-bit Bayesian information criterion (1bBIC) to determine the number of scattering paths. Numerical examples are provided to verify the derived performance bounds with different thresholding schemes and demonstrate the performance of the proposed channel estimation algorithms.
Keyword:
Massive MIMO
angular-domain channel estimation
one-bit quantization
antenna-varying thresholds
time-varying thresholds
deterministic CRB
hybrid CRB
Bayesian CRB
ML
JML-MAP
MAP
1bRELAX
1bBIC
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期刊

IEEE Transactions on Vehicular Technology 封面图
IEEE Transactions on Vehicular Technology
IF:
7.1
论文数:
1.8W
被引数:
6.6W

机构

State University System of Florida 封面图
State University System of Florida
学者数:
12.8W
论文数: 10.9W
被引数: 130
C
chinese academy of sciences
学者数:
56.7W
论文数: 45.0W
被引数: 704
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