Low-complexity implicit detection for massive MIMO using Neumann series
X Zhang, H Zeng, B Ji, G Zhang - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In massive MIMO systems, the high complexity of signal detection comes mainly from
computing a Gram matrix and its inversion. In this correspondence, we propose a low …
computing a Gram matrix and its inversion. In this correspondence, we propose a low …
Angular-domain massive MIMO detection: Algorithm, implementation, and design tradeoffs
In massive multiple-input multiple-output (MIMO) systems, the large size of channel state
information (CSI) matrix significantly increases the computational complexity of uplink …
information (CSI) matrix significantly increases the computational complexity of uplink …
Low-complexity symbol detection for massive MIMO uplink based on Jacobi method
In this paper, we propose a low-complexity symbol detection algorithm for massive multiple-
input multiple-output (MIMO) uplink. Grounded on the fact that a primary property of the …
input multiple-output (MIMO) uplink. Grounded on the fact that a primary property of the …
A comparative study of low-complexity MMSE signal detection for massive MIMO systems
S Zhao, B Shen, Q Hua - … on Internet and Information Systems (TIIS), 2018 - koreascience.kr
For uplink multi-user massive MIMO systems, conventional minimum mean square error
(MMSE) linear detection method achieves near-optimal performance when the number of …
(MMSE) linear detection method achieves near-optimal performance when the number of …
Efficient iterative massive MIMO detection using Chebyshev acceleration
Massive multiple-input multiple-output (MIMO) detection is one of the most important, yet
complex parts of the fifth generation (5G) baseband receiver. The linear minimum mean …
complex parts of the fifth generation (5G) baseband receiver. The linear minimum mean …
A low complexity soft-output data detection scheme based on Jacobi method for massive MIMO uplink transmission
In massive multiple-input multiple-output (MIMO) systems, linear minimum mean-square
error (MMSE) detection can achieve near-optimal performance. However, it suffers from high …
error (MMSE) detection can achieve near-optimal performance. However, it suffers from high …
Low‐complexity linear massive MIMO detection based on the improved BFGS method
L Li, J Hu - IET Communications, 2022 - Wiley Online Library
Linear minimum mean square error (MMSE) detection achieves a good trade‐off between
performance and complexity for massive multiple‐input multiple‐output (MIMO) systems. To …
performance and complexity for massive multiple‐input multiple‐output (MIMO) systems. To …
A low-complexity detection algorithm for uplink massive MIMO systems based on alternating minimization
In this letter, we propose an algorithm based on the alternating minimization technique to
solve the uplink massive multiple-input multiple-output (MIMO) detection problem. The …
solve the uplink massive multiple-input multiple-output (MIMO) detection problem. The …
A low complexity signal detection scheme based on improved Newton iteration for massive MIMO systems
F Jin, Q Liu, H Liu, P Wu - IEEE Communications Letters, 2019 - ieeexplore.ieee.org
Massive multiple-input multiple-output (MIMO) systems need to handle a large number of
matrix inversion operations during the signal detection process. Several methods have been …
matrix inversion operations during the signal detection process. Several methods have been …
A multistage linear receiver approach for MMSE detection in massive MIMO
A key property of a Large-scale MIMO, also known as" massive MIMO" is the orthogonality
among channels when the number of antennas at the base station becomes large. Utilizing …
among channels when the number of antennas at the base station becomes large. Utilizing …