Results 261 to 270 of about 4,382,513 (303)

Efficient SIC-MMSE Detection Using Neumann Series Expansion

2018 International Conference on Information and Communication Technology Convergence (ICTC), 2018
In this paper, we propose a complexity reduced soft interference cancellation minimum mean squared error (SIC-MMSE) detection scheme for coded massive MIMO systems.
Zhilin Fu, Satya Chan, Sooyoung Kim
semanticscholar   +2 more sources

An Efficient Approximate Expectation Propagation Detector With Block-Diagonal Neumann-Series

IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 2023
Expectation propagation (EP) achieves near-optimal performance for large-scale multiple-input multiple-output (L-MIMO) detection, however, at the expense of unaffordable matrix inversions.
Huizheng Wang, Bingyang Cheng, X. Tan, Xiaohu You, Chuan Zhang   +4 more
semanticscholar   +1 more source

Low-Complexity Implicit Detection for Massive MIMO Using Neumann Series

IEEE Transactions on Vehicular Technology, 2022
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-complexity MIMO detection method based on the Neumann series (NS), which does not ...
Xiaohui Zhang, Huacheng Zeng, Baofeng Ji, Gaoyuan Zhang   +3 more
semanticscholar   +1 more source

Approximate Expectation Propagation Massive MIMO Detector With Weighted Neumann-Series

IEEE Transactions on Circuits and Systems - II - Express Briefs, 2021
Expectation propagation (EP) achieves near-optimal performance for massive multiple-input multiple-output (MIMO) detection, however, at the cost of multiple expensive matrix inversions.
X. Tan, Huijun Han, Muhao Li, Kai Sun, Yongming Huang, X. You, Chuan Zhang   +6 more
semanticscholar   +1 more source

Fast Converging Weighted Neumann Series Precoding for Massive MIMO Systems

IEEE Wireless Communications Letters, 2018
B. Nagy, M. Elsabrouty, S. Elramly
semanticscholar   +3 more sources

A Matrix Inversion Free Method for Computing Katz Centrality of Taipei Metro System Using Neumann Series

International Conference on Consumer Electronics-Taiwan, 2021
In this paper, the Katz centrality and Neumann series are used to identify the station importance of Taipei metro system. First, node importance of complex network is computed by the Katz centrality whose solution needs to solve the matrix inversion (MI).
C. Tseng, Su-Ling Lee
semanticscholar   +1 more source

Efficient Expectation Propagation Massive MIMO Detector With Neumann-Series Approximation

IEEE Transactions on Circuits and Systems - II - Express Briefs, 2020
Expectation propagation (EP) attains near-optimal performance for massive multiple-input multiple-output (MIMO) detection. However, the inevitable matrix inversions and exponentiations at each EP iteration bring great challenges to realistic hardware ...
X. Tan, Weihong Xu, Yaping Zhang, Zaichen Zhang, X. You, Chuan Zhang   +5 more
semanticscholar   +1 more source

A Temperature Data Denoising Method Using Laplacian Matrix and Neumann Series

International Symposium on Computer, Consumer and Control, 2020
In this paper, a temperature data denoising method using Laplacian matrix and Neumann series is presented. First, the denoising problem is formulated as an optimization problem whose solution needs to solve the matrix inversion.
C. Tseng, Su-Ling Lee
semanticscholar   +1 more source

Neumann series and lattice sums

Journal of Mathematical Physics, 2005
We consider sums over the square lattice which depend only on radial distance, and provide formulas which enable sums of functions with Neumann series to be reexpressed as combinations of hypergeometric series. We illustrate the procedure using trigonometric sums previously studied by Borwein and Borwein, sums combining logarithms, Bessel functions Jλ,
McPhedran, R. C., Nicorovici, N. A., Botten, L. C.   +2 more
openaire   +1 more source

NSNO: Neumann Series Neural Operator for Solving Helmholtz Equations in Inhomogeneous Medium

Journal of Systems Science and Complexity
In this paper, the authors propose Neumann series neural operator (NSNO) to learn the solution operator of Helmholtz equation from inhomogeneity coefficients and source terms to solutions.
Fukai Chen, Ziyang Liu, Guochang Lin, Junqing Chen, Zuoqiang Shi   +4 more
semanticscholar   +1 more source