Adaptive Conjugate Gradient DFEs for Wideband MIMO Systems Using Galerkin Projections

2007 ◽  
Author(s):  
Vassilis Kekatos ◽  
Aris S. Lalos ◽  
Kostas Berberidis
Keyword(s):  
Conjugate Gradient ◽  
Mimo Systems ◽  
Galerkin Projections

scholarly journals A Low Complexity Precoding Algorithm Based on Parallel Conjugate Gradient for Massive MIMO Systems

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 54010-54017 ◽  
Author(s):  
Geng Chen ◽  
Qingtian Zeng ◽  
Xiaomei Xue ◽  
ZhengQuan Li
Keyword(s):  
Conjugate Gradient ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Low Complexity

Energy- and Area-Efficient Recursive-Conjugate-Gradient-Based MMSE Detector for Massive MIMO Systems

2020 ◽  
Vol 68 ◽  
pp. 573-588 ◽  
Author(s):  
Leibo Liu ◽  
Guiqiang Peng ◽  
Pan Wang ◽  
Sheng Zhou ◽  
Qiushi Wei ◽  
...  
Keyword(s):  
Conjugate Gradient ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Gradient Based ◽  
Mmse Detector ◽  
Area Efficient

scholarly journals Modified Conjugate Gradient Algorithms for Gram Matrix Inversion of Massive MIMO Downlink Linear Precoding

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2834-2840
Keyword(s):  
Conjugate Gradient ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Low Complexity ◽  
Matrix Inversion ◽  
Gram Matrix ◽  
Linear Precoding ◽  
Inversion Algorithm ◽  
The Matrix

This paper deals with various low complexity algorithms for higher order matrix inversion involved in massive MIMO system precoder design. The performance of massive MIMO systems is optimized by the process of precoding which is divided into linear and nonlinear. Nonlinear precoding techniques are most complex precoding techniques irrespective of its performance. Hence, linear precoding is generally preferred in which the complexity is mainly contributed by matrix inversion algorithm. To solve this issue, Krylov subspace algorithm such as Conjugate Gradient (CG) was considered to be the best choice of replacement for exact matrix inversions. But CG enforces a condition that the matrix needs to be Symmetric Positive Definite (SPD). If the matrix to be inverted is asymmetric then CG fails to converge. Hence in this paper, a novel approach for the low complexity inversion of asymmetric matrices is proposed by applying two different versions of CG algorithms- Conjugate Gradient Squared (CGS) and Bi-conjugate Gradient (Bi-CG). The convergence behavior and BER performance of these two algorithms are compared with the existing CG algorithm. The results show that these two algorithms outperform CG in terms of convergence speed and relative residue.

Adaptive Conjugate Gradient DFEs for Wideband MIMO Systems

2009 ◽  
Vol 57 (6) ◽  
pp. 2406-2412 ◽  
Author(s):  
A.S. Lalos ◽  
V. Kekatos ◽  
K. Berberidis
Keyword(s):  
Conjugate Gradient ◽  
Mimo Systems
Sign in / Sign up

Export Citation Format

Share Document