On the Low-Complexity, Hardware-Friendly Tridiagonal Matrix Inversion for Correlated Massive MIMO Systems

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.

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Enhanced Low-Complexity Matrix Inversion Method for Massive MIMO Systems

2019 16th International Symposium on Wireless Communication Systems (ISWCS) ◽

10.1109/iswcs.2019.8877131 ◽

2019 ◽

Cited By ~ 1

Author(s):

Yasser Naguib Ahmed

Keyword(s):

Massive Mimo ◽

Mimo Systems ◽

Low Complexity ◽

Matrix Inversion ◽

Inversion Method ◽

Matrix Inversion Method

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Iterative matrix inversion based low complexity detection in large/massive MIMO systems

2016 IEEE International Conference on Communications Workshops (ICC) ◽

10.1109/iccw.2016.7503871 ◽

2016 ◽

Cited By ~ 3

Author(s):

Vipul Gupta ◽

Abhay Kumar Sah ◽

A. K. Chaturvedi

Keyword(s):

Massive Mimo ◽

Mimo Systems ◽

Low Complexity ◽

Matrix Inversion

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An Efficient Precoding Algorithm for mmWave Massive MIMO Systems

Symmetry ◽

10.3390/sym11091099 ◽

2019 ◽

Vol 11 (9) ◽

pp. 1099 ◽

Cited By ~ 3

Author(s):

Imran Khan ◽

Shagufta Henna ◽

Nasreen Anjum ◽

Aduwati Sali ◽

Jonathan Rodrigues ◽

...

Keyword(s):

Massive Mimo ◽

Mimo Systems ◽

Matching Pursuit ◽

Mimo System ◽

Multiple Input Multiple Output ◽

Low Complexity ◽

Global Optimum ◽

Vital Role ◽

Matrix Inversion ◽

Inner Product

Symmetrical precoding and algorithms play a vital role in the field of wireless communications and cellular networks. This paper proposed a low-complexity hybrid precoding algorithm for mmWave massive multiple-input multiple-output (MIMO) systems. The traditional orthogonal matching pursuit (OMP) has a large complexity, as it requires matrix inversion and known candidate matrices. Therefore, we propose a bird swarm algorithm (BSA) based matrix-inversion bypass (MIB) OMP (BSAMIBOMP) algorithm which has the feature to quickly search the BSA global optimum value. It only directly finds the array response vector multiplied by the residual inner product, so it does not require the candidate’s matrices. Moreover, it deploys the Banachiewicz–Schur generalized inverse of the partitioned matrix to decompose the high-dimensional matrix into low-dimensional in order to avoid the need for a matrix inversion operation. The simulation results show that the proposed algorithm effectively improves the bit error rate (BER), spectral efficiency (SE), complexity, and energy efficiency of the mmWave massive MIMO system as compared with the existing OMP hybrid and SDRAltMin algorithm without any matrix inversion and known candidate matrix information requirement.

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