Low Complexity Hybrid PSO-BB Detection Algorithm for Massive MIMO System

In this paper, a novel iterative discrete estimation (IDE) algorithm, which is called the modified IDE (MIDE), is proposed to reduce the computational complexity in MIMO detection in uplink massive MIMO systems. MIDE is a revision of the alternating direction method of multipliers (ADMM)-based algorithm, in which a self-updating method is designed with the damping factor estimated and updated at each iteration based on the Euclidean distance between the iterative solutions of the IDE-based algorithm in order to accelerate the algorithm’s convergence. Compared to the existing ADMM-based detection algorithm, the overall computational complexity of the proposed MIDE algorithm is reduced from O N t 3 + O N r N t 2 to O N t 2 + O N r N t in terms of the number of complex-valued multiplications, where Ntand Nr are the number of users and the number of receiving antennas at the base station (BS), respectively. Simulation results show that the proposed MIDE algorithm performs better in terms of the bit error rate (BER) than some recently-proposed approximation algorithms in MIMO detection of uplink massive MIMO systems.

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A Novel Bitwise Factor Graph Belief Propagation Detection Algorithm for Massive MIMO System

Communications and Networking - Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ◽

10.1007/978-3-319-66625-9_44 ◽

2017 ◽

pp. 453-462

Author(s):

Lin Li ◽

Weixiao Meng

Keyword(s):

Massive Mimo ◽

Belief Propagation ◽

Mimo System ◽

Detection Algorithm ◽

Factor Graph

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Signal Detection Based on Parallel Group Detection Algorithm for High-Load Massive MIMO Systems

Wireless Communications and Mobile Computing ◽

10.1155/2019/5609740 ◽

2019 ◽

Vol 2019 ◽

pp. 1-12

Author(s):

Thanh-Binh Nguyen ◽

Minh-Tuan Le ◽

Vu-Duc Ngo

Keyword(s):

Massive Mimo ◽

Mimo Systems ◽

Mimo System ◽

Detection Algorithm ◽

High Load ◽

Signal Recovery ◽

Parallel Group ◽

Group Detection ◽

Practical Complexity ◽

Ber Performance

In this paper, a parallel group detection (PGD) algorithm is proposed in order to address the degradation in the bit error rate (BER) performance of linear detectors when they are used in high-load massive MIMO systems. The algorithm is constructed by converting the equivalent extended massive MIMO system into two subsystems, which can be simultaneously detected by the classical detection procedures. Then, using the PGD and the classical ZF as well as the QR-decomposition- (QRD-) based detectors, we proposed two new detectors, called ZF-based PGD (ZF-PGD) and QRD-based PGD (QRD-PGD). The PGD is further combined with the sorted longest basis (SLB) algorithm to make the signal recovery more accurate, thereby resulting in two new detectors, namely, the ZF-PGD-SLB and the QRD-PGD-SLB. Various complexity evaluations and simulations prove that the proposed detectors can significantly improve the BER performance compared to their classical linear and QRD counterparts with the practical complexity levels. Hence, our proposed detectors can be used as efficient means of estimating the transmitted signals in high-load massive MIMO systems.

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Compressed sensing based semidefinite relaxation detection algorithm for overloaded uplink multiuser massive MIMO system

2017 IEEE International Conference on Communications (ICC) ◽

10.1109/icc.2017.7997445 ◽

2017 ◽

Author(s):

Lin Li ◽

Weixiao Meng ◽

Cheng Li

Keyword(s):

Compressed Sensing ◽

Massive Mimo ◽

Mimo System ◽

Detection Algorithm ◽

Semidefinite Relaxation

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A signal detection algorithm based on chebyshev accelerated symmetrical successive over-relaxation iteration for massive MIMO system

2017 9th International Conference on Wireless Communications and Signal Processing (WCSP) ◽

10.1109/wcsp.2017.8171111 ◽

2017 ◽

Cited By ~ 1

Author(s):

Xiaoxiang Liu ◽

Jing Zhang

Keyword(s):

Signal Detection ◽

Massive Mimo ◽

Mimo System ◽

Detection Algorithm ◽

Successive Over Relaxation ◽

Relaxation Iteration

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

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b1351.0982s1119 ◽

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.

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