scholarly journals A Review to Massive MIMO Detection Algorithms: Theory and Implementation

2020 ◽  
Author(s):  
Bastien Trotobas ◽  
Amor Nafkha ◽  
Yves Louët
Keyword(s):  
Massive Mimo ◽  
Mimo Detection ◽  
Detection Algorithms

Performance analysis of various massive MIMO detection algorithms in 5G Wireless technologies

2019 ◽  
Vol 10 ◽  
Author(s):  
Shihab Jimaa ◽  
Jawahir Al-Ali
Keyword(s):  
Massive Mimo ◽  
Spectrum Efficiency ◽  
System Capacity ◽  
Network Coverage ◽  
Mimo Detection ◽  
Infinity Norm ◽  
Detection Algorithms ◽  
Alternating Direction ◽  
5G Systems ◽  
Efficient Power

Background: The 5G will lead to a great transformation in the mobile telecommunications sector. Objective: The huge challenges being faced by wireless communications such as the increased number of users have given a chance for 5G systems to be developed and considered as an alternative solution. The 5G technology will provide a higher data rate, reduced latency, more efficient power than the previous generations, higher system capacity, and more connected devices. Method: It will offer new different technologies and enhanced versions of the existing ones, as well as new features. 5G systems are going to use massive MIMO (mMIMO), which is a promising technology in the development of these systems. Furthermore, mMIMO will increase the wireless spectrum efficiency and improve the network coverage. Result: In this paper we present a brief survey on 5G and its technologies, discuss the mMIMO technology with its features and advantages, review the mMIMO capacity and energy efficiency and also presents the recent beamforming techniques. Conclusion: Finally, simulation of adopting different mMIMO detection algorithms are presented, which shows the alternating direction method of multipliers (ADMM)-based infinity-norm (ADMIN) detector has the best performance.

scholarly journals Multisegment Mapping Network for Massive MIMO Detection

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yongzhi Yu ◽  
Jianming Wang ◽  
Limin Guo
Keyword(s):  
Deep Learning ◽  
Computational Complexity ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Activation Function ◽  
Symbol Error Rate ◽  
Mimo Detection ◽  
Residual Structure ◽  
Detection Algorithms ◽  
Input Multiple Output

The massive multiple-input multiple-output (MIMO) technology is one of the core technologies of 5G, which can significantly improve spectral efficiency. Because of the large number of massive MIMO antennas, the computational complexity of detection has increased significantly, which poses a significant challenge to traditional detection algorithms. However, the use of deep learning for massive MIMO detection can achieve a high degree of computational parallelism, and deep learning constitutes an important technical approach for solving the signal detection problem. This paper proposes a deep neural network for massive MIMO detection, named Multisegment Mapping Network (MsNet). MsNet is obtained by optimizing the prior detection networks that are termed as DetNet and ScNet. MsNet further simplifies the sparse connection structure and reduces network complexity, which also changes the coefficients of the residual structure in the network into trainable variables. In addition, this paper designs an activation function to improve the performance of massive MIMO detection in high-order modulation scenarios. The simulation results show that MsNet has better symbol error rate (SER) performance and both computational complexity and the number of training parameters are significantly reduced.

One-Bit Quantized Massive MIMO Detection Based on Variational Approximate Message Passing

2018 ◽  
Vol 66 (9) ◽  
pp. 2358-2373 ◽  
Author(s):  
Zhaoyang Zhang ◽  
Xiao Cai ◽  
Chunguang Li ◽  
Caijun Zhong ◽  
Huaiyu Dai
Keyword(s):  
Message Passing ◽  
Massive Mimo ◽  
Mimo Detection ◽  
Approximate Message Passing

scholarly journals Optimal Massive MIMO Detection for 5G Communication Systems via Hybrid n-Bit Heuristic Assisted-VBLAST

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 173646-173656
Author(s):  
Muhammad Haroon Siddiqui ◽  
Kiran Khurshid ◽  
Imran Rashid ◽  
Adnan Ahmed Khan ◽  
Khubaib Ahmed
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Detection ◽  
5G Communication
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