Massive MIMO Systems for 5G

The global bandwidth shortage in the wireless communication sector has motivated the study and exploration of wireless access technology known as massive Multiple-Input Multiple-Output (MIMO). Massive MIMO is one of the key enabling technology for next-generation networks, which groups together antennas at both transmitter and the receiver to provide high spectral and energy efficiency using relatively simple processing. Obtaining a better understating of the massive MIMO system to overcome the fundamental issues of this technology is vital for the successful deployment of 5G—and beyond—networks to realize various applications of the intelligent sensing system. In this paper, we present a comprehensive overview of the key enabling technologies required for 5G and 6G networks, highlighting the massive MIMO systems. We discuss all the fundamental challenges related to pilot contamination, channel estimation, precoding, user scheduling, energy efficiency, and signal detection in a massive MIMO system and discuss some state-of-the-art mitigation techniques. We outline recent trends such as terahertz communication, ultra massive MIMO (UM-MIMO), visible light communication (VLC), machine learning, and deep learning for massive MIMO systems. Additionally, we discuss crucial open research issues that direct future research in massive MIMO systems for 5G and beyond networks.

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The Downlink Performance for Cell-Free Massive MIMO with Instantaneous CSI in Slowly Time-Varying Channels

Entropy ◽

10.3390/e23111552 ◽

2021 ◽

Vol 23 (11) ◽

pp. 1552

Author(s):

Tongzhou Han ◽

Danfeng Zhao

Keyword(s):

Power Control ◽

Massive Mimo ◽

Mimo Systems ◽

Mimo System ◽

Multiple Input Multiple Output ◽

Time Varying ◽

Input Multiple Output ◽

Efficiency Performance ◽

A Cell ◽

Time Varying Channel

In centralized massive multiple-input multiple-output (MIMO) systems, the channel hardening phenomenon can occur, in which the channel behaves as almost fully deterministic as the number of antennas increases. Nevertheless, in a cell-free massive MIMO system, the channel is less deterministic. In this paper, we propose using instantaneous channel state information (CSI) instead of statistical CSI to obtain the power control coefficient in cell-free massive MIMO. Access points (APs) and user equipment (UE) have sufficient time to obtain instantaneous CSI in a slowly time-varying channel environment. We derive the achievable downlink rate under instantaneous CSI for frequency division duplex (FDD) cell-free massive MIMO systems and apply the results to the power control coefficients. For FDD systems, quantized channel coefficients are proposed to reduce feedback overhead. The simulation results show that the spectral efficiency performance when using instantaneous CSI is approximately three times higher than that achieved using statistical CSI.

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Pilot Decontamination Using Asynchronous Fractional Pilot Scheduling in Massive MIMO Systems

Sensors ◽

10.3390/s20216213 ◽

2020 ◽

Vol 20 (21) ◽

pp. 6213

Author(s):

Muhammad Irshad Zahoor ◽

Zheng Dou ◽

Syed Bilal Hussain Shah ◽

Imran Ullah Khan ◽

Sikander Ayub ◽

...

Keyword(s):

Massive Mimo ◽

Mimo Systems ◽

Mimo System ◽

Multiple Input Multiple Output ◽

Multiple Input ◽

Input Multiple Output ◽

Ideal Number ◽

Sum Rate ◽

Inter Cell Interference ◽

Time Division

Due to large spectral efficiency and low power consumption, the Massive Multiple-Input-Multiple-Output (MIMO) became a promising technology for the 5G system. However, pilot contamination (PC) limits the performance of massive MIMO systems. Therefore, two pilot scheduling schemes (i.e., Fractional Pilot Reuse (FPR) and asynchronous fractional pilot scheduling scheme (AFPS)) are proposed, which significantly mitigated the PC in the uplink time division duplex (TDD) massive MIMO system. In the FPR scheme, all the users are distributed into the central cell and edge cell users depending upon their signal to interference plus noise ratio (SINR). Further, the capacity of central and edge users is derived in terms of sum-rate, and the ideal number of the pilot is calculated which significantly maximized the sum rate. In the proposed AFPS scheme, the users are grouped into central users and edge users depending upon the interference they receive. The central users are assigned the same set of pilots because these users are less affected by interference, while the edge users are assigned the orthogonal pilots because these users are severely affected by interference. Consequently, the pilot overhead is reduced and inter-cell interference (ICI) is minimized. Further, results verify that the proposed schemes outperform the previous proposed traditional schemes, in terms of improved sum rates.

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A Comparison of Norm Based Antenna Selection and Random Antenna Selection with Regard to Energy Efficiency in Wireless System with Large Number of Users

International Journal of Sensors Wireless Communications and Control ◽

10.2174/2210327909666190319145555 ◽

2020 ◽

Vol 10 (2) ◽

pp. 189-196

Author(s):

Ashu Taneja ◽

Nitin Saluja

Keyword(s):

Energy Efficiency ◽

Mimo Systems ◽

Antenna Selection ◽

Mimo System ◽

Multiple Input Multiple Output ◽

Base Station ◽

Transmit Antenna Selection ◽

Wireless System ◽

Multiple Input ◽

Input Multiple Output

Background: The paper considers the wireless system with large number of users (more than 50 users) and each user is assigned large number of antennas (around 200) at the Base Station (BS). Objective: The challenges associated with the defined system are increased power consumption and high complexity of associated circuitry. The antenna selection is introduced to combat these problems while the usage of linear precoding reduces computational complexity. The literature suggests number of antenna selection techniques based on statistical properties of signal. However, each antenna selection technique suits well to specific number of users. Methods: In this paper, the random antenna selection is compared with norm-based antenna selection. It is analysed that the random antenna selection leads to inefficient spectral efficiency if the number of users are more than 50 in Multi-User Multiple-Input Multiple Output (MU-MIMO) system. Results: The paper proposes the optimization of Energy-Efficiency (EE) with random transmit antenna selection for large number of users in MU-MIMO systems. Conclusion: Also the computation leads to optimization of number of transmit antennas at the BS for energy efficiency. The proposed algorithm results in improvement of the energy efficiency by 27% for more than 50 users.

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Improved Port Modulation for Multiuser Massive MIMO Systems

International Journal of Interdisciplinary Telecommunications and Networking ◽

10.4018/ijitn.2015100102 ◽

2015 ◽

Vol 7 (4) ◽

pp. 15-25

Author(s):

Yujiao He ◽

Jianing Zhao ◽

Lijuan Tao ◽

Fuyu Hou ◽

Wei Jia

Keyword(s):

Massive Mimo ◽

Mimo Systems ◽

Mimo System ◽

Multiple Input Multiple Output ◽

Channel State ◽

State Information ◽

Multiple Input ◽

Input Multiple Output ◽

Simulation Results ◽

Csi Feedback

This paper proposes an improved port modulation (PM) method which can be applied to the multiuser (MU) massive multiple-input multiple-output (MIMO) system. The precoding process of the improved PM can be divided into two parts: port precoding and MU precoding. The methods of the precoding and detection are provided and the performance of the proposed improved PM is simulated and analyzed. Simulation results show that the proposed improved PM system can achieve a satisfying bit error rate (BER) performance with a cutdown channel state information (CSI) feedback.

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Efficient Detectors based on Group Detection for Massive MIMO systems

REV Journal on Electronics and Communications ◽

10.21553/rev-jec.167 ◽

2018 ◽

Author(s):

Thanh-Binh Nguyen ◽

Minh-Tuan Le ◽

Vu-Duc Ngo ◽

Tien-Dong Nguyen ◽

Huy-Dung Han

Keyword(s):

Massive Mimo ◽

Mimo Systems ◽

Mimo System ◽

Minimum Mean Square Error ◽

Multiple Input Multiple Output ◽

Bell Laboratory ◽

Channel Matrix ◽

Input Multiple Output ◽

Group Detection ◽

Ber Performance

In Multiple Input Multiple Output (MIMO) systems, the complexities of detectors depend on the size of the channel matrix. In Massive MIMO systems, detection complexity becomes remarkably higher because the dimensions of the channel matrix get much larger. In order to recover the signals in the up-link of a Massive MIMO system at reduced complexities, we first divide the system into two sub-systems. After that, we apply the Minimum Mean Square Error (MMSE) and Bell Laboratory Layer Space Time (BLAST) detectors to each subsystem, resulting in the so-called MMSE-GD and BLAST-GD detectors, respectively. To further enhance the BER performance of Massive MIMO systems under the high-load conditions, we propose two additional detectors, called MMSE-IGD and BLAST-IGD by respectively applying the conventional MMSE and BLAST on the sub-systems in an iterative manner. It is shown via computer simulation and analytical results that the proposed detectors enable the system to achieve not only higher BER performance but also low detection complexities as compared to the conventional linear detectors. Moreover, the MMSE-IGD and BLAST-IGD can significantly improve BER performance of Massive MIMO systems.

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Massive MIMO Techniques for 5G and Beyond—Opportunities and Challenges

Electronics ◽

10.3390/electronics10141667 ◽

2021 ◽

Vol 10 (14) ◽

pp. 1667

Author(s):

David Borges ◽

Paulo Montezuma ◽

Rui Dinis ◽

Marko Beko

Keyword(s):

Energy Efficiency ◽

Massive Mimo ◽

Mimo Systems ◽

Multiple Input Multiple Output ◽

Spatial Multiplexing ◽

Existing Problems ◽

Multiple Input ◽

Input Multiple Output ◽

Mimo Transmission ◽

Diversity Gains

Telecommunications have grown to be a pillar to a functional society and the urge for reliable and high throughput systems has become the main objective of researchers and engineers. State-of-the-art work considers massive Multiple-Input Multiple-Output (massive MIMO) as the key technology for 5G and beyond. Large spatial multiplexing and diversity gains are some of the major benefits together with an improved energy efficiency. Current works mostly assume the application of well-established techniques in a massive MIMO scenario, although there are still open challenges regarding hardware and computational complexities and energy efficiency. Fully digital, analog, and hybrid structures are analyzed and a multi-layer massive MIMO transmission technique is detailed. The purpose of this article is to describe the most acknowledged transmission techniques for massive MIMO systems and to analyze some of the most promising ones and identify existing problems and limitations.

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A companding approach for PAPR suppression in OFDM based massive MIMO system

Journal of Optical Communications ◽

10.1515/joc-2020-0255 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Ajay Kumar Yadav ◽

Pritam Keshari Sahoo ◽

Yogendra Kumar Prajapati

Keyword(s):

Massive Mimo ◽

Orthogonal Frequency Division Multiplexing ◽

Mimo System ◽

Multiple Input Multiple Output ◽

Average Power ◽

Base Station ◽

Convex Optimization Problem ◽

Multiple Input ◽

Input Multiple Output ◽

Mimo Ofdm

Abstract Orthogonal frequency division multiplexing (OFDM) based massive multiuser (MU) multiple input multiple output (MIMO) system is popularly known as high peak-to-average power ratio (PAPR) issue. The OFDM-based massive MIMO system exhibits large number of antennas at Base Station (BS) due to the use of large number of high-power amplifiers (HPA). High PAPR causes HPAs to work in a nonlinear region, and hardware cost of nonlinear HPAs are very high and also power inefficient. Hence, to tackle this problem, this manuscript suggests a novel scheme based on the joint MU precoding and PAPR minimization (PP) expressed as a convex optimization problem solved by steepest gradient descent (GD) with μ-law companding approach. Therefore, we develop a new scheme mentioned to as MU-PP-GDs with μ-law companding to minimize PAPR by compressing and enlarging of massive MIMO OFDM signals simultaneously. At CCDF = 10−3, the proposed scheme (MU-PP-GDs with μ-law companding for Iterations = 100) minimizes the PAPR to 3.70 dB which is better than that of MU-PP-GDs, (iteration = 100) as shown in simulation results.

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PROBLEM STATEMENT OF JOINT ANTENNA SELECTION AND PRECODING IN MASSIVE MIMO COMMUNICATION SYSTEMS

Электросвязь ◽

10.34832/elsv.2021.21.8.008 ◽

2021 ◽

Author(s):

В.Б. КРЕЙНДЕЛИН ◽

М.В. ГОЛУБЕВ

Keyword(s):

Massive Mimo ◽

Communication Systems ◽

Mimo Systems ◽

Antenna Selection ◽

Multiple Input Multiple Output ◽

Research Areas ◽

Multiple Input ◽

Input Multiple Output ◽

Legal Restrictions ◽

Multiple Transmission

Совместный с прекодингом автовыбор антенн на приемной и передающей стороне - одно из перспективных направлений исследований для реализации технологий Multiple Transmission and Reception Points (Multi-TRP, множество точек передачи и приема) в системах со многими передающими и приемными антеннами Massive MIMO (Multiple-Input-Multiple-Output), которые активно развиваются в стандарте 5G. Проанализированы законодательные ограничения, влияющие на применимость технологий Massive MIMO, и специфика реализации разрабатываемого алгоритма в миллиметровомдиапа -зоне длин волн. Рассмотрены алгоритмы формирования матриц автовыбора антенн как на передающей, так и на приемной стороне. Сформулирована строгая математическая постановка задачи для двух критериев работы алгоритма: максимизация взаимной информации и минимизация среднеквадратичной ошибки. Joint precoding and antenna selection both on transmitter and receiver sides is one of the promising research areas for evolving toward the Multiple Transmission and Reception Points (Multi-TRP) concept in Massive MIMO systems. This technology is under active development in the coming 5G 3GPP releases. We analyze legal restrictions for the implementation of 5G Massive MIMO technologies in Russia and the specifics of the implementation of the developed algorithm in the millimeter wavelength range. Algorithms of antenna auto-selection matrices formation on both transmitting and receiving sides are considered. Two criteria are used for joint antenna selection and precoding: maximizing mutual information and minimizing mean square error.

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Maximizing Energy Efficiency for Consumption Circuit Power in Downlink Massive MIMO Wireless Networks

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v7i6.pp2977-2985 ◽

2017 ◽

Vol 7 (6) ◽

pp. 2977 ◽

Cited By ~ 3

Author(s):

Adeeb Salh ◽

Lukman Audah ◽

Nor Shahida M. Shah ◽

Shipun A. Hamzah

Keyword(s):

Energy Efficiency ◽

Massive Mimo ◽

Mimo Systems ◽

Mimo System ◽

Minimum Mean Square Error ◽

Data Rate ◽

Optimal Number ◽

Zero Forcing ◽

High Data ◽

Circuit Power

Massive multi-input–multi-output (MIMO) systems are crucial to maximizing energy efficiency (EE) and battery-saving technology. Achieving EE without sacrificing the quality of service (QoS) is increasingly important for mobile devices. We first derive the data rate through zero forcing (ZF) and three linear precodings: maximum ratio transmission (MRT), zero forcing (ZF), and minimum mean square error (MMSE). Performance EE can be achieved when all available antennas are used and when taking account of the consumption circuit power ignored because of high transmit power. The aim of this work is to demonstrate how to obtain maximum EE while minimizing power consumed, which achieves a high data rate by deriving the optimal number of antennas in the downlink massive MIMO system. This system includes not only the transmitted power but also the fundamental operation circuit power at the transmitter signal. Maximized EE depends on the optimal number of antennas and determines the number of active users that should be scheduled in each cell. We conclude that the linear precoding technique MMSE achieves the maximum EE more than ZF and MRTbecause the MMSE is able to make the massive MIMO system less sensitive to SNR at an increased number of antennas.

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