Special Issue "Massive MIMO Systems"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: 31 July 2019

Special Issue Editors

Guest Editor
Dr. Kazuki Maruta

Graduate School of Engineering, Chiba University, Chiba 263-8522, Japan
Website | E-Mail
Interests: adaptive array, massive MIMO, cooperative base station, multihop relay
Guest Editor
Dr. Francisco Falcone

Department of Electrical and Electronic Engineering, Public University of Navarre, 31006 Pamplona, Navarra, Spain
Website | E-Mail
Interests: electromagnetic modelling; simulation and design; wireless systems; context-aware environments; smart cities; internet of things

Special Issue Information

Dear Colleagues,

We are going to see the first decade since the fundamental concept of Massive MIMO (or called large-scale MIMO) has emerged. Massive MIMO technologies are now in implementation and trial stages towards 5G and beyond. Thanks to its excessive degree of freedom (DoF), massive MIMO has unlimited potentiality to further enhance system capabilities and still expands various research topics with depth. It can be further discussed and believed to break limitations in wireless communications such as spectral and energy efficiencies for better support of continuously increasing mobile data traffic, as well as terminals.

This Special Issue accordingly calls recent advances related to massive MIMO technologies that cover all signal processing, system level analysis, and implementation aspects. Topics of interest in this Special Issue include, but are not limited to, the following:

  • Hybrid beamforming
  • Beam tracking for moving target
  • Millimeter wave
  • Full digital-signal processing
  • Energy efficiency and wireless power transfer
  • Localization and direction-of-arrival (DoA) estimation
  • Compressed sensing
  • Pilot decontamination and channel estimation
  • Antenna array configuration
  • Machine learning approach for pre/post coding
  • Implementation and caribration
  • Proof-of-concept (PoC) and trials

Dr. Kazuki Maruta
Prof. Francisco Falcone
Guest Editors

Manuscript Submission Information

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Published Papers (10 papers)

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Research

Open AccessArticle An Efficient Pilot Assignment Scheme for Addressing Pilot Contamination in Multicell Massive MIMO Systems
Electronics 2019, 8(4), 372; https://doi.org/10.3390/electronics8040372
Received: 25 February 2019 / Revised: 17 March 2019 / Accepted: 21 March 2019 / Published: 27 March 2019
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Abstract
The reuse of the same pilot group across cells to address bandwidth limitations in a network has resulted in pilot contamination. This causes severe inter-cell interference at the targeted cell. Pilot contamination is associated with multicell massive multiple-input multiple-output (MIMO) systems which degrades [...] Read more.
The reuse of the same pilot group across cells to address bandwidth limitations in a network has resulted in pilot contamination. This causes severe inter-cell interference at the targeted cell. Pilot contamination is associated with multicell massive multiple-input multiple-output (MIMO) systems which degrades the system performance even when extra arrays of antennas are added to the network. In this paper, we propose an efficient pilot assignment (EPA) scheme to address this issue by maximizing the minimum uplink rate of the target cell’s users. To achieve this, we exploit the large-scale characteristics of the fading channel to minimize the amount of outgoing inter-cell interference at the target cell. Results from the simulation show that the EPA scheme outperforms both the conventional and the smart pilot assignment (SPA) schemes by reducing the effect of inter-cell interference. These results, show that the EPA scheme has significantly improved the system performance in terms of achievable uplink rate and cumulative distribution function (CDF) for both signal-to-interference-plus-noise ratio (SINR), and uplink rate. Full article
(This article belongs to the Special Issue Massive MIMO Systems)
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Open AccessArticle Evaluation of Multi-Beam Massive MIMO Considering MAC Layer Using IEEE802.11ac and FDD-LTE
Electronics 2019, 8(2), 225; https://doi.org/10.3390/electronics8020225
Received: 26 January 2019 / Revised: 14 February 2019 / Accepted: 14 February 2019 / Published: 18 February 2019
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Abstract
Massive multiple-input multiple-output (MIMO) transmission has attracted attention as a key technology for use in fifth-generation mobile communication systems. Multi-beam massive MIMO systems that apply beam selection in analog components and blind algorithms in digital components to eliminate the requirement for channel state [...] Read more.
Massive multiple-input multiple-output (MIMO) transmission has attracted attention as a key technology for use in fifth-generation mobile communication systems. Multi-beam massive MIMO systems that apply beam selection in analog components and blind algorithms in digital components to eliminate the requirement for channel state information have been proposed as a method for reducing overhead. In this study, we developed an adaptive modulation scheme for implementing multi-beam massive MIMO and used computer simulation to compare it with digital and analog–digital hybrid beam-forming methods. The effectiveness of the proposed system was verified in a medium access control layer based on the IEEE802.11ac and frequency division duplex-LTE representative wireless communication standards. Full article
(This article belongs to the Special Issue Massive MIMO Systems)
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Open AccessFeature PaperArticle Hybrid Beamforming for Millimeter-Wave Heterogeneous Networks
Electronics 2019, 8(2), 133; https://doi.org/10.3390/electronics8020133
Received: 23 December 2018 / Revised: 21 January 2019 / Accepted: 23 January 2019 / Published: 28 January 2019
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Abstract
Heterogeneous networks (HetNets) employing massive multiple-input multiple-output (MIMO) and millimeter-wave (mmWave) technologies have emerged as a promising solution to enhance the network capacity and coverage of next-generation 5G cellular networks. However, the use of traditional fully-digital MIMO beamforming methods, which require one radio [...] Read more.
Heterogeneous networks (HetNets) employing massive multiple-input multiple-output (MIMO) and millimeter-wave (mmWave) technologies have emerged as a promising solution to enhance the network capacity and coverage of next-generation 5G cellular networks. However, the use of traditional fully-digital MIMO beamforming methods, which require one radio frequency (RF) chain per antenna element, is not practical for large-scale antenna arrays, due to the high cost and high power consumption. To reduce the number of RF chains, hybrid analog and digital beamforming has been proposed as an alternative structure. In this paper, therefore, we consider a HetNet formed with one macro-cell base station (MBS) and multiple small-cell base stations (SBSs) equipped with large-scale antenna arrays that employ hybrid analog and digital beamforming. The analog beamforming weight vectors of the MBS and the SBSs correspond to the the best-fixed multi-beams obtained by eigendecomposition schemes. On the other hand, digital beamforming weights are optimized to maximize the receive signal-to-interference-plus-noise ratio (SINR) of the effective channels consisting of the cascade of the analog beamforming weights and the actual channel. The performance is evaluated in terms of the beampatterns and the ergodic channel capacity and shows that the proposed hybrid beamforming scheme achieves near-optimal performance with only four RF chains while requiring considerably less computational complexity. Full article
(This article belongs to the Special Issue Massive MIMO Systems)
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Open AccessArticle LOS-Based Equal Gain Transmission and Combining in General Frequency-Selective Ricean Massive MIMO Channels
Electronics 2019, 8(1), 79; https://doi.org/10.3390/electronics8010079
Received: 13 December 2018 / Revised: 6 January 2019 / Accepted: 7 January 2019 / Published: 10 January 2019
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Abstract
In general frequency-selective Ricean fading environments with doubly-ended spatial correlation, this paper investigates the spectral efficiency of a broadband massive multiple-input multiple-output (MIMO) system. In particular, in order to reduce overhead of channel estimation effectively, it proposes a scheme of equal gain transmission [...] Read more.
In general frequency-selective Ricean fading environments with doubly-ended spatial correlation, this paper investigates the spectral efficiency of a broadband massive multiple-input multiple-output (MIMO) system. In particular, in order to reduce overhead of channel estimation effectively, it proposes a scheme of equal gain transmission and combining, which is only based on line- of-sight (LOS) component and has low hardware complexity. With the scheme, several interesting transmit power scaling properties without and with spatial correlation are derived when the number of antennas at the transmitter or the number of antennas at the receiver grows in an unlimited way. Furthermore, the asymptotical rate analysis is extended to the cooperative relaying scenarios with decode-and-forward and amplify-and-forward protocols, respectively, and then two novel power scaling laws are given. Full article
(This article belongs to the Special Issue Massive MIMO Systems)
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Open AccessArticle Efficient Pilot Decontamination Schemes in 5G Massive MIMO Systems
Electronics 2019, 8(1), 55; https://doi.org/10.3390/electronics8010055
Received: 26 November 2018 / Revised: 26 December 2018 / Accepted: 27 December 2018 / Published: 3 January 2019
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Abstract
Massive Multiple-input Multiple-output (MIMO) is an emerging technology for the 5G wireless communication systems which has the potential to provide high spectral efficient and improved link reliability and accommodate large number of users. Aiming at the problem of pilot contamination in massive MIMO [...] Read more.
Massive Multiple-input Multiple-output (MIMO) is an emerging technology for the 5G wireless communication systems which has the potential to provide high spectral efficient and improved link reliability and accommodate large number of users. Aiming at the problem of pilot contamination in massive MIMO systems, this paper proposes two algorithms to mitigate it. The first algorithm is depending on the idea of Path Loss to perform User Grouping (PLUG) which divide the users into the center and edge user groups depending on different levels of pilot contamination. It assigns the same pilot sequences to the center users which slightly suffer from pilot contamination and assign orthogonal pilot sequences to the edge users which severely suffer from pilot contamination. It is assumed that the number of users at the edge of each cell is the same. Therefore, to overcome such limitations of PLUG algorithm, we propose an improved PLUG (IPLUG) algorithm which provides the decision parameters for user grouping and selects the number of central and edge users in each cell in a dynamic manner. Thus, the algorithm prevents the wrong division of users in good channel conditions being considered as an edge user which causes large pilot overhead, and also identifies the users with worst channel conditions and prevents the wrong division of such users from the center user group. The second algorithm for pilot decontamination utilizes the idea of pseudo-random codes in which orthogonal pilot are assigned to different cells. Such codes are deployed to get a transmission pilot by scrambling the user pilot in the cell. Since the pilot contamination is generated because different cells multiplex the same set of orthogonal pilots and the pseudo-random sequences have good cross-correlation characteristics, this paper uses this feature to improve the orthogonality of pilots between different cells. Simulation results show that the proposed algorithms can effectively improve channel estimation performance and achievable rate as compared with other schemes. Full article
(This article belongs to the Special Issue Massive MIMO Systems)
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Open AccessArticle Channel Sounding for Multi-User Massive MIMO in Distributed Antenna System Environment
Electronics 2019, 8(1), 36; https://doi.org/10.3390/electronics8010036
Received: 20 November 2018 / Revised: 14 December 2018 / Accepted: 21 December 2018 / Published: 1 January 2019
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Abstract
We propose a generation scheme for a sounding reference signal (SRS) suitable for supporting a large number of users in massive multi-input multi-output (MIMO) system with a distributed antenna system (DAS) environment. The proposed SRS can alleviate the pilot contamination problem which occurs [...] Read more.
We propose a generation scheme for a sounding reference signal (SRS) suitable for supporting a large number of users in massive multi-input multi-output (MIMO) system with a distributed antenna system (DAS) environment. The proposed SRS can alleviate the pilot contamination problem which occurs inherently in the multi-user system due to the limited number of orthogonal sequences. The proposed SRS sequence is generated by applying a well-chosen phase rotation to the conventional LTE/LTE-A SRS sequences without requiring an increased amount of resource usage. We also propose using the correlation-aided channel estimation algorithm as a supplemental scheme to obtain more reliable and refined channel estimation. It is shown that the proposed SRS sequence and the supplemental channel estimation scheme improve significantly the channel estimation performance in multi-user massive MIMO systems. Full article
(This article belongs to the Special Issue Massive MIMO Systems)
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Open AccessArticle Spectral and Energy Efficiency of Distributed Massive MIMO with Low-Resolution ADC
Electronics 2018, 7(12), 391; https://doi.org/10.3390/electronics7120391
Received: 15 November 2018 / Revised: 2 December 2018 / Accepted: 3 December 2018 / Published: 4 December 2018
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Abstract
In this paper, considering a more realistic case where the low-resolution analog-to-digital convertors (ADCs) are employed at receiver antennas, we investigate the spectral and energy efficiency in multi-cell multi-user distributed massive multi-input multi-output (MIMO) systems with two linear receivers. An additive quantization noise [...] Read more.
In this paper, considering a more realistic case where the low-resolution analog-to-digital convertors (ADCs) are employed at receiver antennas, we investigate the spectral and energy efficiency in multi-cell multi-user distributed massive multi-input multi-output (MIMO) systems with two linear receivers. An additive quantization noise model is provided first to study the effects of quantization noise. Using the model provided, the closed-form expressions for the uplink achievable rates with a zero-forcing (ZF) receiver and a maximum ratio combination (MRC) receiver under quantization noise and pilot contamination are derived. Furthermore, the asymptotic achievable rates are also given when the number of quantization bits, the per user transmit power, and the number of antennas per remote antenna unit (RAU) go to infinity, respectively. Numerical results prove that the theoretical analysis is accurate and show that quantization noise degrades the performance in spectral efficiency, but the growth in the number of antennas can compensate for the degradation. Furthermore, low-resolution ADCs with 3 or 4 bits outperform perfect ADCs in energy efficiency. Numerical results imply that it is preferable to use low-resolution ADCs in distributed massive MIMO systems. Full article
(This article belongs to the Special Issue Massive MIMO Systems)
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Open AccessArticle Planar Array Diagnostic Tool for Millimeter-Wave Wireless Communication Systems
Electronics 2018, 7(12), 383; https://doi.org/10.3390/electronics7120383
Received: 8 October 2018 / Revised: 21 November 2018 / Accepted: 23 November 2018 / Published: 3 December 2018
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Abstract
In this paper, a diagnostic tool or procedure based on Bayesian compressive sensing (BCS) is proposed for identification of failed element(s) which manifest in millimeter-wave planar antenna arrays. With adequate a priori knowledge of the reference antenna array radiation pattern, a diagnostic problem [...] Read more.
In this paper, a diagnostic tool or procedure based on Bayesian compressive sensing (BCS) is proposed for identification of failed element(s) which manifest in millimeter-wave planar antenna arrays. With adequate a priori knowledge of the reference antenna array radiation pattern, a diagnostic problem of faulty elements was formulated. Sparse recovery algorithms, including total variation (TV), mixed 1 / 2 norm, and minimization of the 1 , are readily available in the literature, and were used to diagnose the array under test (AUT) from measurement points, consequently providing faster and better diagnostic schemes than the traditional mechanisms, such as the back propagation algorithm, matrix method algorithm, etc. However, these approaches exhibit some drawbacks in terms of effectiveness and reliability in noisy data, and a large number of measurement data points. To overcome these problems, a methodology based on BCS was adapted in this paper. From far-field radiation pattern samples, planar array diagnosis was formulated as a sparse signal recovery problem where BCS was applied to recover the locations of the faults using relevance vector machine (RVM). The resulted BCS approach was validated through simulations and experiments to provide suitable guidelines for users, as well as insight into the features and potential of the proposed procedure. A Ka-band ( 28.9   GHz ) 10 × 10 rectangular microstrip patch antenna array that emulates failure with zero excitation was designed for far-field measurements in an anechoic chamber. Both simulated and measured far-field samples were used to test the proposed approach. The proposed technique is demonstrated to detect diagnostic problems with fewer measurements provided the prior knowledge of the array radiation pattern is known, and the number of faults is relatively smaller than the array size. The effectiveness and reliability of the technique is verified experimentally and via simulation. In addition to a faster diagnosis and better reconstruction accuracy, the BCS-based technique shows more robustness to additive noisy data compared to other compressive sensing methods. The proposed procedure can be applied to next-generation transceivers, aerospace systems, radar systems, and other communication systems. Full article
(This article belongs to the Special Issue Massive MIMO Systems)
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Open AccessArticle Computationally Efficient Channel Estimation in 5G Massive Multiple-Input Multiple-output Systems
Electronics 2018, 7(12), 382; https://doi.org/10.3390/electronics7120382
Received: 9 November 2018 / Revised: 22 November 2018 / Accepted: 28 November 2018 / Published: 3 December 2018
Cited by 1 | PDF Full-text (2932 KB) | HTML Full-text | XML Full-text
Abstract
Traditional channel estimation algorithms such as minimum mean square error (MMSE) are widely used in massive multiple-input multiple-output (MIMO) systems, but require a matrix inversion operation and an enormous amount of computations, which result in high computational complexity and make them impractical to [...] Read more.
Traditional channel estimation algorithms such as minimum mean square error (MMSE) are widely used in massive multiple-input multiple-output (MIMO) systems, but require a matrix inversion operation and an enormous amount of computations, which result in high computational complexity and make them impractical to implement. To overcome the matrix inversion problem, we propose a computationally efficient hybrid steepest descent Gauss–Seidel (SDGS) joint detection, which directly estimates the user’s transmitted symbol vector, and can quickly converge to obtain an ideal estimation value with a few simple iterations. Moreover, signal detection performance was further improved by utilizing the bit log-likelihood ratio (LLR) for soft channel decoding. Simulation results showed that the proposed algorithm had better channel estimation performance, which improved the signal detection by 31.68% while the complexity was reduced by 45.72%, compared with the existing algorithms. Full article
(This article belongs to the Special Issue Massive MIMO Systems)
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Open AccessArticle Downlink Spectral Efficiency Analysis in Distributed Massive MIMO with Phase Noise
Electronics 2018, 7(11), 317; https://doi.org/10.3390/electronics7110317
Received: 25 October 2018 / Revised: 6 November 2018 / Accepted: 10 November 2018 / Published: 12 November 2018
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Abstract
To achieve the advantages provided by massive multiple-input multiple-output (MIMO), a large number of antennas need to be deployed at the base station. However, for the reason of cost, inexpensive hardwares are employed in the realistic scenario, which makes the system distorted by [...] Read more.
To achieve the advantages provided by massive multiple-input multiple-output (MIMO), a large number of antennas need to be deployed at the base station. However, for the reason of cost, inexpensive hardwares are employed in the realistic scenario, which makes the system distorted by hardware impairments. Hence, in this paper, we analyze the downlink spectral efficiency in distributed massive MIMO with phase noise and amplified thermal noise. We provide an effective channel model considering large-scale fading, small-scale fast fading and phase noise. Based on the model, the estimated channel state information (CSI) is obtained during the pilot phase. Under the imperfect CSI, the closed-form expressions of downlink achievable rates with maximum ratio transmission (MRT) and zero-forcing (ZF) precoders in distributed massive MIMO are derived. Furthermore, we also give the user ultimate achievable rates when the number of antennas tends to infinity with both precoders. Based on these expressions, we analyze the impacts of phase noise on the spectral efficiency. It can be concluded that the same limit rate is achieved with both precoders when phase noise is present, and phase noise limits the spectral efficiency. Numerical results show that ZF outdoes MRT precoder in spectral efficiency and ZF precoder is more affected by phase noise. Full article
(This article belongs to the Special Issue Massive MIMO Systems)
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