Massive Multiple-input Multiple-output Antenna Research Articles

Statistical Analysis of 5G Channel Propagation using MIMO and Massive MIMO Technologies

Multiple Input Multiple Output (MIMO) and massive MIMO technologies play a significant role in mitigating five generation (5G) channel propagation impairments. These impairments increase as frequency increases, and they become worse at millimeter-waves (mmWaves). They include difficulties of material penetration, Line-of-Sight (LoS) inflexibility, small cell coverage, weather circumstances, etc. This paper simulates the 5G channel at the E-band frequency using the Monte Carlo approach-based NYUSIM tool. The urban microcell (UMi) is the communication environment of this simulation. Both MIMO and massive MIMO use uniformly spaced rectangular antenna arrays (URA). This study investigates the effects of MIMO and massive MIMO on LOS and Non-LOS (NLOS) environments. The simulations considered directional and omnidirectional antennas, the Power Delay Profile (PDP), Root Mean Square (RMS) delay spread, and small-scale PDP for both LOS and NLOS environments. As expected, the wide variety of the results showed that the massive MIMO antenna outperforms the MIMO antenna, especially in terms of the signal power received at the end-user and for longer path lengths.

A massive MIMO frame antenna with frequency agility and polarization diversity for LTE and 5G applications

A switchable antenna array is presented for upcoming 4G/5G massive multiple-input multiple-output (MIMO) smartphone applications. The designed antenna is constructed of two modules of the antenna array, namely, a switchable 2 × 2 MIMO 4G antenna module with frequency and circular polarization diversities and a 6 × 6 MIMO 5G antenna module with pattern diversity. Each element in the 4G and 5G modules is fed using by a microstrip line with a tuning slot on the ground plane, consisting of a spiral patch and a short-ended C-shaped stab as parasitic element on the non-metal frame. An area of 22 × 9.3 mm2 is occupied with each element on the ground plane. Spatial diversity and polarization techniques are used for these antenna elements with the purpose of the reduced coupling effects and enhanced isolation can be achieved. The module of 4G antenna can be work and switch between two operating bands of LTE-2500 and 5G band by embedding a PIN diode in the structure of antenna element, while the 5G antenna module can be operate in the 3.4–3.6 GHz and could meet the request of upcoming 5G application. The proposed MIMO antenna array is fabricated and tested. Measured isolation of the proposed antenna is more than 15.2 dB in the ON and OFF states of the PIN diodes without applying of any decoupling structures. Furthermore, measured antenna efficiency, radiation pattern, envelop correlation coefficient, and ergodic channel capacity over the desired bands are also verified in this article.

3D Metallic Plate Lens Antenna based Beamspace Channel Estimation Technique for 5G Mmwave Massive MIMO Systems

Beamspace channel estimation mechanism for massive MIMO (multiple input multiple output) antenna system presents a major process to compensate the 5G spectrum challenges caused by the proliferation of information from mobile devices. However, this estimation is required to ensure the perfect channel state information (CSI) for lower amount of Radio Frequency (RF) chains for each beam. In addition, phase shifter (PS) components used in this estimation need high power to select the beam in the desired direction. To overcome these limitations, in this work, we propose Regular Scanning Support Detection (RSSD) based channel estimation mechanism. Moreover, we utilise a 3D lens antenna array having metallic plate and a switch in our model which compensates the limitation of phase shifters. Simulation results show that the proposed RSSD based channel estimation surpasses traditional technique and SD based channel estimation even in lower SNR area which is highly desirable in the millimeter wave (mmWave) massive MIMO systems.

18 Element Massive MIMO/Diversity 5G Smartphones Antenna Design for Sub-6 GHz LTE Bands 42/43 Applications

This work presents an 18 element antenna system compatible with massive multiple input multiple output (MIMO)/Diversity fourth/fifth generation (4G/5G) smartphones. The antennas are designed at sub-6 GHz long term evolution (LTE) band 42 (3.4-3.6 GHz) and LTE band 43 (3.6-3.8 GHz). A simple slot type antenna is considered as the radiating element, with open ended slots used for obtaining a compact design. These slots also act as decoupling elements to improve the isolation among different radiators. The proposed antenna elements are designed on a low-cost FR-4 substrate having dimension of 150 mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times80$ </tex-math></inline-formula> mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times1.6$ </tex-math></inline-formula> mm, which can be typically used for 6-inch smart phones. The simulated and measured values of antenna gain are found to be greater than 5.3 dBi. Simulated and measured results of the proposed design show excellent impedance matching (reflection coefficient>20 dB), port isolation (>20 dB), total efficiency (>87%) and Envelope Correlation Coefficient (< 0.01) over the operating frequency. MIMO antenna performance metrics are verified by calculating the ergodic channel capacity with Kronecker channel model.

A Statistical Estimation of 5G Massive MIMO Networks’ Exposure Using Stochastic Geometry in mmWave Bands

This paper aims to derive an analytical modelling of the downlink exposure in 5G massive Multiple Input Multiple Output (MIMO) antenna networks using stochastic geometry. The Poisson point process (PPP) is assumed for base station (BS) distribution. The power received at the transmitter is modeled as a shot-noise process with a modified power law. The distributions of 5G massive MIMO antenna gain and channel gain were obtained by fitting simulation results from the NYUSIM channel simulator. The fitted distributions, e.g., exponential and gamma distribution for antenna and channel gain respectively, were then implemented into an analytical framework. In this paper, we obtained the closed-form expression of the moment-generating function (MGF) for the total exposure in the network. The framework is then validated by numerical simulations. The sensitivity analysis is carried out to investigate the impact of key parameters, e.g., BS density, path loss exponent, and transmission probability. We then proved and quantified the significant impact the transmission probability on global exposure, which indicates the importance of considering the network usage in 5G exposure estimations.

Optimization of Data Exchange in 5G Vehicle-to-Infrastructure Edge Networks

In recent years, intelligent transportation systems are a vital part of the development of smart cities. In intelligent transportation systems, it is necessary for each vehicle to know the states of all other running vehicles within a range, depends on the road speed limit. The states include location, travelling direction, speed, and possibly other useful information. Knowing the states of surrounding vehicles is critical in high-risk locations, such as traffic intersections and roundabouts. The development of 5G and its technologies, such as massive multiple-input multiple-output antenna, enables a new communication model, termed vehicle-to-infrastructure edge network (V2IEN), to achieve the above communication goal. In this paper, we study the optimization of the data throughput of the proposed V2IENs in 5G with the Time Division Duplex scheme. We show that due to the nature of information flow in the proposed V2IENs, the uplink and downlink traffic loads are asymmetric. This asymmetric characteristic allows maximizing the degrees of freedom of the V2IENs by optimizing the time-slot resources for uplink and downlink transmission. In this work, we present the sum-DoF capacity of the V2IENs with proof. We demonstrate that a significant DoF gain is achieved for the V2IENs by carefully allocate the system transmission time resources. We further propose an iterative algorithm for network sum-rate maximization via the optimization of the vehicle and base station precoders. Numerical results demonstrate that a careful design of the precoders at the base station and at the vehicles can considerably improve the V2IENs performance.

Approximate Expectation Propagation Massive MIMO Detector With Weighted Neumann-Series

Expectation propagation (EP) achieves near-optimal performance for massive multiple-input multiple-output (MIMO) detection, however, at the cost of multiple expensive matrix inversions. An EP with approximation (EPA) algorithm has been introduced to address this issue, which maintains the good performance with only one matrix inversion for initialization. Nevertheless, the accuracy of this inversion has a strong impact on the convergence of EPA, which hinders the practical implementation of the algorithm. In this brief, a weighted Neumann series approximation (wNSA) is first proposed for explicit inverse matrix approximation, which attains enhanced convergence rate and accuracy compared to standard NSA for various MIMO antenna configurations. wNSA is then combined with EPA to propose an efficient, flexible, and hardware-friendly EPA-wNSA detector. Simulation results are illustrated to confirm the similar good performance of the proposed EPA-wNSA as EP. The hardware architecture of EPA-wNSA detector is also proposed and implemented on 65 nm CMOS technology. Implementation results show that this architecture achieves a throughput of 0.86 Gb/s, which outperforms state-of-the-art (SOA) EP-based detectors.

Implementation of a Cloud-Based Cell-Free Distributed Massive MIMO System

With the ever increasing requirements for ultra efficiency, advanced technologies such as massive multiple-input multiple-output (MIMO) have been considered. By offering more flexility of antenna deployment, a distributed setup of a massive MIMO system can benefit from considerable efficiency improvement over the colocated counterpart. However, distributed massive MIMO antennas will result in design and implementation challenges regarding synchronization, calibration, real-time baseband processing, and so on. Thus, equipped with general-purpose processors, we propose a cloud-based cell-free distributed massive MIMO system, which can not only archive 5G NR requirements but also easily be extended to different application scales. As an illustrative example, a 128 x 128 distributed MU-MIMO system with frequency 100 MHz@3.5 GHz is given. Test results show that 10.185 Gb/s throughput and more than 100 b/s/Hz spectrum utilization can be obtained. Flexibly scaling to the target deployment density, this system can support various applications on cross-industry collaboration.

Automatic Calibration Using a Modified Genetic Algorithm for Millimeter-Wave Antenna Modules in MIMO Systems

This study proposes a method for designing and calibrating a millimeter-wave (mm-wave) multiple-input multiple-output (MIMO) antenna module. Herein, we adopt a design example involving a 64-element MIMO antenna array arranged in a triangular lattice (instead of the commonly used rectangular lattice) to achieve a 3°dB enhancement in effective isotropic radiated power. Analyzing a grating lobe diagram indicates a scan volume of ±60°/±45° in the azimuth/elevation direction. To calibrate the massive mm-wave MIMO antenna module, we propose a modified genetic algorithm to align the amplitude/phase of the transmitting/receiving signal of the module to reduce the time required for the calibration process. Finally, we conducted a simple experiment to validate the proposed method.

OTA Testing for Massive MIMO Devices Using Cascaded APM Networks and Channel Emulators

This paper proposes an over-the-air (OTA) testing setup for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) equipment using cascaded amplitude and phase modulation (APM) network and channel emulator. Compared with the existing test setup with mechanical switch, the proposed testing setup enables more accurate reconstruction of the radio channel environment under the multiprobe anechoic chamber (MPAC) setup without increasing the number of channel emulators (CEs) to control the system cost. The constructed MPAC testing setup for mmWave and massive MIMO equipment is composed of an anechoic chamber, a sectored probe wall containing a number of probes, an APM network, a fading channel emulator, and a user emulator (UE). In this paper, the structural model and the performance advantages of the proposed radiated testing setup are described, and a fully connected APM network for radiated testing is more prominent than the existing switch. Moreover, the angular spectrum is selected as the performance metric for the reconstructed channel. The ability of the proposed system to reconstruct the power angular spectrum (PAS) of the target channel is studied under both static and dynamic channel models, which can reflect the performance of beamforming procedures of the massive MIMO antenna arrays, e.g., beam acquisition, tracking, and refinement. The simulation results for angular spectrum support the superiority of the proposed OTA testing setup. Furthermore, the simulations for average channel capacity also show that radiated testing setup using cascaded APM network and channel emulator is valid.

Dynamic Metasurface Antennas for Uplink Massive MIMO Systems

Massive multiple-input-multiple-output (MIMO) communications are the focus of considerable interest in recent years. While the theoretical gains of massive MIMO have been established, implementing MIMO systems with large-scale antenna arrays in practice is challenging. Among the practical challenges associated with massive MIMO systems are increased cost, power consumption, and physical size. In this paper, we study the implementation of massive MIMO antenna arrays using dynamic metasurface antennas (DMAs), an emerging technology which inherently handles the aforementioned challenges. Specifically, DMAs realize large-scale planar antenna arrays and can adaptively incorporate signal processing methods such as compression and analog combining in the physical antenna structure, thus reducing the cost and power consumption. First, we propose a mathematical model for massive MIMO systems with DMAs and discuss their constraints compared to ideal antenna arrays. Then, we characterize the fundamental limits of uplink communications with the resulting systems and propose two algorithms for designing practical DMAs for approaching these limits. Our numerical results indicate that the proposed approaches result in practical massive MIMO systems whose performance is comparable to that achievable with ideal antenna arrays.

Mobile-Phone Antenna Array with Diamond-Ring Slot Elements for 5G Massive MIMO Systems

A design of mobile-phone antenna array with diamond-ring slot elements is proposed for fifth generation (5G) massive multiple-input/multiple-output (MIMO) systems. The configuration of the design consists of four double-fed diamond-ring slot antenna elements placed at different corners of the mobile-phone printed circuit board (PCB). A low-cost FR-4 dielectric with an overall dimension of 75 × 150 mm2 is used as the design substrate. The antenna elements are fed by 50-Ohm L-shaped microstrip-lines. Due to the orthogonal placement of microstrip feed lines, the diamond-ring slot elements can exhibit the polarization and radiation pattern diversity characteristic. A good impedance bandwidth (S11 ≤ −10 dB) of 3.2–4 GHz has been achieved for each antenna radiator. However, for S11 ≤ −6 dB, this value is 3–4.2 GHz. The proposed design provides the required radiation coverage of 5G smartphones. The performance of the proposed MIMO antenna design is examined using both simulation and experiment. High isolation, high efficiency and sufficient gain-level characteristics have been obtained for the proposed MIMO smartphone antenna. In addition, the calculated total active reflection coefficient (TARC) and envelope correlation coefficient (ECC) of the antenna elements are very low over the whole band of interest which verify the capability of the proposed multi-antenna systems for massive MIMO and diversity applications. Furthermore, the properties of the design in Data-mode/Talk-mode are investigated and presented.

Artificial Intelligence Defined 5G Radio Access Networks

Massive multiple-input multiple-output antenna systems, millimeter wave communications, and ultra-dense networks have been widely perceived as the three key enablers that facilitate the development and deployment of 5G systems. This article discusses the intelligent agent in 5G base station which combines sensing, learning, understanding and optimizing to facilitate these enablers. We present a flexible, rapidly deployable, and cross-layer artificial intelligence (AI)-based framework to enable the imminent and future demands on 5G and beyond infrastructure. We present example AI-enabled 5G use cases that accommodate important 5G-specific capabilities and discuss the value of AI for enabling beyond 5G network evolution.

A Novel MIMO Channel Model for Congested Communication Environments

This paper presents a novel multiple-input multiple-output (MIMO) channel model for congested curved-street vehicle-to-vehicle (V2V) non-line-of-sight communication environments, where the scatterers are located within narrow arcs along the curved street. The mobile transmitter and mobile receiver are equipped with massive MIMO antenna array; therefore, three-dimensional spherical antenna arrays are introduced in the model, rather than two-dimensional planar wavefront assumption used in traditional MIMO channel models. The closed expressions for the probability density functions of the azimuth angle of departure, the elevation angle of departure, the azimuth angle of arrival, and elevation angle of arrival are first deduced by analyzing the proposed V2V channel model. We then analyze the temporal and spatial cross-correlation functions corresponding to the single- and doublebounced scattering propagation paths. Comparisons with previously reported results are used to validate the applicability and feasibility of the proposed model.

Elevation Beamforming With Full Dimension MIMO Architectures in 5G Systems: A Tutorial

Full dimension (FD) multiple-input multiple-output (MIMO) technology has attracted substantial research attention from both wireless industry and academia in the last few years as a promising technique for next-generation wireless communication networks. FD-MIMO scenarios utilize a planar 2-D active antenna system (AAS) that not only allows a large number of antenna elements to be placed within feasible base station (BS) form factors, but also provides the ability of adaptive electronic beam control over both the elevation and the traditional azimuth dimensions. This paper presents a tutorial on elevation beamforming analysis for cellular networks utilizing FD massive MIMO antenna arrays. In contrast to existing works that focus on the standardization of FD-MIMO in the 3rd generation partnership project (3GPP), this tutorial is distinguished by its depth with respect to the theoretical aspects of antenna array and 3-D channel modeling. In an attempt to bridge the gap between industry and academia, this preliminary tutorial introduces the relevant array and transceiver architecture designs proposed in the 3GPP Release 13 that enable elevation beamforming. Then it presents and compares two different 3-D channel modeling approaches that can be utilized for the performance analysis of elevation beamforming techniques. The spatial correlation in FD-MIMO arrays is characterized and compared based on both channel modeling approaches and some insights into the impact of different channel and array parameters on the correlation are drawn. All these aspects are put together to provide a mathematical framework for the design of elevation beamforming schemes in single-cell and multi-cell scenarios. Simulation examples associated with comparisons and discussions are also presented. To this end, this paper highlights the state-of-the-art research and points out future research directions.

A Virtual Over-the-Air Method for 5G Massive MIMO Base Station Testing With Flexible Virtual Probes

Massive multiple-input-multiple-output (MIMO) is known as a large-scale antenna technology and has been enabled for the fifth generation (5G) mobile communication systems. The over-the-air (OTA) testing of massive MIMO antenna system has attracted a lot of attention in terms of evaluating the radio performance of a 5G base station (BS). As a promising OTA test methodology, the sectored multi-probe anechoic chamber (MPAC) setup is employed for the performance testing of massive MIMO BS. However, the system cost and installation are still an issue to be considered in practice (e.g., the anechoic chamber and multiple probes), though it can accurately reconstruct the flexible propagation channels by channel emulation methods. This paper proposes a virtual OTA test framework for the performance testing of massive MIMO BS on the basis of MPAC setups. As an alternative, the proposed virtual OTA test system adopting the concept of virtual probes solves the inconveniences and limitations of the actual probe installation in MPAC setups. The BS array responses to the actual probes of MPAC setups are generated in a phase matrix for the virtual probes. First, in this paper, the system description of virtual OTA testing is given. Then, the emulation method of spatial clusters is presented for the virtual OTA testing. Finally, simulations are performed with good channel emulation accuracy.

A Three-Port Polarization and Pattern Diversity Ring Antenna

In this letter, a novel design of a three-port antenna exhibiting pattern and polarization diversity characteristics is proposed. The radiating element of the proposed antenna comprises a ring loaded with periodical interdigital capacitors. The selective excitation of the three ports of the antenna enables omnidirectional and dual-polarized broadside radiation patterns in an overlapping bandwidth of 73 MHz (2.574 $-$ 2.647 GHz). The mutual coupling between any set of the two ports in the three-port antenna system is less than $-$ 20 dB. Six elements of the three-port ring antenna are arranged along the edges of a hexagon to generate 12 distinct beams (six dual-polarized broadside beams and six omnidirectional beams). Low mutual coupling and uncorrelated radiation patterns between the adjacent ports make the proposed three-port ring antenna a good candidate for use as an antenna element in massive multiple-input–multiple-output antenna systems for 5G applications.

Massive MIMO Antenna Selection: Switching Architectures, Capacity Bounds, and Optimal Antenna Selection Algorithms

Antenna selection is a multiple-input multiple-output (MIMO) technology, which uses radio frequency (RF) switches to select a good subset of antennas. Antenna selection can alleviate the requirement on the number of RF transceivers, thus being attractive for massive MIMO systems. In massive MIMO antenna selection systems, RF switching architectures need to be carefully considered. In this paper, we examine two switching architectures, i.e., full-array and sub-array. By assuming independent and identically distributed Rayleigh flat fading channels, we use asymptotic theory on order statistics to derive the asymptotic upper capacity bounds of massive MIMO channels with antenna selection for the both switching architectures in the large-scale limit. We also use the derived bounds to further derive the upper bounds of the ergodic achievable spectral efficiency considering the channel state information (CSI) acquisition. It is also showed that the ergodic capacity of sub-array antenna selection system scales no faster than double logarithmic rate. In addition, optimal antenna selection algorithms based on branch-and-bound are proposed for both switching architectures. Our results show that the derived asymptotic bounds are effective and also apply to the finite-dimensional MIMO. The CSI acquisition is one of the main limits for the massive MIMO antenna selection systems in the time-variant channels. The proposed optimal antenna selection algorithms are much faster than the exhaustive-search-based antenna selection, e.g., 1000 × speedup observed in the large-scale system. Interestingly, the full-array and sub-array systems have very close performance, which is validated by their exact capacities and their close upper bounds on capacity.

Massive MIMO antenna selection algorithms based on iterative swapping

Based on capacity maximisation metric, an iterative swapping antenna selection method is proposed for massive multiple-input multiple-output (MIMO). Then a ‘local’ swapping algorithm is proposed for massive MIMO antenna selection, which swaps the target antennas ‘locally’. A ‘global’ swapping algorithm is also proposed to reduce the computational complexity, which exchanges the target antennas ‘globally’. Both of the proposed algorithms are near optimal, due to the consideration of the influences of the unselected antennas and the selected ones on the antenna to be selected. Last, numerical simulations are provided to validate the proposed algorithms.

Toward an Efficient C-RAN Optical Fronthaul for the Future Networks: A Tutorial on Technologies, Requirements, Challenges, and Solutions

The exponential traffic growth, demand for high speed wireless data communications, as well as incessant deployment of innovative wireless technologies, services, and applications, have put considerable pressure on the mobile network operators (MNOs). Consequently, cellular access network performance in terms of capacity, quality of service, and network coverage needs further considerations. In order to address the challenges, MNOs, as well as equipment vendors, have given significant attention to the small-cell schemes based on cloud radio access network (C-RAN). This is due to its beneficial features in terms of performance optimization, cost-effectiveness, easier infrastructure deployment, and network management. Nevertheless, the C-RAN architecture imposes stringent requirements on the fronthaul link for seamless connectivity. Digital radio over fiber-based common public radio interface (CPRI) is the fundamental means of distributing baseband samples in the C-RAN fronthaul. However, optical links which are based on CPRI have bandwidth and flexibility limitations. Therefore, these limitations might constrain or make them impractical for the next generation mobile systems which are envisaged not only to support carrier aggregation and multi-band but also envisioned to integrate technologies like millimeter-wave (mm-wave) and massive multiple-input multiple-output antennas into the base stations. In this paper, we present comprehensive tutorial on technologies, requirements, architectures, challenges, and proffer potential solutions on means of achieving an efficient C-RAN optical fronthaul for the next-generation network such as the fifth generation network and beyond. A number of viable fronthauling technologies such as mm-wave and wireless fidelity are considered and this paper mainly focuses on optical technologies such as optical fiber and free-space optical. We also present feasible means of reducing the system complexity, cost, bandwidth requirement, and latency in the fronthaul. Furthermore, means of achieving the goal of green communication networks through reduction in the power consumption by the system are considered.