Massive MIMO Techniques Research Articles

Enhancement of Rural Connectivity by Recycling TV Towers with Massive MIMO Techniques

Nowadays, the digital divide is one of the major issues facing the global community. Around 3 billion people worldwide are still not-connected or under-connected. In this article, we investigate the use of TV towers with multi user (MU) massive multiple input multiple output (mMIMO) techniques to offer connectivity in rural areas. Specifically, the coverage range is assessed for a MU mMIMO base station (BS) mounted on a high tower as a TV tower, and compared with a legacy mMIMO BS. The obtained results show that one high tower BS can cover an area at least 25 times larger than the area covered by a legacy BS. This is of high interest as recycling TV towers can enhance rural connectivity with low expenditures. We apply the proposed solution to a realistic case study in an Ethiopian rural area, based on population densities and locations of current BS and TV towers. Our study shows that a high number of people can be covered by existing TV towers. Non-technological challenges and additional possible solutions to enhance rural connectivity are also discussed.

Resource optimization of MIMO using neural network for 5G communication

The principal objective of this work is to optimize the resources of massive MIMO techniques by an application of a neural network algorithm in order to reduce the manufacturing cost of 5G technology within the wireless peripheries of tropical regions. For plenty of annual precipitation in the tropical regions, the radio signals of these areas get attenuated in communicating any message i.e. signal fading occurs. Various diversity techniques have been used for diminishing signal fading in these tropical areas. MIMO technique is a spatial diversity technique used to minimize signal fading. In this paper, 1 × 1 to 256 × 256 MIMO techniques have been designed with the help of MATLAB and Xilinx system generator, and an 8 × 8 MIMO has been implemented in Xilinx Kintex7 FPGA. A CMOS logic technique has been incorporated to optimize the resources of different MIMO techniques, and for this purpose a two-layer feed forward neural network algorithm has been adopted. A comparison of the theoretical values obtained from the design by using both Xilinx system generator and Simulink with the values derived from the design by using CMOS logic gates, has been displayed in this paper. For neural network optimization, three types of training algorithms have been applied.

A Novel Meander Line Metamaterial Absorber Operating at 24 GHz and 28 GHz for the 5G Applications

Fifth generation (5G) communication systems deploy a massive MIMO technique to enhance gain and spatial multiplexing in arrays of 16 to 128 antennas. In these arrays, it is critical to isolate the adjacent antennas to prevent unwanted interaction between them. Fifth generation absorbers, in this regard, are the recent interest of many researchers nowadays. The authors present a dual-band novel metamaterial-based 5G absorber. The absorber operates at 24 GHz and 28 GHz and is composed of symmetric meander lines connected through a transmission line. An analytical model used to calculate the total number of required meander lines to design the absorber is delineated. The analytical model is based on the total inductance offered by the meander line structure in an impedance-matched electronic circuit. The proposed absorber works on the principal of resonance and absorbs two 5G bands (24 GHz and 28 GHz). A complete angular stability analysis was carried out prior to experiments for both transverse electric (TE) and transverse magnetic (TM) polarizations. Further, the resonance conditions are altered by changing the substrate thickness and incidence angle of the incident fields to demonstrate the functionality of the absorber. The comparison between simulated and measured results shows that such an absorber would be a strong candidate for the absorption in millimetre-wave array antennas, where elements are placed in proximity within compact 5G devices.

Channel Estimation and Prediction in a Pilot-Less Massive MIMO TDD Using Non-Coherent DMPSK

A novel time division duplex massive MIMO technique is proposed based on performing a pilot-less channel estimation in the uplink (UL) utilizing reconstructed differentially encoded data. Spatial multiplexing and differentially encoded data is applied both in the UL and in the downlink (DL). In this system, a reference signal is the first one of the differentially encoded streams in the UL and DL, and the pilots for data estimation are avoided while maintaining spatial multiplexing capabilities. To improve the channel estimation we propose to use a linear Wiener filter and we also propose different symbols placing strategies in an OFDM grid. We also propose a detection improvement of the UL data utilizing the predicted channels. We perform an analysis of the MSE of the blind channel estimation using the differentially encoded data and analyze the symbol-error-rate for both the UL and the DL when channel aging is considered. The analysis is corroborated via numerical results and the proposed scheme is shown to outperform its pilot-based counterpart.

Surveying on MIMO Technology for Future Wireless Communication

Massive MIMO is an extension of traditional MIMO with the exception that the BSs in massive MIMO are equipped with large number of antennas, usually hundred or more. This large number of antennas provide several positive advantages towards wireless communication with respect to increasing volume of data traffic. Each antenna is capable of serving multiple users simultaneously leading to reduction in power consumption as well as data rate amplification. Additionally, narrow and more focused beams are pointed to individual user devices located at the cell edge thereby upgrading of downlink signal quality. Using massive MIMO technique also increases reliability of the links, reduces noise effects, and mitigates and interference. With increasing number of users gets service, the throughput of the system also increases.

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

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.

Sum-rate optimization for NOMA based two-tier hetnets with massive MIMO enabled wireless backhauling

In this paper, massive MIMO and NOMA techniques are jointly considered in a two tier heterogeneous network for accommodating huge traffic. In addition, full duplex communication is used at SBS to enhance system performance. First, SINR and rate equations are modeled while considering imperfect channel state information and zero-forcing beamforming. In the proposed framework, both macro base station and small cell base station can serve multiple users by using NOMA. Since, existing literature mainly focuses on orthogonal multiple access (OMA) based UA schemes, it is necessary to re-design user association (UA) schemes for NOMA. Hence, based on the proposed framework, a joint UA and power allocation (PA) optimization problem is designed with the perspective of optimizing the sum-rate of the system while accounting for quality of service and backhaul constraints. Since, the initially formulated problem is non-convex, a distributive algorithm is propounded where a joint problem is separated into two convex subproblems (viz., UA and PA). Furthermore, the complexity of the proposed algorithm is examined and Jain’s fairness index is measured. Simulation results demonstrate the effectiveness of the proposed algorithm by comparing with optimal solution and other base-line algorithms.

Comparative Study of Efficiency Enhancement Technologies in 5G Networks - A survey

Mobile communication technologies are tremendously grown in the last few years. With the advent of the fifth generation of wireless networks, and with millions of base stations and billions of connected devices, the need for spectral and energy-efficient system design will be more convincing. In this paper, the evolution of mobile communication networks starting from first-generation to the fifth generation with comparative studies are first introduced. Then, summarizing the recent research initiatives towards the next generation, 5G, evolution. The main requirements of 5G networks and emerging technologies are highlighted. Furthermore, an overview of several technologies that might be used to achieve the 5G requirements including Massive-MIMO, Millimetre-waves, beamforming, full-duplex, and Small-Cells are explained. Finally, a comparative analysis survey of Spectral Efficiency (SE) and Energy-Efficiency (EE) based Massive MIMO techniques is introduced as a key contribution of this review article. Good trade-off conditions between EE and SE technologies based on various algorithms are explained with comparative analysis.

Massive MIMO Transmission for LEO Satellite Communications

Low earth orbit (LEO) satellite communications are expected to be incorporated in future wireless networks, in particular 5G and beyond networks, to provide global wireless access with enhanced data rates. Massive MIMO techniques, though widely used in terrestrial communication systems, have not been applied to LEO satellite communication systems. In this paper, we propose a massive MIMO transmission scheme with full frequency reuse (FFR) for LEO satellite communication systems and exploit statistical channel state information (sCSI) to address the difficulty of obtaining instantaneous CSI (iCSI) at the transmitter. We first establish the massive MIMO channel model for LEO satellite communications and simplify the transmission designs via performing Doppler and delay compensations at user terminals (UTs). Then, we develop the low-complexity sCSI based downlink (DL) precoder and uplink (UL) receiver in closed-form, aiming to maximize the average signal-to-leakage-plus-noise ratio (ASLNR) and the average signal-to-interference-plus-noise ratio (ASINR), respectively. It is shown that the DL ASLNRs and UL ASINRs of all UTs reach their upper bounds under some channel condition. Motivated by this, we propose a space angle based user grouping (SAUG) algorithm to schedule the served UTs into different groups, where each group of UTs use the same time and frequency resource. The proposed algorithm is asymptotically optimal in the sense that the lower and upper bounds of the achievable rate coincide when the number of satellite antennas or UT groups is sufficiently large. Numerical results demonstrate that the proposed massive MIMO transmission scheme with FFR significantly enhances the data rate of LEO satellite communication systems. Notably, the proposed sCSI based precoder and receiver achieve the similar performance with the iCSI based ones that are often infeasible in practice.

A Methodology to Characterize Power Control Systems for Limiting Exposure to Electromagnetic Fields Generated by Massive MIMO Antennas

The fifth-generation (5G) New Radio (NR) cellular network has been launched recently. The assignment of new spectrum bands and the widespread use of Massive MIMO (MaMIMO) and beamforming techniques for better radio coverage are two major features of the new architecture. They imply both opportunities and challenges, one of the most daring one among the latter ones is the research for methods to assess human exposure to electromagnetic fields radiated by the base stations. The long-term time-varying behavior and spatial multiplexing feature of the MaMIMO antennas, along with the radio resource utilization and adoption of Time-Division Duplexing (TDD), requires that the assessment of exposure to electromagnetic fields radiated by 5G systems is based on a statistical approach that relies on the space and time distribution of the radiated power. That, in turn, is determined through simulations based on the actual maximum transmitted power – defined as the 95th percentile of the empirical distribution obtained from historical data of radiated power – rather than on the nominal one. To ensure that exposure limits are never exceeded, a monitoring and control system (usually referred to as Power Lock (PL)) that limits the transmitted power can be used. In this paper we propose a methodology, independent from the specific technical solution implemented by the manufacturer, to characterize such control systems and determine their capability to limit the average power transmitted over a given time interval to a value that keeps the corresponding average exposure to electromagnetic fields below a specified value. Experimental results show the effectiveness of the methodology and that it can also be used to identify when the PL interacts with the higher levels of the MaMIMO system architecture.

Current Status and Directions of IEEE 802.11be, the Future Wi-Fi 7

While customers rivet their eyes on Wi-Fi 6, in the bowels of the IEEE 802.11 Working Group that creates Wi-Fi standards, the next generation Wi-Fi is being developed. At the very first sight, the new IEEE 802.11be amendment to the Wi-Fi standard is nothing but scaled 11ax with doubled bandwidth and the increased number of spatial streams, which together provide data rates as high as 40 Gbps. A bit deeper dive into the 802.11 activities reveals that 11be will support real-time applications. In reality, 11be introduces many more revolutionary changes to Wi-Fi, which will form a basement for further Wi-Fi evolution. Although by now (May 2020), the development process is at the very early phase without any draft specification, the analysis of the discussion in the 802.11 Working Group gives insights into the main innovations of 11be. In addition to the ones above, they include native multi-link operation, channel sounding optimization that opens the door for massive MIMO, advanced PHY and MAC techniques, the cooperation of various access points. The paper analyzes hundreds of features proposed for the new technology, focusing on the open problems that can be solved by the researchers who want to contribute to the development of 802.11be.

Downlink user association and uplink scheduling for energy harvesting users in software-defined mobile networks

In this paper we consider a heterogeneous network which consists of a macro base station and some pico base stations utilizing massive MIMO and MIMO techniques, respectively. A central software-defined mobile network (SDMN) controller is adopted in order to provide user association and energy scheduling. The users are considered battery limited and are capable of simultaneous wireless information and power transfer (SWIPT) in order to harvest energy and address the energy shortage issue. These users harvest energy from the received signals in the downlink and consume it via their uplink communications. This paper deals with the downlink user association by jointly optimizing the overall sum-rate of the network and the harvested energy by introducing an appropriate utility function. In this regard, the optimum user association and power splitting factor for each user are calculated via the downlink optimization stage. Then, the process of uplink scheduling is defined as choosing the best users in each time epoch to transfer data as well as optimizing their transmit power by solving Lyapunov drift-plus-penalty function. Simulation results are provided in order to confirm the optimality of the proposed algorithm in comparison with the previous user association and uplink scheduling approaches in terms of providing fairness and battery management among users.

Fundamentals of Massive MIMO (Marzetta, T., et al; 2016) [Book Reviews

MIMO or multiple-input multiple-output technology is the use of multiple antennas in wireless networks to increase the throughput of such a network to solve the current limitations of the electromagnetic spectrum and is the only viable approach for substantial improvement of spectral efficiency. MIMO technology is classified into one of three categories whose development occurred at different non-overlapping time intervals: point-to-point MIMO, multiuser MIMO, and massive MIMO. In this book, engineering principles of massive MIMO are examined and explained, which arguably will be the ultimate embodiment of MIMO technology. The book explains different technologies of MIMO and their important differences through key topics in multi-cell systems, such as propagation modeling, multiplexing and demultiplexing, channel estimation, power control, performance evaluation, and analyses, and development of advanced massive MIMO techniques and algorithms to design complex wireless communication systems. The book covers a lot of technologies related to MIMO and their design. It offers a detailed picture of wireless networks that implement multiple inputs and multiple outputs, and it offers a great deal of knowledge in how to design and implement such networks and how to measure their performance and efficiency. This book also has plenty of examples and offers discussions at the end of each chapter related to the subject.

Optimal Low‐Power Design of a Multicell Multiuser Massive MIMO System at 3.7 GHz for 5G Wireless Networks

Massive MIMO techniques are expected to deliver significant performance gains for the future wireless communication networks by improving the spectral and the energy efficiencies. In this paper, we propose a method to optimize the positions, the coverage, and the energy consumption of the massive MIMO base stations within a suburban area in Ghent, Belgium, while meeting the low power requirements. The results reveal that massive MIMO provides better performances for the crowded scenario where users’ mobility is limited. With 256 antennas, a massive MIMO base station can simultaneously multiplex 18 users at the same time‐frequency resource while consuming 8 times less power and providing 200 times more capacity than a 4G reference network for the same coverage. Moreover, a pilot reuse pattern of 3 is recommended in a multiuser multicell environment to obtain a good tradeoff between the high spectral efficiency and the low power requirement.

Functional Split of Zero-Forcing Based Massive MIMO for Fronthaul Load Reduction

The evolution towards centralized radio access network (C-RAN) for 5G is driven by the need for improved network performance and reduced total-cost-of-ownership (TCO). In C-RAN, physically separated remote radio units (RRUs) and baseband units (BBUs) are connected via fronthaul (FH) links, which are capacity constrained. When base-station antennas are upgraded to support massive MIMO techniques, an intra PHY split between RRU and BBU becomes favorable to avoid the dramatic rate growth on the FH links. In this paper, we present a new uplink functional split alternative that decomposes the massive MIMO processing, on the basis of zero-forcing (ZF) equalization, into two phases: dimension-reduction phase and interference cancellation phase, which are implemented in RRU and BBU respectively. Compared with the traditional C-RAN architecture having all baseband processing in the BBU, the new scheme largely alleviates the FH load by reducing the number of FH streams to be equal to the number of MIMO user layers. Compared with an existing split that places all MIMO processing in RRU, the new scheme reduces the RRU complexity without compromising the post-processing performances.

A comprehensive survey: Small cell meets massive MIMO

The deluge of huge data demanding applications has imposed a challenge for next generation cellular system to support high data rate with reduced energy consumption besides ensuring good quality of service. Massive MIMO and small cells are the foremost technologies to address such challenges. Massive MIMO technique refers to deploying a very large number of antennas at the base station, and thus, improving energy efficiency and spectral efficiency of wireless networks. Small cell provides high data rate and good coverage with reduced transmit power by decreasing the distance between base station and user. This paper surveys state of the art of massive MIMO technique with small cell network. First, we discuss fundamental background for massive MIMO. Then, performance metrics and modeling tools for system analysis are studied. Next, details of enabling technologies to massive MIMO small cell network are stated in the paper. Finally, the paper highlights future challenges and research problems.

On the Multi-User Multi-Cell Massive Spatial Modulation Uplink: How Many Antennas for Each User?

Massive spatial modulation aided multiple-input multiple-output (SM-MIMO) systems have recently been proposed as a novel combination of spatial modulation (SM) and of conventional massive MIMO, where the base station (BS) is equipped with a large number of antennas and simultaneously serves multiple user equipment (UE) that employ SM for their uplink transmission. Since the massive SM-MIMO concept combines the benefits of both the SM and massive MIMO techniques, it has recently attracted substantial research interest. In this paper, we study the achievable uplink spectral efficiency (SE) of a multi-cell massive SM-MIMO system, and derive closed-form expressions to asymptotically lower-bound the SE yielded by two linear BS combining schemes, including maximum ratio (MR) combining and zero forcing (ZF) combining, when a sufficiently large number of BS antennas are equipped. The derivation takes into account the impact of transmitter spatial correlations, of imperfect channel estimations, of user-specific power controls and of different pilot reuse factors. The proposed asymptotic bounds are shown to be tight, even when the scale of BS antennas is limited. The new SE results facilitate a system-level investigation of the optimal number of uplink transmit antennas (TAs) $N$ with respect to SE maximization. Explicitly, we provide theoretical insights on the SE of massive SM-MIMO systems. Furthermore, we demonstrate that massive SM-MIMO systems are capable of outperforming the SE of conventional massive MIMOs relying on single-TA UEs.

Analysis and Evaluation of Performance Gains and Tradeoffs for Massive MIMO Systems

Massive MIMO technique offers significant performance gains for the future of wireless communications via improving the spectral efficiency, energy efficiency and the channel quality with simple linear processing such as maximum-ratio transmission (MRT) or zero-forcing (ZF) by providing each user a large degree of freedom. In this paper, the system performance gains are studied in a multi-cell downlink massive MIMO system under the main considerations such as perfect channel estimation, imperfect channel estimation and the effect of interference among cells due to pilot sequences contamination. Then, mathematical expressions are derived for these gains i.e., spatial multiplexing gain, array gain and spatial diversity gain. After that, essential tradeoffs among these gains are considered under the effect of non-orthogonal interference, these tradeoffs are: spatial diversity gain vs. spatial multiplexing gain and array gain vs. spatial multiplexing gain. Simulation results show that the unbounded number of base station antennas boosts the array gain through concentrating the energy to spatial directions where users are sited, hence diminishing loss in array gain due to pilot contamination. The simulation results reveal also that massive MIMO strengthens the spatial multiplexing gain through increasing the number of served users via the same system resources in spite the effect of inter-cell interference. Finally, the spatial diversity gain is measured in term of outage probability and the simulation results show that raising the number of antennas will improve the outage probability. Meanwhile increasing the number of served users will lead to degrade the outage probability per user due to non-orthogonal interference from other cells.

Future railway services-oriented mobile communications network

The future development of the railway is highly desired to evolve into a new era where infrastructure, trains, travelers, and goods will be increasingly interconnected to provide high comfort, with optimized door-to-door mobility at higher safety. For this vision, it is required to realize seamless high data rate wireless connectivity for railways. To improve the safety and comfort of future railways, wireless communications for railways are required to evolve from only voice and traditional train control signaling services to various high data rate services including critical high-definition (HD) video and other more bandwidth-intensive passenger services, such as onboard and wayside HD video surveillance, onboard real-time high data rate services, train multimedia dispatching video streaming, railway mobile ticketing, and the Internet of Things for railways. Corresponding mobile communications network architecture under various railway scenarios including inter-car, intra-car, inside station, train-to-infrastructure and infrastructure- to-infrastructure are proposed in this article. Wireless coverage based on massive MIMO for railway stations and train cars is proposed to fulfill the requirement of high-data-rate and high spectrum efficiency. The technical challenges brought by the massive MIMO technique are discussed as well.