Multiple-input Multiple-output Channel Characteristics Research Articles

Measurements and Characteristics Analysis of 6G Ultra-Massive MIMO Wireless Channels With Different Antenna Configurations and Scenarios

In this paper, ultra-massive multiple-input multiple-output (MIMO) channel measurements at 5.3 GHz are conducted, including different antenna array configurations and different measurement scenarios. The antenna array configurations include uniform linear array (ULA) and distributed uniform linear array (DULA). The measurement scenarios include single-user fixed-to-fixed (F2F), multi-user F2F, and single-user fixed-to-mobile (F2M) measurement scenarios. The statistical properties of ultra-massive MIMO channels are studied, including delay power spectral density (DPSD), space cross-correlation function (SCCF), angle cross-correlation function (ACCF), frequency correlation function (FCF), root mean square (RMS) delay spread (DS), RMS angle spread (AS), singular value spread (SVS), scalar product (SP), level crossing rate (LCR), average fading duration (AFD), Doppler power spectral density (PSD), etc. The specific ultra-massive MIMO channel characteristics are investigated and validated by channel measurements, including spatial non-stationarity, spherical wavefront behavior, channel hardening, and sparse properties in the angle domain. In addition, channel capacities are investigated. The channel measurement results will be a great importance for ultra-massive MIMO communication system deployments.

Recent Advances of Ultramassive Multiple-Input, Multiple-Output Technologies: Realizing a Sixth-Generation Future in Spatial and Beam Domains

To explore the full potential of ultramassive multiple-input, multiple-output (MIMO) communication systems, it is fundamental to understand new ultramassive MIMO channel characteristics and establish pervasive channel models. On this basis, large-dimensional spatial-temporal transmission and random access technologies need to be investigated and evaluated for better practical implementation. First, this article reviews recent advances of ultramassive MIMO technologies in the traditional spatial domain, including wireless channel characterization and modeling, channel estimation, spatial multiplexing, and precoding. Second, considering the dramatic increase of base station (BS) antennas and access users in ultramassive MIMO systems, the confronted high-dimensional complexity and computing burden of these ultramassive MIMO technologies are indicated. To provide an efficient and systematic solution, the emerging tendency to transform related technologies from the traditional spatial domain to the beam domain is introduced. The utilities of large sparsity merit, reduced energy consumption, and improved usage of radio frequency (RF) chains in the beam domain channel are elaborated. Last, future challenges of ultramassive MIMO communication systems are discussed.

3-D Ray Launching MIMO Channel Geometric Estimation

The complete multiple-input–multiple-output (MIMO) channel simulation in deterministic techniques can be a computationally intensive task, due to the inherent scenario's complexity and number of antennas. The spatial coherence among MIMO elements is a reasonable assumption to approximate the channel from a single point simulation. In this letter, a novel method to incorporate a geometrical approximation of the MIMO channel into a three-dimensional ray launching (3D-RL) algorithm is presented. The method is antenna type independent and the orientation of the array is embedded in the antenna representation. Relevant information of the MIMO channel characteristics like the root mean square (rms) delay spread, the maximum delay spread, phase and channel capacity are obtained and compared with the full 3D-RL simulation of the entire MIMO array, achieving 93.4% reduction in computational time.

Three-Dimensional Geometry-Based Stochastic Channel Modeling for Intelligent Reflecting Surface-Assisted UAV MIMO Communications

In this letter, a three-dimensional (3D) geometry-based stochastic multiple-input multiple-output (MIMO) channel model for intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV) communications is proposed. The IRS is distributed on the surface of buildings to assist the UAV transmitter to reflect its signals to the receiver on the ground level and to improve the communication quality by passive beamforming at the IRS. In such a channel model, the signals transmitted from the UAV transmitter will first get scattered by the clusters between the UAV and IRS before arriving at the IRS, and subsequently arrive at the ground receiver. We separate this channel model into a subchannel model between the UAV and the IRS, as well as a subchannel model between the IRS and the receiver. Based on the derivations of complex channel coefficients for the above two subchannel models, we investigate the impact of IRS on the underlying propagation channel by studying the spatial cross-correlation functions (CCFs). Simulation results are provided to show the statistical propagation characteristics of the IRS-assisted UAV MIMO channels.

Impact of UAV Rotation on MIMO Channel Characterization for Air-to-Ground Communication Systems

Unmanned aerial vehicle (UAV) communications have been considered as one of the promising technologies to support numerous applications in the fifth and sixth generations wireless networks. A deep understanding of propagation channel is necessary for the design of wireless communication systems. A three-dimensional (3D) wideband non-stationary geometry-based stochastic model (GBSM) is proposed for UAV multiple-input multiple-output (MIMO) channels in this paper. The proposed GBSM considers the both line-of-sight (LoS) and non-LoS (NLoS) components in the transmission links from a UAV transmitter (Tx) to a ground receiver (Rx), the proposed 3D GBSM is used for the first time to investigate the impact of UAV rotation, which results in time-varying channel parameters and reflects the non-stationarity of channel. Based on the proposed model, we derive and study some significant statistical properties, including the transfer function, space-time-frequency correlation function, Doppler power spectrum, and quasi-stationary interval. Numerical results show that the UAV rotation has a significant impact on channel statistical properties and non-stationarity. It is found that, even for a low range of UAV rotations, channel correlations are significantly affected, and the time correlation gradually increases with the pitch angle of UAV. Finally, the impact of using directional antennas at Tx on channel characteristics is analyzed. It is found that the channel correlation with directional antenna is significantly increased compared with the results with omnidirectional antenna. These observations and conclusions can be used as a reference for the system design and performance analysis of UAV-MIMO communication systems.

Investigation of MIMO Channel Characteristics in Tunnel at 1.4725 and 6 GHz

AbstractIn recent years, high‐speed railway and subway are being built rapidly in China. Tunnel scenario is a major scenario in some of the high‐speed railways and most of the subways. Channel characteristic is the decisive condition of wireless communication system design in tunnel. The availability of multiple‐input multiple‐output (MIMO) in tunnel is an important issue in the next generation communication network. This paper presents results from a wideband measurement campaign at center frequency of 1.4725 and 6 GHz in a tunnel laboratory. The path loss, root‐mean‐square delay spread (RMS‐DS) characteristics by single‐input single‐output (SISO) measurement and the angle spread, channel matrix singular values, and MIMO capacity at various link distances by MIMO measurement are illustrated. and these provide insights for MIMO system deployment. And also, the threshold of singular value for channel matrix rank reduction is given.

Experimental Investigation of Millimeter-Wave MIMO Channel Characteristics in Tunnel

A 28 GHz millimeter-wave (mm-wave) propagation measurement campaign was performed to predict the multiple-input multiple-output (MIMO) channel performance in a tunnel environment. Two kinds of polarization configurations were studied in this paper. In order to overcome the serious path loss (PL) of mm-wave propagation, a high gain directional horn antenna was used in the measurements of tunnel environment. The measurement results and simulation results at same specific locations are compared. The result of comparison indicates that the simulation model matches the measurement well. Then the MIMO capacity at other locations of the tunnel can be predicted by the simulation model. Further-more, it is inferred that the antenna array elements of horizontally polarized configuration have higher capacity than the vertically polarized under the constant signal-to-noise ratio (SNR).

Compressive MIMO Beamforming of Data Collected in a Refractive Environment

AbstractThe phenomenon of ducting is caused by abnormal atmospheric refractivity patterns and is known to allow electromagnetic waves to propagate over the horizon with unusually low propagation loss. It is unknown what effect ducting has on multiple input multiple output (MIMO) channels, particularly its effect on multipath propagation in MIMO channels. A high‐accuracy angle‐of‐arrival and angle‐of‐departure estimation technique for MIMO communications, which we will refer to as compressive MIMO beamforming, was tested on simulated data then applied to experimental data taken from an over the horizon MIMO test bed located in a known ducting hot spot in Southern California. The multipath channel was estimated from the receiver data recorded over a period of 18 days, and an analysis was performed on the recorded data. The goal is to observe the evolution of the MIMO multipath channel as atmospheric ducts form and dissipate to gain some understanding of the behavior of channels in a refractive environment. This work is motivated by the idea that some multipath characteristics of MIMO channels within atmospheric ducts could yield important information about the duct.

Investigation of MIMO Channel Characteristics in a Two-Section Tunnel at 1.4725 GHz

This paper presents results from a wide band single-input–single-output (SISO) and 16 × 16 virtual multiple-input–multiple-output (MIMO) measurement campaign at a center frequency of 1.4725 GHz in a 100-meter long tunnel laboratory which is terminated by a vertical wall with a metallic door. The path loss, root-mean-square delay spread (RMS-DS) characteristics, and power delay profiles (PDPs) are described. In addition, we provide results for the MIMO channel amplitude matrix, which offers a new perspective in understanding MIMO characteristics in tunnel scenarios. Our measurement results are analyzed and compared to ray tracing simulations. The relationships among the angle spread, channel matrix singular values, and MIMO capacity at various link distances are illustrated, and these provide insights into MIMO system deployment.

Super-Resolution Sparse MIMO-OFDM Channel Estimation Based on Spatial and Temporal Correlations

This letter proposes a parametric sparse multiple input multiple output (MIMO)-OFDM channel estimation scheme based on the finite rate of innovation (FRI) theory, whereby super-resolution estimates of path delays with arbitrary values can be achieved. Meanwhile, both the spatial and temporal correlations of wireless MIMO channels are exploited to improve the accuracy of the channel estimation. For outdoor communication scenarios, where wireless channels are sparse in nature, path delays of different transmit-receive antenna pairs share a common sparse pattern due to the spatial correlation of MIMO channels. Meanwhile, the channel sparse pattern is nearly unchanged during several adjacent OFDM symbols due to the temporal correlation of MIMO channels. By simultaneously exploiting those MIMO channel characteristics, the proposed scheme performs better than existing state-of-the-art schemes. Furthermore, by joint processing of signals associated with different antennas, the pilot overhead can be reduced under the framework of the FRI theory.

MIMO Signal Processing for Mode-Division Multiplexing: An overview of channel models and signal processing architectures

We present the fundamentals of multiple-input, multiple-output (MIMO) signal processing for mode-division multiplexing (MDM) in multimode fiber (MMF). As an introduction, we review current long-haul optical transmission systems and how continued traffic growth motivates study of new methods to increase transmission capacity per fiber. We describe the key characteristics of MIMO channels in MMF, contrasting these with wireless MIMO channels. We review MMF channel models, the statistics derived from them, and their implications for MDM system performance and complexity. We show that optimizing performance and complexity requires management of channel parameters-particularly group delay (GD) spread and mode-dependent loss and gain-by design of transmission fibers and optical amplifiers, and by control of mode coupling along the link. We describe a family of fibers optimized for low GD spread, which decreases with an increasing number of modes. We compare the performance and complexity of candidate MIMO signal processing architectures in a representative long-haul system design, and show that programmable frequency-domain equalization (FDE) of chromatic dispersion (CD) and adaptive FDE of modal dispersion (MD) is an attractive combination. We review two major algorithms for adaptive FDE of MD-least mean squares (LMS) and recursive least squares (RLS)-and analyze their complexity, throughput efficiency, and convergence time. We demonstrate that, with careful physical link design and judicious choice of signal processing architectures, it is possible to overcome MIMO signal processing challenges in MDM systems.

A Simplified MIMO Channel Characteristics Evaluation Scheme Based on Ray Tracing and Its Application to Indoor Radio Systems

In this letter, we propose a method of propagation characteristics analysis that enables simplified assessment of the transmission characteristics of multiple-input–multiple-output (MIMO) communication in indoor environments and assess its accuracy. In the proposed method, ray-tracing analysis is combined with a statistical method based on antenna array principles. Ray-tracing analysis is a rigorous method, but it is highly demanding in terms of computing time. Accordingly, in our method, ray tracing is only implemented between a pair of transmitting and receiving antenna points that are used as reference, after which statistical analysis is applied to estimate the properties of the surrounding areas. The results of an environment analysis of an empty room containing no objects produced via our method were compared to a room analyzed by ray tracing alone, from which we found our simplified method to be highly accurate within a range of several wavelengths from the receiving reference points.

Emulating Spatial Characteristics of MIMO Channels for OTA Testing

This paper discusses over-the-air (OTA) testing for multiple-input multiple-output (MIMO) capable terminals with emphasis on channel spatial characteristics emulation. A novel technique to obtain optimum power weights for the OTA probes based on convex optimization is proposed. The proposed technique emulates spatial correlation as well as introduces constraints on the maximum deviation between the target power azimuth spectrum (PAS) and the emulated PAS in terms of mean angle of arrival (AoA) and azimuth spread (AS). Simulation results show that the proposed emulation technique presents better performance compared with existing techniques in the literature. This improvement is further demonstrated by measurement results in a practical MIMO OTA setup.

Optimal Spectrum Sharing in MIMO Cognitive Radio Networks via Semidefinite Programming

In cognitive radio (CR) networks with multiple-input multiple-output (MIMO) links, secondary users (SUs) can exploit holes in the space domain to access the spectrum allocated to a primary system. However, they need to suppress the interference caused to primary users (PUs), as the secondary system should be transparent to the primary system. In this paper, we study the optimal secondary-link beamforming pattern that balances between the SU's throughput and the interference it causes to PUs. In particular, we aim to maximize the throughput of the SU, while keeping the interference temperature at the primary receivers below a certain threshold. Unlike traditional MIMO systems, SUs may not have the luxury of knowing the channel state information (CSI) on the links to PUs. This presents a key challenge for a secondary transmitter to steer interference away from primary receivers. In this paper, we consider three scenarios, namely when the secondary transmitter has complete, partial, or no knowledge about the channels to the primary receivers. In particular, when complete CSI is not available, the interference-temperature constraints are to be satisfied with high probability, thus resulting in chance constraints that are typically hard to deal with. Our contribution is fourfold. First, by analyzing the distributional characteristics of MIMO channels, we propose a unified homogeneous quadratically constrained quadratic program (QCQP) formulation that can be applied to all three scenarios, in which different levels of CSI knowledge give rise to either deterministic or probabilistic interference-temperature constraints. The homogeneous QCQP formulation, though non-convex, is amenable to semidefinite programming (SDP) relaxation methods. Secondly, we show that the SDP relaxation admits no gap when the number of primary links is no larger than two. A polynomial-time algorithm is presented to compute the optimal solution to the QCQP problem efficiently. Thirdly, we propose a randomized polynomial-time algorithm for constructing a near-optimal solution to the QCQP problem when there are more than two primary links. Finally, we show that when the secondary transmitter has no CSI on the links to primary receivers, the optimal solution to the QCQP problem can be found by a simple matrix eigenvalue-eigenvector computation, which can be done much more efficiently than solving the QCQP directly.

Design and Analysis of a Multiple-Input Receiver for Mimo Wireless Applications

In this article, we present multiple-input receiver architecture for MIMO (Multiple-Input Multiple-Output) wireless communication applications. The proposed implementation is provided by a defined number of identical receiver units that are fed by a RF modulated signal on specific carrier frequency, power strength and initial phase. These units carry out the corresponding amplification, filtering and demodulation procedures. Details on design and implementation of this Printed-Circuit-Board are introduced and further discussed. Experimental results are also presented, allowing the validation of investigation on the performance of the current receiver architecture. Besides, these measurements indicate that the proposed device, combining with a suitable antenna array, provides a versatile receiver platform for baseband signal processing. The incoming RF modulated signals have frequencies on the range of 2.4 GHz, several phases, magnitudes and modulation modes. From these, it seems that the proposed receiver implementation supports MIMO communication and multiple port channel characterization applications at 2.4 GHz ISM (Industrial, Scientific and Medical) band.

Wideband MIMO channel characterization in TV studios and inside buildings in the 2.2–2.5 GHz frequency band

Multiple input multiple output (MIMO) measurements were performed with a chirp sounder with a switched antenna array at the transmitter and eight parallel receiver channels with 96‐MHz bandwidth at 2.25 GHz in TV studios and 240‐MHz bandwidth at 2.38 GHz inside buildings. MIMO capacity was estimated from the data with linear and circular arrays with array sizes 2 by 2, 4 by 4, and 6 by 8. Mean capacity estimates for 30‐dB signal‐to‐noise ratio for both line of sight and obstructed line of sight were on the order of 11–31 b/s/Hz for the 2 by 2 to 4 by 4 antenna configurations and for the 6 by 8 directional antenna measurements a median capacity of 50 b/s/Hz. This is an increase of 20 b/s/Hz from the 4 by 4 omnidirectional antenna array indicating diversity gain as well as an increase due to the number of antennas.

Sensitivity of the MIMO Channel Characterization to the Modeling of the Environment

An important factor in electromagnetic wave propagation simulation, performed by a 3D ray-tracing method is the modeling of the environment. Results being sensitive to descriptive accuracy, this paper presents a study on the effect of indoor environment modeling precision on multiple input multiple output (MIMO) channel characterization. In order to give some diversity to the results, the investigation takes into account two unfurnished indoor environments. The first environment investigated is the entrance hall of a building at the University of Poitiers, while the second is a more confined environment and is represented by the first floor of the authors' laboratory. For these two indoor environments, four levels of description are proposed in order to establish the geometrical and electrical modeling impact on MIMO channel characterization. Results are obtained by analyzing the capacity, variation in correlation, multipath richness and eigenvalues in relation to the polarization, the presence of line-of-sight (LOS) or non-LOS (NLOS) configurations. The effects of the spacing between antennas and the number of transmitter and receiver antennas are also investigated.

Frequency Dependent Indoor MIMO Channel Characterisation between 2 and 12 GHz Based on Full Spatial Correlation Matrices

The integration of wideband and multiple-input multiple-output (MIMO) radio technologies represents a powerful tool for different wireless communication standards. In the test process of these systems, new strategies for MIMO channel modelling and characterisation are necessary in order to investigate how the frequency band and the bandwidth affect the system performance. In this paper, a MIMO channel experimental characterisation based on full spatial correlation (FSC) MIMO matrices estimated from frequency domain measurements is presented. Measurements performed between 2 and 12 GHz in a stationary office scenario in both line-of-sight (LOS) and non-line-of-sight (NLOS) conditions are considered. Results show frequency dependency on the experimental MIMO channel characteristics under a high SNR regime, equal electric separation between array elements and isolation of the path loss effect. The ergodic and 1% outage capacities were reduced while the central frequency increases for different array configurations. Remarkable changes on the magnitude of the spatial correlation coefficients and on the MIMO system eigenvalues were observed for different band frequencies.

New Closed-Form of the Largest Eigenvalue PDF for Max-SNR MIMO System Performances

Multiple-input multiple-output (MIMO) maxi-mum-SNR (max-SNR) system employs the maximum ratio combiner (MRC) at the receiver side and the maximum ratio transmitter (MRT) at the transmitter side. Its performances highly depend on MIMO channel characteristics, which vary according to both the number of antennas and their distribution between the transmitter and receiver sides. By using the decomposition of the ordered Wishart distribution in the uncorrelated Rayleigh case, we derived a closed-form expression of the largest eigenvalue probability density function (PDF). The final result yields to an expression form of the PDF where polynomials are multiplied by exponentials; it is worth underlining that, though this form had been previously observed for given couples of antennas, to date no formally-written closed-form was available in the literature for an arbitrary couple. Then, this new expression permits one to quickly and easily get the well known largest eigenvalue PDF and use it to determine the binary error probability (BEP) of the max-SNR.

Empirical analysis of a 2 x 2 MIMO channel in outdoor-indoor scenarios for BFWA applications

The unquestionable advantages of multiple-input multiple-output (MIMO) systems are having a strong influence on the development of new wireless systems, both in wireless local-area networks (WLANs), and in those designed to offer broadband fixed wireless access (BFWA) services in wireless metropolitan-area networks (WMANs). The MIMO channel characterization in different environments and for different operating frequency bands is a crucial factor in the design of new systems and standards, and for adequate planning of existing systems. This article makes two main contributions. First, the experimental characterization of a 2 times 2 MIMO channel at a frequency of 2.4 GHz in a canonical outdoor-indoor scenario is presented. The channel characterization performed includes the analysis of the spatial correlation between the MIMO system subchannels and its impact on the channel capacity. Second, on the basis of the capacity results obtained, a proposal is made for the use of a 2 times 2 MIMO system in outdoor-indoor scenarios for BFWA applications in metropolitan environments. The proposal is based on the experimentally verified hypothesis that the path loss due to building penetration can be practically compensated for by the diversity gain of 2 times 2 systems