Multiple-input Multiple-output Channel Research Articles

Synchronous time multiplexing for non-line-of-sight multiple-input multiple-output optical camera communications.

In typical multiple-input multiple-output (MIMO) optical camera communication (OCC) systems, the spatial correlation of MIMO channels is large. Optical signals between light sources can easily interfere with each other, negatively impacting the overall transmission performance. In this work, we propose a time-multiplexing integral modulation scheme for a non-line-of-sight MIMO OCC system, where each LED transmits different signals to improve both the data rate and security of the system. A genetic algorithm (GA)-based adaptive multi-threshold scheme is designed to demodulate the blurred fringes in multi-level pulse amplitude modulation. The experimental results show that at a distance of 2.5 m, a data rate of 16.4 kb/s can reach with the BER performance of 3.01 × 10-3, which validates the superiority and reliability of our proposed schemes.

Jamming precoding in AF relay-aided PLC systems with multiple eavessdroppers

Enhancing information security has become increasingly significant in the digital age. This paper investigates the concept of physical layer security (PLS) within a relay-aided power line communication (PLC) system operating over a multiple-input multiple-output (MIMO) channel based on MK model. Specifically, we examine the transmission of confidential signals between a source and a distant destination while accounting for the presence of multiple eavesdroppers, both colluding and non-colluding. We propose a two-phase jamming scheme that leverages a full-duplex (FD) amplify-and-forward (AF) relay to address this challenge. Our primary objective is to maximize the secrecy rate, which necessitates the optimization of the jamming precoding and transmitting precoding matrices at both the source and the relay while adhering to transmit power constraints. We present a formulation of this problem and demonstrate that it can be efficiently solved using an effective block coordinate descent (BCD) algorithm. Simulation results are conducted to validate the convergence and performance of the proposed algorithm. These findings confirm the effectiveness of our approach. Furthermore, the numerical analysis reveals that our proposed algorithm surpasses traditional schemes that lack jamming to achieve higher secrecy rates. As a result, the proposed algorithm offers the benefit of guaranteeing secure communications in a realistic channel model, even in scenarios involving colluding eavesdroppers.

On the periodicity of singular vectors and the holomorphic block-circulant SVD on the unit circumference

We investigate the singular value decomposition of a rectangular matrix that is analytic on the complex unit circumference, which occurs, e.g., with the matrix of transfer functions representing a broadband multiple-input multiple-output channel. Our analysis is based on the Puiseux series expansion of the eigenvalue decomposition of analytic para-Hermitian matrices on the complex unit circumference. We study the case in which the rectangular matrix does not admit a full analytic singular value factorization, either due to partly multiplexed systems or to sign ambiguity. We show how to find an SVD factorization in the ring of Puiseux series where each singular value and the associated singular vectors present the same period and multiplexing structure, and we prove that it is always possible to find an analytic pseudo-circulant factorization, meaning that any arbitrary arrangements of multiplexed systems can be converted into a parallel form. In particular, one can show that the sign ambiguity can be overcome by allowing non-real holomorphic singular values.

Intelligent Reflecting Surface Aided MIMO With Cascaded LoS Links: Channel Modeling and Full Multiplexing Region

In this paper, we build up a new intelligent reflecting surface (IRS) aided multiple-input multiple-output (MIMO) channel model, named the cascaded LoS MIMO channel, that is applicable to both near-field and far-field scenarios. The proposed channel model consists of a transmitter (Tx) and a receiver (Rx) both equipped with uniform linear arrays (ULAs), and an IRS is used to enable communications between the transmitter and the receiver through the line-of-sight (LoS) links seen by the IRS. When modeling the reflection of electromagnetic waves at the IRS, we take into account the curvature of the wavefront on different reflecting elements. Based on the established channel model, we show that an IRS-assisted MIMO channel is able to support spatial multiplexing solely by the cascaded LoS links. We generalize the notion of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Rayleigh distance</i> originally coined for the single-hop MIMO channel to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">full multiplexing region (FMR)</i> for the cascaded LoS MIMO channel, where the FMR is the union of all the Tx-IRS and IRS-Rx distance pairs that enable full multiplexing communication. We derive an inner bound of the FMR under a special passive beamforming (PB) strategy named reflective focusing, and provide the corresponding orientation settings of the antenna arrays that achieve full multiplexing.

Modelling the elevation power angle spectrum of a MIMO channel

&lt;p&gt;Multiple-Input Multiple-Output (MIMO) channel modelling is constantly researched, and the innovation of its three-dimensional (3D) models is the introduction of the elevation domain parameters, in particular the elevation angle of arrival (EOA) and elevation angle of departure (EOD) where their power angle spectrum (PAS) and their angular spread (AS) greatly impact the 3D MIMO performance. PAS is the basic characteristic used to estimate and model angular dispersion in wireless channels. Propagating signal waves are constrained into a path having an angle within which the power is contained. One of the scenes that will have a significant effect on these parameters is the relative height between the BS and the building. They will also depend on the distance between the base station (BS) and the user equipment (UE). In this work, we investigate the effect of distance and height on the power angle spectrum of a street canyon and a high-rise scenario in the urban environment. The wireless Insite X3D ray tracing engine and a 3D digital map of the environment were used for the simulation. It is seen that the elevation power spectrum (EPS) in the elevation domain decreases with distance and height in both scenarios for the arrival and departure. The appearance of multiple peaks leads to a double-normal distribution in the arrival of the high-rise as height increases, which is a result of reflections from multiple clusters. The azimuth power spectrum (APS) in the azimuth domain also decreases with distance and height at the arrival but increases with distance and height at the departure. The result of the power angle spectrum in this work can be used for modelling angular dispersion as well as designing adaptive antennas for wireless communication.&lt;/p&gt;

Reconfigurable MIMO antenna: previous advancements and the potential for future wireless communication

Abstract Future smart reconfigurable antennas (RAs) (Haupt R-L and Lanagan M (2013) Reconfigurable antennas. IEEE Antennas and Propagation Magazine 55, 49–61) will likely be fully multipurpose and controlled by software and equipped with machine learning skills that can discern and respond to alterations in the radio frequency environment. Cognitive radio utilizations will be accomplished using a new generation of antenna technology and communication protocols. The effective use of frequencies and the use of polarization diversity and radiation pattern reconfigurability to send data over existing congested frequencies will be major advantages for such applications. The usage of antennas that can be reconfigured in multiple-input multiple-output (MIMO) channels will enhance channel capacity while simultaneously improving channel efficiency and lowering costs (Christodoulou C-G, Tawk Y, Lane S-A and Erwin S-R (2012) Reconfigurable antennas for wireless and space applications. Proceedings of the IEEE 100, 2250–2261). There are a lot of antennas used both at the transmitter and at the receiver front end in a MIMO system. The benefit of employing such arrangements is that different types of information can be conveyed at a similar time, boosting the spectral efficiency of communication in a multipath situation. The coding rate, modulation level, and transmission signaling method of a MIMO system can all be changed in response to changing channel circumstances and user needs. In a MIMO context, polarization reconfigurable/frequency-reconfigurable/radiation pattern RA increase the degree of freedom and enhancing the system’s performance. The usage of such antennas greatly enhances capacity by enabling a choice of various polarization configurations and pattern diversity. Antenna arrays that can be reconfigured are also an appealing MIMO system solution that needs to retain robust communication channels, particularly in portable gadgets where the area is limited.

Antenna Selection for Reconfigurable Intelligent Surfaces: A Transceiver-Agnostic Passive Beamforming Configuration

Reconfigurable intelligent surface (RIS) is capable of improving the wireless system performance by steering the reflected signal in the desired direction. One of the major challenges is that both the transceiver and RIS have to be jointly optimized, where the optimization problems have to be reformulated for different system models and scenarios. To circumvent this challenge, new low-complexity antenna selection (AS) algorithms for transceiver-agnostic RIS configuration are proposed. Given a multiple-input multiple-output (MIMO) channel, the proposed RIS-AS opts for accurately aligning the RIS both with the transmit antenna (TA) and receive antenna (RA) for the sake of maximizing the MIMO channel’s overall output power. The proposed RIS-AS only has to configure the RIS alone, i.e. without iterations with the transceiver optimization. As a result, the proposed RIS-AS has the compelling benefit that they are generically applicable, regardless of the specific transceiver architecture. Our simulation results confirm that the proposed RIS-AS is capable of supporting any MIMO configuration, regardless of their closed/open-loop, single-/full-RF and multiplexing-/diversity-oriented setups.

Parabolic Wavefront Model for Line-of-Sight MIMO Channels

Motivated by the widespread adoption of the parabolic wavefront model for line-of-sight (LOS) multiple-input multiple-output (MIMO) communication, this paper presents a comprehensive analysis of this model’s validity and simple conditions that ensure its applicability. Then, with the model’s scope clearly delineated, the paper expounds a number of properties of the channel that results from applying it. Connections are drawn among these properties under the umbrella of a Fourier interpretation, and their significance to LOS MIMO communication is substantiated.

Pathloss Modeling and Analysis for Intelligent Reflecting Surface-Assisted Terahertz MIMO Wireless Systems

In this paper, the impact of the intelligent reflecting surface (IRS) on the propagation characteristics is analyzed from the arguments of the physical and electromagnetic characteristics of the channel. Analytical expressions for free-space pathloss are derived based on the terahertz multiple-input multiple-output (MIMO) channel model in different communication scenarios. This calculation method is broadly applicable and is used to characterize pathloss as a function of the configuration of our system model. Numerical results show that setting the phase matrix of IRS based only on the angle of arrival (AoA) and angle of departure (AoD) can significantly reduce the pathloss when the far-field condition is met. However, when the distance between the transceiver and the IRS is the same order of magnitude or less than the side length of the IRS, both direction and distance information are required to configure the IRS. This model provides an insightful consideration in the design of IRS-assisted wireless system.

A Scalable Spatial–Temporal Correlated Non-Stationary Channel Fading Generation Method

To address the challenges of complex implementation structures and high hardware resource consumption in multiple-input multiple-output (MIMO) channel emulators, this paper proposes a hardware generation method for spatial–temporal correlated non-stationary channel fading. Firstly, a hardware generation architecture is developed for field-programmable gate array (FPGA) platforms, which can also reduce the complexity of the channel emulator. Secondly, an improved CORDIC method is introduced to reduce algorithm latency and hardware consumption while expanding the function convergence domain, with a relative error maintained at the level of 10-4. Furthermore, based on the idea of time-division multiplexing, an efficient hardware operation of a lower triangular matrix is adopted to minimize the consumption of hardware resources. Finally, the measured results demonstrate that the statistical characteristics of the channel fading generated by the proposed method are in good agreement with the theoretical ones, with an average error of less than 2%. Additionally, under identical simulation conditions, hardware resource consumption is reduced by 6.87%. These findings provide compelling evidence of the enhanced efficiency and accuracy in simulating MIMO channels achieved through the proposed method.

Hybrid mmWave MIMO Systems Under Hardware Impairments and Beam Squint: Channel Model and Dictionary Learning-Aided Configuration

Low overhead channel estimation based on compressive sensing (CS) has been widely investigated for hybrid wideband millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. The channel sparsifying dictionaries used in prior work are built from ideal array response vectors evaluated on discrete angles of arrival/departure. In addition, these dictionaries are assumed to be the same for all subcarriers, without considering the impacts of hardware impairments and beam squint. In this manuscript, we derive a general channel and signal model that explicitly incorporates the impacts of hardware impairments, practical pulse shaping functions, and beam squint, overcoming the limitations of mmWave MIMO channel and signal models commonly used in previous work. Then, we propose a dictionary learning (DL) algorithm to obtain the sparsifying dictionaries embedding hardware impairments, by considering the effect of beam squint without introducing it into the learning process. We also design a novel CS channel estimation algorithm under beam squint and hardware impairments, where the channel structures at different subcarriers are exploited to enable channel parameter estimation with low complexity and high accuracy. Numerical results demonstrate the effectiveness of the proposed DL and channel estimation strategy when applied to realistic mmWave channels.

Asymptotic Mutual Information Analysis for Double-Scattering MIMO Channels: A New Approach by Gaussian Tools

The asymptotic mutual information (MI) analysis for multiple-input multiple-output (MIMO) systems over double-scattering channels has achieved engaging results, but the convergence rates of the mean, variance, and the distribution of the MI are not yet available in the literature. In this paper, by utilizing the large random matrix theory (RMT), we give a central limit theory (CLT) for the MI and derive the closed-form approximation for the mean and the variance by a new approach—Gaussian tools. The convergence rates of the mean, variance, and the characteristic function are proved to be <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i> (1/ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> ) for the first time, where <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> is the number of receive antennas. Furthermore, the impact of the number of effective scatterers on the mean and variance was investigated in the moderate-to-high SNR regime with some interesting physical insights. The proposed evaluation framework can be utilized for the asymptotic performance analysis of other systems over double-scattering channels.

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.

On the BER Performance of Constant Envelope OFDM in Frequency Selective MIMO Channels With ML Detection

In this contribution, we investigate the issue of constant envelope orthogonal frequency-division multiplexing (CE-OFDM) transmission in multipath fading channels, by quantifying its bit-error rate (BER) performance with the aid of maximum likelihood (ML) detection in multiple-input multipleoutput (MIMO) configurations. Through theoretical derivation, we demonstrate the advantage of CE-OFDM over its traditional counterparts as original OFDM and discrete Fourier transformspread-OFDM (DFT-s-OFDM) in terms of BER performance, which is ultimately supported by the simulation results.

CUDA-Optimized GPU Acceleration of 3GPP 3D Channel Model Simulations for 5G Network Planning

The simulation of massive multiple-input multiple-output (MIMO) channel models is becoming increasingly important for testing and validation of fifth-generation new radio (5G NR) wireless networks and beyond. However, simulation performance tends to be limited when modeling a large number of antenna elements combined with a complex and realistic representation of propagation conditions. In this paper, we propose an efficient implementation of a 3rd Generation Partnership Project (3GPP) three-dimensional (3D) channel model, specifically designed for graphics processing unit (GPU) platforms, with the goal of minimizing the computational time required for channel simulation. The channel model is highly parameterized to encompass a wide range of configurations required for real-world optimized 5G NR network deployments. We use several compute unified device architecture (CUDA)-based optimization techniques to exploit the parallelism and memory hierarchy of the GPU. Experimental data show that the developed system achieves an overall speedup of about 240× compared to the original C++ model executed on an Intel processor. Compared to a design previously accelerated on a datacenter-class field programmable gate array (FPGA), the GPU design has a 33.3% higher single-precision performance but a 7.5% higher power consumption. The proposed GPU accelerator can provide fast and accurate channel simulations for 5G NR network planning and optimization.

A low-complexity algorithm based on variational Bayesian inference for MIMO channel estimation

With an increase in the number of transmitters in multiple-input multiple-output (MIMO) communication systems, there is a cubic rise in the computational complexity of the traditional sparse Bayesian learning (SBL) channel estimation algorithm. While various algorithms are effective for single-input single-output (SISO) systems, they are not suitable for the MIMO scenario. This paper introduces a MIMO channel estimation algorithm based on variational Bayesian inference (VBI) by assuming the independence of the variational distribution among different channels. The high-dimensional channel vectors estimated in the conventional MIMO-SBL algorithm are decomposed into multiple parallel low-dimensional channel vectors with different sparsity using VBI. Consequently, the complexity exhibits a linear relationship with the number of transmitters, as demonstrated through numerical analysis. Simulations confirm the improved estimation accuracy of the MIMO-VBI algorithm. Experimental results reveal that MIMO systems can achieve lower bit error rates using the MIMO-VBI algorithm, with reduced runtime for channel lengths exceeding 100 symbols.

Three-Dimensional Image Transmission of Integral Imaging through Wireless MIMO Channel.

For the reconstruction of high-resolution 3D digital content in integral imaging, an efficient wireless 3D image transmission system is required to convey a large number of elemental images without a communication bottleneck. To support a high transmission rate, we herein propose a novel wireless three-dimensional (3D) image transmission and reception strategy based on the multiple-input multiple-output (MIMO) technique. By exploiting the spatial multiplexing capability, multiple elemental images are transmitted simultaneously through the wireless MIMO channel, and recovered with a linear receiver such as matched filter, zero forcing, or minimum mean squared error combiners. Using the recovered elemental images, a 3D image can be reconstructed using volumetric computational reconstruction (VCR) with non-uniform shifting pixels. Although the received elemental images are corrupted by the wireless channel and inter-stream interference, the averaging effect of the VCR can improve the visual quality of the reconstructed 3D images. The numerical results validate that the proposed system can achieve excellent 3D reconstruction performance in terms of the visual quality and peak sidelobe ratio though a large number of elemental images are transmitted simultaneously over the wireless MIMO channel.

Impact of channel imperfections on variant SMTs MIMO systems over revised Nakagami-[formula omitted] channel model

Recently, a revised model for the Nakagami-m multiple-input multiple-output (MIMO) channel has been proposed, yielding distinct results and conclusions compared to the existing model. This article focuses on evaluating and discussing the performance of MIMO space modulation techniques (SMTs) transmission schemes, namely space shift keying (SSK), quadrature space shift keying (QSSK), spatial modulation (SM), and quadrature spatial modulation (QSM), over the revised channel model. The evaluation considers spatial correlation, imperfect channel state information (CSI), and examines various performance metrics such as average bit error rate (ABER), mutual information, and capacity. Specifically, a closed-form expression for the ABER is derived under the assumption of a maximum-likelihood (ML) receiver. Additionally, formulas for mutual information and capacity are derived and thoroughly discussed. To validate the derived formulas, extensive Monte Carlo simulations are performed. Furthermore, the impact of system parameters on the ABER, mutual information, and capacity is investigated, providing a comprehensive analysis of their variations. A comparative study is conducted between different transmission schemes using the revised model, elucidating their relative performance. Moreover, a comparison is made between the reported results of the revised model and the existing Nakagami-m model, as well as other channel distributions such as Rayleigh and Rice fading channels. The findings clearly demonstrate the disparities between the existing and revised models, with the revised model exhibiting superior performance. Notably, when comparing the scenario of m=1 with a Rayleigh fading channel, an exact match is observed for the revised channel model, while some differences are detected for the existing model.

MIMO Channel Estimation Using Score-Based Generative Models

Channel estimation is a critical task in multiple-input multiple-output (MIMO) digital communications that substantially effects end-to-end system performance. In this work, we introduce a novel approach for channel estimation using deep score-based generative models. A model is trained to estimate the gradient of the logarithm of a distribution and is used to iteratively refine estimates given measurements of a signal. We introduce a framework for training score-based generative models for wireless MIMO channels and performing channel estimation based on posterior sampling at test time. We derive theoretical robustness guarantees for channel estimation with posterior sampling in single-input single-output scenarios, and experimentally verify performance in the MIMO setting. Our results in simulated channels show competitive in-distribution performance, and robust out-of-distribution performance, with gains of up to 5 dB in end-to-end coded communication performance compared to supervised deep learning methods. Simulations on the number of pilots show that high fidelity channel estimation with 25% pilot density is possible for MIMO channel sizes of up to 64 × 256. Complexity analysis reveals that model size can efficiently trade performance for estimation latency, and that the proposed approach is competitive with compressed sensing in terms of floating-point operation (FLOP) count.

Multifrequency Wireless Channel Measurements and Characterization in Large Indoor Office Environments

This paper performs extensive channel measurements and characteristics analysis to investigate large-scale fading (LSF) and small-scale fading (SSF) of wireless local area network (WLAN) channels in large indoor office environments. Multi-frequency single-input single-output (SISO) channel measurements are conducted at 3, 5.5, and 6.5 GHz under the same conditions to explore the frequency dependence of LSF, delay spread (DS), and K-factor (KF). Then, SISO channel measurements with different half-power beamwidths (HPBWs) of antennas are performed at 5.5 GHz in access point (AP) to user equipment (UE) and AP to AP scenarios. The effects of antenna HPBW on LSF, DS, and KF are investigated, thereby inspiring the AP deployment in high density (HD) scenarios. Finally, 32×64 multiple-input multiple-output (MIMO) channel measurements at 5.5 GHz are conducted to study the SSF of the time non-stationarity and multi-link correlation. The time non-stationarity, including the parameters drifting and cluster evolution caused by the movement of the UE, is verified by measurement results. Multi-link correlations are illustrated from perspectives of the angular power spectral density (APSD) and correlation matrix collinearity (CMC). The results show that the distance between users and separation angle can affect the multi-link correlation.