Stochastic Channel Model Research Articles

Spatial channel correlation for local scattering with linear MMSE‐based estimator and detector in multi‐cell large scale MU‐MIMO networks

AbstractScalable Multi‐antenna systems are designed to gain improvement in energy and spectral efficiency under different propagation conditions by equipping the BSs with hundreds or even more antennas. A better understanding of such systems leads to overcome the essential challenges, which is important for the beneficial deployment in future networks. In wireless communication systems, channel models describe the main characteristics of the propagation environment and are essential for systems performance evaluation. This article considers a multi‐cell large scale multiuser MIMO (LS‐MU‐MIMO) system with a physical correlated channel model and linear‐based MMSE estimator and detector. A physical local scattering geometric‐based stochastic channel model for dense urban and suburban scenarios is presented in this article to illustrate the impact of propagation environment on signal transmission in a general framework of antenna spatial correlation. Also, a pilot signaling‐based channel estimation in the uplink scenario, the effect of pilot contamination (PC), and spatial correlation on the channel estimation are studied. The effect of PC and channel estimation on the performance of LS‐MU‐MIMO system is investigated by applying MMSE‐based channel estimator and detector over uniform linear arrays (ULA) of BS antennas in different scattering environments. Moreover, different pilot reuse patterns are considered, and their impact on the average sum SE has been investigated. The simulation results show that LS‐MU‐MIMO system can provide higher performance for dense urban scenarios where the user terminals (UTs) have limited mobility and higher coherence time than suburban scenarios. Furthermore, while higher spatial correlation will result in improvement in the channel estimation quality, it contributes imperfectly to the channel hardening effect.

Geometry-Based Channel Modelling for Vehicle-to-Vehicle Communication: A Review

Vehicle-to-Vehicle (V2V) communication has received a lot of attention over recent years since it can improve the efficiency and safety of roads for drivers and travellers besides other numerous applications. However dynamic nature of this environment makes it difficult to come up with a suitable wireless communication channel model that can be used in the simulation of any V2V communication system. This paper reviews the recent techniques used for geometry-based stochastic channel modelling for V2V communication. It starts by presenting the various classes of wireless communication channel models available in the literature with more emphasis on the Geometry-Based Stochastic channel Models (GBSM). Then the paper discusses in more detail the state of the art of the regular-shaped and irregular-shaped GBSM for the two- and three-dimensional models. Finally, main challenges are identified and future research directions in this area are recommended.

A General Wideband Non-Stationary Stochastic Channel Model for Intelligent Reflecting Surface-Assisted MIMO Communications

Intelligent reflecting surface (IRS), which is composed of a large number of low-cost passive elements, has the ability to reflect the incident signal independently with an adjustable phase and amplitude shifts, has been regarded as a key and emerging technology for achieving the cost-effectively spectrum and addressing energy issues in the next generation of wireless networks. In this paper, we propose a general wideband non-stationary channel model for IRS-assisted multiple-input multiple-output (MIMO) communication scenarios, which aims at capturing the underlying propagation characteristics of IRS-assisted communication systems. By properly adjusting the key system parameters, the proposed channel model can be used to describe various IRS-assisted communication scenarios. Furthermore, we separate the channel between the mobile transmitter (MT) and mobile receiver (MR) into the subchannel between the MT and IRS, the subchannel between the IRS and MR, and the subchannel between the MT and MR. The physical properties of each subchannel are investigated accordingly; then, we develop an equivalent channel model to study the key characteristics of the proposed IRS-assisted channel model, such as the time-varying spatial-temporal (ST) cross-correlation functions (CCFs), temporal auto-correlation functions (ACFs), and frequency CCFs. Finally, numerical results demonstrate that the proposed channel model is practical for describing the IRS-assisted MIMO wireless communication scenarios.

Towards 6G: Paradigm of realistic terahertz channel modeling

Terahertz (THz) communications are envisioned as a key technology for the sixth-generation wireless communication system (6G). However, it is not practical to perform large-scale channel measurements with high degrees of freedom at THz frequency band. This makes empirical or stochastic modeling approaches relying on measurements no longer stand. In order to break through the bottleneck of scarce full-dimensional channel sounding measurements, this paper presents a novel paradigm for THz channel modeling towards 6G. With the core of high-performance ray tracing (RT), the presented paradigm requires merely quite limited channel sounding to calibrate the geometry and material electromagnetic (EM) properties of the three-dimensional (3D) environment model in the target scenarios. Then, through extensive RT simulations, the parameters extracted from RT simulations can be fed into either ray-based novel stochastic channel models or cluster-based standard channel model families. Verified by RT simulations, these models can generate realistic channels that are valuable for the design and evaluation of THz systems. Representing two ends of 6G THz use cases from microscopy to macroscopy, case studies are made for close-proximity communications, wireless connections on a desktop, and smart rail mobility, respectively. Last but not least, new concerns on channel modeling resulting from distinguishing features of THz wave are discussed regarding propagation, antenna array, and device aspects, respectively.

Modeling Multi-Frequency Characteristics for Classroom and Hall Scenarios at 2-4, 9-11 and 27-29 GHz Bands

This paper investigates the wideband channel characteristics obtained in a classroom and a hall indoor scenarios at 2-4, 9–11 and 27-29GHz. A virtual uniform circular array (UCA) based channel sounding system was utilized to capture wideband spatial channel characteristics. The propagation parameters of multipath components (MPCs) were estimated by using a high resolution parameter estimation (HRPE) algorithm. The estimated MPCs are further grouped into clusters via a novel clustering identification algorithm based on the KPowerMeans algorithm. The comparison of the composite and cluster-level characteristics at multiple frequency bands in both scenarios is investigated. Moreover, the impact of the indoor room environment, i.e. dimension and furniture, on the propagation channel is also analyzed. The statistics of channel parameters at multiple frequency bands extracted constitute a stochastic clustered spatial channel model.

Real-Time Vehicular Wireless System-Level Simulation

Future automation and control units for advanced driver assistance systems (ADAS) will exchange sensor and kinematic data with nearby vehicles using wireless communication links to improve traffic safety. In this paper we present an accurate real-time system-level simulation for multi-vehicle communication scenarios to support the development and test of connected ADAS systems. The physical and data-link layer are abstracted and provide the frame error rate (FER) to a network simulator. The FER is strongly affected by the non-stationary doubly dispersive fading process of the vehicular radio communication channel. We use a geometry-based stochastic channel model (GSCM) to enable a simplified but still accurate representation of the non-stationary vehicular fading process. The propagation path parameters of the GSCM are used to efficiently compute the time-variant condensed radio channel parameters per stationarity region of each communication link during run-time. Five condensed radio channel parameters mainly determine the FER forming a parameter vector: path loss, root mean square delay spread, Doppler bandwidth, <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> -factor, and line-of-sight Doppler shift. We measure the FER for a pre-defined set of discrete grid points of the parameter vector using a channel emulator and a given transmitter-receiver modem pair. The FER data is stored in a table and looked up during run-time of the real-time system-level simulation. We validate our methodology using empirical measurement data from a street crossing scenarios demonstrating a close match in terms of FER between simulation and measurement.

Multi-Node Vehicular Wireless Channels: Measurements, Large Vehicle Modeling, and Hardware-in-the-Loop Evaluation

Understanding multi-node vehicular wireless communication channels is crucial for future time-sensitive safety applications for human-piloted as well as partly autonomous vehicles on roads, railways and in the air. These highly dynamic wireless communication channels are characterized by rapidly changing channel statistics. In this paper we present the first fully mobile multi-node vehicular wireless channel sounding system, which is capable of simultaneously capturing multiple channel frequency responses, ensuring that measurement conditions are identical for all observed links. We use it to analyze road scenarios with multiple vehicles and a large obstructing double-decker bus. The empirical measurement data is used to parametrize a model for the large obstructing vehicle within a geometry-based stochastic channel model. We compare the time-variant channel statistics obtained from our channel model with the ones from the measurement campaign. By means of a channel emulator we obtain the packet error rates of commercial modems for the measured and the simulated wireless communication channels and compare them, in order to validate the model at the link level. We find that the path loss, the root mean square (RMS) delay spread, and the RMS Doppler spread deviate by less than 3.6 dB, 78 ns, and 52 Hz, respectively, for 80% of the total simulation duration. The PER obtained from measured data is within the maximum and minimum bounds of our model for 86% of the simulation duration.

A geometry‐based stochastic channel model and its application for intelligent reflecting surface assisted wireless communication

A geometry‐based stochastic channel model and its application for intelligent reflecting surface assisted wireless communication

Impact of Inter-Channel Interference on Shallow Underwater Acoustic OFDM Systems

This paper investigates the impacts of Inter-Channel Interference (ICI) effects on a shallow underwater acoustic (UWA) orthogonal frequency-division multiplexing (OFDM) communication system. Considering both the turbulence of the water surface and the roughness of the bottom, a stochastic geometry-based channel model utilized for a wide-band transmission scenario has been exploited to derive a simulation model. Since the system bandwidth and the sub-carrier spacing is very limited in the range of a few kHz, the channel capacity of a UWA system is severely suffered by the ICI and Doppler effects. For further investigation, we construct the signal-to-noise-plus-interference ratio (SINR) based on the simulation model, then evaluate the channel capacity. Numerical results show that the various factors of a UWA-OFDM system as subcarriers, bandwidth, and OFDM symbols affects the channel capacity under the different Doppler frequencies. Those observations give hints to select the good parameters for UWA-OFDM systems.

Projective Approach in Determining Homogeneous Hyperspherical Geometrically-Based Stochastic Channel Model’s Statistics: Angle of Departure, Angle of Arrival and Time of Arrival

This article proposes geometrically-based stochastic channel model with scatterers homogeneously distributed within $N$ -dimensional ( $N$ -D) hyperspherical-shaped scattering region for single-bounce propagation scenario, with arbitrary positions of base station (BS) and mobile station (MS). For such defined geometrically-based stochastic channel model, the angular and temporal statistics are determined by introducing the projective approach. Accordingly, azimuthal angle and time of arrival marginal PDFs are derived in closed form, while the elevation angle PDF can be delivered numerically in general, and in closed-form for specific environmental parameters. The fidelity of the analytically obtained results is evaluated by their comparison to the corresponding normalized histograms. Also, it is shown that the proposed $N$ -D model can be used to analyze some of the existing channel models like 2-D uniform disk and 3-D uniform (hemi)sphere models. Additionally, by introducing the mentioned projective approach, it is shown that the angular statistics of the proposed $N$ -D model are the same as the angular statistics of some nonuniform 2-D and 3-D models, which is an important property of the proposed model. Such observation enabled us, for the first time in the literature, to determinate angular statistics for geometrically-based stochastic channel models such as inverted parabolic scattering model, 2-D Gaussian model and 3-D Gaussian hemisphere model, for arbitrary positions of BS and MS. Such angular characteristics of proposed channel model are validated through several empirical datasets.

Statistical analysis of MIMO mobile-to-mobile communication channel employing elliptical scattering geometry

ABSTRACT Geometrical-based stochastic channel modelling approach of the wireless propagation radio links remained the topic of interest in the researcher community over the last few decades. Researchers and theorists have examined and verified through measurements the impact of various parameters of the channel on the correlations between the array elements of multiple-input and multiple-output (MIMO) antenna for different wireless propagation scenarios. In the previously proposed elliptical-based scattering channel model , mobile stations (MSs) are assumed to be fixed at the centre of elliptical geometry that resembles the situation when fast-moving calling subscribers to reside in streets, canyons or on the highways, where the scattering objects like vegetation, high-rise structures and safety walls are present at roadside terrain. In this paper, the elliptical-scattering channel model is analysed for power density spectrum (PDS) when any of the MSs moves with some velocity in any direction. Moreover, the derived theoretical results are plotted for various channel parameters like relative velocities of the MSs, and normalized frequency used. Finally, the result of the PDS of the proposed M2M elliptical scattering model is compared with the results of the F2M channel model.

3D deterministic ray tracing method for massive MIMO channel modelling and parameters extraction

Geometric stochastic method and deterministic ray tracing method are two common methods of modelling massive multiple-input multiple-output (MIMO) channels. The former has high computational efficiency but a large number of input parameters need to be extracted from measurements for different environments. Conversely, the latter is more suitable for a specific environment but consumes a lot of computing costs. In this study, a novel three-dimensional (3D) deterministic ray tracing method for massive MIMO channel modelling is proposed. The computational efficiency can be improved in two aspects compared with conventional deterministic ray tracing methods. Firstly, substantial intersection tests used in determining the propagation paths of rays are replaced with the adjacency relationships between tetrahedrons. Secondly, the process of ray tracing is independent of the location of a receiving antenna and therefore repeated ray tracing process is unnecessary for different elements of receiving antenna array. The proposed method is also used as a substitute for measurements to extract input parameters for geometric stochastic channel models. The accuracy of the proposed method in massive MIMO channel modelling and parameters extraction is verified by comparing the results with measurements and other existing channel models.

Geometry-Cluster-Based Stochastic MIMO Model for Vehicle-to-Vehicle Communications in Street Canyon Scenarios

Vehicle-to-vehicle (V2V) wireless communications have many envisioned applications for ensuring traffic safety and for addressing traffic congestion. However, developing suitable communication systems and standards for this purpose requires developers to have accurate models for the V2V propagation channel. Likewise, the dynamic evolution of multipath components (MPCs) in V2V channels has not been well modeled in existing models. In this paper, we propose a geometry-based stochastic channel model for a lightly built-up urban environment and then parametrize the model from measurements. The MPCs are extracted based on a high-resolution parameter estimation; they are tracked and clustered through a joint algorithm. The identified clusters are classified as line-of-sight, reflections from static scatterers, reflections from mobile scatterers, multiple-bounce reflections, and diffuse scattering. Specifically, the multiple-bounce reflections are modeled as twin clusters that follow the COST 273/COST2100 approach. The paper gives a full parameterization of the channel model and supplies a step-by-step implementation recipe. We verify the model by comparing two second-order statistics, i.e., the root-mean-square (RMS) delay spread and the angular spreads of arrival/departure derived from the channel model, to the results obtained directly from the measurements. Furthermore, we also identify several key factors that strongly impact the synthetic channel performance.

Measurement‐Based Experimental Statistical Modeling of Propagation Channel in Industrial IoT Scenario

AbstractThis paper presents 3–4 and 38–40 GHz wideband channel characteristics for industrial internet‐of‐things (IIoT) scenario based on measurements. The channel measurement equipment applied in the measurements consists of a programmable vector network analyzer and necessary auxiliaries. An extensive amount of data in line‐of‐sight (LoS) and non‐line‐of‐sight (NLoS) scenarios is collected with omnidirectional antennas in both transmitter and receiver ends. With the Space‐Alternating Generalized Expectation‐maximization (SAGE) algorithm, the multipath components (MPCs) of the received signals are extracted to calculate the channel model parameters, for example, channel gain coefficient, delay spread, and Ricean K factor. By studying the statistical characteristics of these parameters, a stochastic channel model in IIoT scenario is initially established and compared with the existing indoor channel models. Moreover, the distinctive characteristics of channel parameters in the millimeter wave band and sub‐6 GHz band in the IIoT scenario are demonstrated.

Stochastic channel models for massive and extreme large multiple‐input multiple‐output systems

AbstractIn this article, stochastic channel models for massive multiple‐input multiple‐output (M‐MIMO) and extreme large MIMO (XL‐MIMO) system applications are described, evaluated, and systematically compared. This work aims to cover new aspects of M‐MIMO stochastic channel models in a comprehensive and systematic way. For that, we compare different models, presenting graphically and intuitively the behavior of each model. Each M‐MIMO channel model emulates the environment using different methodologies and properties. Using metrics such as capacity, SINR, singular values decomposition, and condition number, one can understand the influence of each characteristic on the modeling and how it differentiates from other models. Moreover, in new XL‐MIMO scenarios, where the near‐field and visibility region effects arise, our finding demonstrate that for the two assumed schemes of clusters distribution, the clusters location influences the performance of the conjugate beamforming and zero‐forcing precoding due to the correlation effect, which have been analyzed from the geometric M‐MIMO channel models.

Maximum Likelihood Calibration of Stochastic Multipath Radio Channel Models

We propose Monte Carlo maximum likelihood estimation as a novel approach in the context of calibration and selection of stochastic channel models. First, considering a Turin channel model with inhomogeneous arrival rate as a prototypical example, we explain how the general statistical methodology is adapted and refined for the specific requirements and challenges of stochastic multipath channel models. Then, we illustrate the advantages and pitfalls of the method based on simulated data. Finally, we apply our calibration method to wideband signal data from indoor channels.

5G tool for evaluation and comparision of energy efficiency of mobile radio channel using second-order statistics

In order to increase energy efficiency over transmissions channels, common approach for optimization tasks is by means of channel’s second-order statistics. Actual channel modeling tools for 5G networks end with channel’s first-order statistics, although these metrics are not sufficient when channel conditions are rapidly changing, either in time, frequency or space. In this paper, we establish a tool for evaluation and comparision of energy efficiency of mobile radio channel using its second-order statistics, especially level crossing rate (LCR) and average fade durations (AFD), as they can implicitly pinpoint to transmission configurations that are energy efficient or, as oposit, become a waste of energy. Using both deterministic and stochastic channel modeling, we present results after simulations of Rayleigh channel for narrowband case and further extend it to passband cases, suitable for 5G scenario. We conclude about the energy efficiency of different transmission schemes used by the 5G physical layer observing LCR and AFD values.

Computationally Efficient Millimeter-Wave Backscattering Models: A Single-Scattering Model

The use of millimeter-wave (mm-wave) frequency bands for fifth-generation (5G) cellular mobile communications has led to intense interest from academia and industry over these spectrum resources. Despite extensive measurement campaigns and channel modeling efforts, there is a lack of deterministic backscattering models addressing the impact of the size and orientation of static scatterers on the radio channel. In this article, two 3-D computationally efficient models for calculating backscattering based on the Fresnel integrals and the error function are proposed and validated both against simulations and measurements. In addition, applying the same methodology, state-of-the-art mm-wave blockage (forward-scattering) models are modified to capture backscattered fields. Furthermore, both the introduced and the modified models preserve the structure of geometry-based stochastic channel models (GSCMs) and thus their implementation in system-level simulators is substantially beneficial due to their good accuracy and short computation time.

Map-Based Millimeter-Wave Channel Models: An Overview, Data for B5G Evaluation and Machine Learning

Within the mm-Wave range of the B5G communication systems, there will appear many types of applications with different link types. In discussions on how to cover the various channel modeling requirements of such applications, some researchers have suggested map-based channel models that are based on a ray-tracing algorithm. This article thus begins with an overview of mapbased mm-Wave channel models. The overview includes available modeling requirements with map-based channel models and the categorization of map-based channel parameters. We then explain why map-based channel models are necessary for researchers trying to evaluate novel technologies in the mm-Wave range. They are particularly necessary when the technologies operate with a new link type or when channel behaviors of a user exhibit user-specific characteristics. Next, we share the measurement data and the map-based channel parameters, which can model new link types and have user-specific characteristics. Finally, as a use case of the proposed channel model, we evaluate a machine-learning-based beam-selection algorithm that exploits power delay profiles through the shared database and a geometry-based stochastic channel model (GSCM). The delay profiles of the shared database are user-specific so they are highly correlated with angular parameters. Numerical results show that the algorithm can be more accurately evaluated through the shared database than through a GSCM. We expect that our overview and sharing the database will enable researchers to readily design a map-based channel model and evaluate B5G and machine-learning technologies.

A 2-D Geometry-Based Stochastic Channel Model for 5G Massive MIMO Communications in Real Propagation Environments

Spherical wavefront and array nonstationarity due to physically large antenna array are two typical characteristics specific to massive multiple-input–multiple-output (M-MIMO) propagation. Unfortunately, traditional MIMO channel models need to be enhanced to better characterize these two new propagation features. In light of this limitation, this article proposes an enhanced two-dimensional geometry-based stochastic channel model for 5G M-MIMO communications in real propagation environments. Specifically, a coordinate-based channel model framework is first introduced. Based on this, the impact of spherical wavefront can be mathematically described with the aid of some spatial geometric manipulations. Moreover, a general Markov process is developed to model the array nonstationarity characteristic due to cluster appearance and disappearance along the array. Meanwhile, the associated approach to derive the state transition probabilities of the proposed Markov process is detailed. Finally, capabilities of the proposed channel model in characterizing spherical wavefront and array nonstationarity of M-MIMO channels are shown by the numerical simulations. Moreover, validity of our proposal is verified by the measurement data.