Geometry-based Channel Model Research Articles

Geometry-Based Channel Model for Extra-Large Scale Array Communication Systems

Geometry-Based Channel Model for Extra-Large Scale Array Communication Systems

Geometry-Based Channel Modeling for Tunnel Entrance Scenarios of Mountain Railway

Geometry-Based Channel Modeling for Tunnel Entrance Scenarios of Mountain Railway

Modeling the Geometry of an Underwater Channel for Acoustic Communication

The achievement of efficient data transmissions via underwater acoustic channels, while dealing with large data packets and real-time data fed by underwater sensors, requires a~high data rate. However, diffraction, refraction, and reflection phenomena, as well as phase and amplitude variations, are common problems experienced in underwater acoustic (UWA) channels. These factors make it difficult to achieve high-speed and long-range underwater acoustic communications. Due to multipath interference caused by surface and ocean floor reflections, the process of modeling acoustic channels under the water's surface is of key importance. This work proposes a~simple geometry-based channel model for underwater communication. The impact that varying numbers of reflections, low water depth values, and distances between the transmitter and the receiver exert on channel impulse response and transmission loss is examined. The high degree of similarity between numerical simulations and actual results demonstrates that the proposed model is suitable for describing shallow underwater acoustic communication environments.

Channel Measurements and Modeling for Low Terahertz Communications in an Aircraft Cabin

The low terahertz band (0.1–1 THz) offers very high data rates for novel mobile applications and constitutes a promising candidate to meet the requirements in aviation, enabling future wireless in-flight entertainment (IFE) systems. An extensive knowledge of the propagation effects in the radio channel in complex scenarios is a prerequisite to successfully design a communication system. This article presents a measurement campaign in a real aircraft investigating the radio channel at 300 GHz for different deployments of a wireless IFE system. The propagation effects as well as temporal and spatial channel characteristics are analyzed for likely communication links between an access point and a user equipment (UE). In the same way, interference links between two UEs are studied, reporting transmission and reflection losses for various components of the aircraft. A deterministic and geometry-based channel model is derived and extended to cover the effect of human blockage that suggests an integration of the access point into the passenger service unit. The measurement and realistic path loss models can be used in further link and system level simulations and contribute to the design of future IFE systems.

Research on Vehicle-to-Vehicle MIMO Wireless Channels in Various Tunnels

In this paper, we propose a geometry-based channel model for multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) communications in practical tunnel scenarios. In the proposed channel model, the waves transmitted from the transmitter experience line-of-sight (LoS) and non-LoS (NLoS) before arriving at the receiver. The time-varying parameters of the propagation paths and angles are derived to characterize the channel non-stationarity. Furthermore, we derive the correlation property functions of the proposed V2V channel model; they are space cross-correlation functions (CCFs), temporal auto-correlation functions (ACFs), frequency CCFs, as well as the Doppler power spectrum distributions (PSDs). Numerous simulation results of the propagation characteristic for different physical properties of the tunnel, as well as the different motion properties of the transmitter and receiver, are studied and discussed; they demonstrate that the proposed channel model is suitable for describing the practical V2V tunnel communication scenarios.

Geometry-Based UAV-MIMO Channel Modeling Assisted by Intelligent Reflecting Surface

A three dimensional (3-D) geometry-based channel model is proposed for intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV) multiple-input multiple-output (MIMO) communication scenarios where the users are located on the edge of IRS service area. In order to reduce the interference between different IRS reflection units, we first construct an optimization problem about the statistical propagation phases of different IRS reflection units, and then derive the optimal statistical propagation phase by solving the designed optimization problem. Finally, we align the proposed statistical propagation phases of IRS with the stronger components to derive suboptimal IRS reflection phases. Using derived IRS reflection phases, the statistical properties are investigated. The numerical results show that the proposed IRS reflection phases can enhance the received signal strength and reduce the multipath fading effect. Also, it can be observed that when the number of IRS reflection units increases, the spatial correlation significantly decreases.

FPGA Acceleration of 3GPP Channel Model Emulator for 5G New Radio

The channel model is by far the most computing intensive part of the link level simulations of multiple-input and multiple-output (MIMO) fifth-generation new radio (5G NR) communication systems. Simulation effort further increases when using more realistic geometry-based channel models, such as the three-dimensional spatial channel model (3D-SCM). Channel emulation is used for functional and performance verification of such models in the network planning phase. These models use multiple finite impulse response (FIR) filters and have a very high degree of parallelism which can be exploited for accelerated execution on Field Programmable Gate Array (FPGA) and Graphics Processing Unit (GPU) platforms. This paper proposes an efficient re-configurable implementation of the 3rd generation partnership project (3GPP) 3D-SCM on FPGAs using a design flow based on high-level synthesis (HLS). It studies the effect of various HLS optimization techniques on the total latency and hardware resource utilization on Xilinx Alveo U280 and Intel Arria 10GX 1150 high-performance FPGAs, using in both cases the commercial HLS tools of the producer. The channel model accuracy is preserved using double precision floating point arithmetic. This work analyzes in detail the effort to target the FPGA platforms using HLS tools, both in terms of common parallelization effort (shared by both FPGAs), and in terms of platform-specific effort, different for Xilinx and Intel FPGAs. Compared to the baseline general-purpose central processing unit (CPU) implementation, the achieved speedups are 65X and 95X using the Xilinx UltraScale+ and Intel Arria FPGA platform respectively, when using a Double Data Rate (DDR) memory interface. The FPGA-based designs also achieved ~3X better performance compared to a similar technology node NVIDIA GeForce GTX 1070 GPU, while consuming ~4X less energy. The FPGA implementation speedup improves up to 173X over the CPU baseline when using the Xilinx UltraRAM (URAM) and High-Bandwidth Memory (HBM) resources, also achieving 6X lower latency and 12X lower energy consumption than the GPU implementation.

A Non-Stationary Geometry-Based Channel Model for IRS-Assisted UAV-MIMO Channels

A non-stationary three dimensional (3-D) intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV) multiple-input multiple-output (MIMO) channel model is proposed. The time-varying reflection phases of the IRS, which are designed based on the optimal power of the received signal, are investigated. Based on the proposed reflection phases, the effect of the number and geometric area of IRS reflection units and the speed of UAV on channel statistics are also investigated. The numerical results show that the power of received signal can be enhanced and the multipath fading phenomenon can be effectively reduced by using tunable phases of IRS, and the spatial correlation significantly decreases with the increase of the number of IRS reflection units.

Performance Investigation of High-Speed Train OFDM Systems under the Geometry-Based Channel Model

Performance Investigation of High-Speed Train OFDM Systems under the Geometry-Based Channel Model

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.

A 3-D Non-Stationary Wideband Geometry-Based Channel Model for MIMO Vehicle-to-Vehicle Communications in Tunnel Environments

In this paper, we present a three-dimensional (3-D) wideband geometry-based channel model for multiple-input and multiple-output vehicle-to-vehicle (V2V) communication in tunnel environments. We introduce a two-cylinder model to describe moving vehicles, as well as multiple confocal semi-ellipsoid models to depict internal surfaces of tunnel walls. The received signal is constructed as a sum of direct line-of-sight propagations, rays with single and double interactions. The movement between the mobile transmitter and mobile receiver results in time-varying geometric statistics that make our channel model non-stationary. Using this channel model, the proposed channel characteristics are studied for different V2V scenarios. The numerical results demonstrate that the proposed 3-D non-wide-sense stationary (WSS) wideband channel model is practical for characterizing real V2V channels.

A Novel Estimated Wideband Geometry-Based Vehicle-to-Vehicle Channel Model Using an AoD and AoA Estimation Algorithm

In this paper, we propose an estimated wideband geometry-based channel model for vehicle-to-vehicle (V2V) communication environments, which is based on an angle of departure (AoD) and angle of arrival (AoA) estimation algorithm, to determine the ellipse scattering region and to efficiently study the V2V channel characteristics for different propagation delays, i.e., per-tap channel statistics. In the first stage, we estimate the AoD and AoA for the first tap. In this case, the ellipse-scattering region for the first tap can be determined. Then, we estimate the ellipse channel models for other taps based on the estimated model parameters for the first tap. Furthermore, the spatial cross-correlation functions (CCFs) are derived and thoroughly investigated for different propagation delays. The excellent agreement is achieved between the proposed channel statistics and prior results and measurements.

3D Modeling and Analysis of the Space–Time Correlation for 5G Millimeter Wave MIMO Channels

The deployment of millimeter waves (mmW) in 5G mobile networks is considered as a challenging issue due to the lack of knowledge regarding the propagation of mmW in such multipath fading environments. Therefore, the analysis and modeling of such mobile fading channels is required. In this paper, we investigate the space–time correlation functions for multiple-input multiple-output (MIMO) channels in mmW frequency bands. We develop a 3-D geometry-based channel model for Rician channel to overcome the multipath fading. Such a model is able to provide a realistic channel propagation with multiple antenna elements surrounded by a scattering environment. We derive the space–time correlation functions for the scattering environments in terms of the different system parameters of the MIMO fading channel. We present the numerical evaluations to study the influence of the system parameters such as normalized time delay, vertical and horizontal antenna polarization, and separation between antenna elements on the performance of the space–time correlation functions.

Novel 3-D Irregular-Shaped Geometry-Based Channel Modeling for Semi-Ellipsoid Vehicle-to-Vehicle Scattering Environments

This letter presents a 3-D irregular-shaped geometry-based stochastic model for vehicle-to-vehicle (V2V) radio propagation environments, in which an asymmetric directional multiple input and multiple output technique is employed at the mobile transmitter (MT). The time-varying geometric path lengths are introduced in the proposed channel model to capture the non-stationarity, which is caused by the motion of the MT and mobile receiver. More importantly, the impacts of the model parameters and non-stationarity, i.e., relative moving directions and relative moving time, on the channel statistical properties are investigated. The results show that the proposed 3-D model fits the prior results very well, which demonstrate that the model is practical to provide guidelines for the system design and performance analysis of V2V communication systems.

Mobility Model-Based Non-Stationary Mobile-to-Mobile Channel Modeling

Non-stationary mobile-to-mobile (M2M) channel modeling has gained strong momentum as it is vital for developing M2M communications technology. Traditional geometry-based channel models (GSCMs) for M2M communications usually assume fixed velocity and moving direction, which differs from the realistic M2M scenarios and also makes it difficult to incorporate non-stationarity of channel into the regular-shaped GSCMs. In this paper, a mobility model-based method is proposed to incorporate non-stationarity into M2M channel modeling by introducing dynamic velocities and trajectories. A revised Gauss–Markov mobility model is first presented together with the cluster-based two-ring M2M reference model. The mobility model uses tuning parameters to adjust the degree of mobility randomness and covers different M2M mobility trajectories. Then, a closed-form time-variant time-frequency correlation function and the Doppler power spectrum are derived from the model. Based on the numerical analysis, it is found that for a regular-shaped GSCM with a fixed M2M scattering environment, the motion does not introduce non-stationarity, however, the dynamic motion (i.e., the changes of velocity and moving direction) leads to non-stationarity, which is reflected by the time-variant time correlation function and Doppler spectrum. Different propagation modes, cluster number, and intra-cluster nonisotropic scattering also have major impacts on channel non-stationarity. Moreover, the randomness of the mobility model is found to significantly increase the degree of channel non-stationarity. These conclusions are useful for M2M non-stationary channel simulation and communication system evaluation.

A geometry-based non-stationary MIMO channel model for vehicular communications

This paper derives a non-stationary multiple-input multiple-output(MIMO) from the one-ring scattering model. The proposed channel model characterizes vehicular radio propagation channels with considerations of moving base and mobile stations, which makes the angle of arrivals (AOAs) along with the angle of departures (AODs) time-variant. We introduce the methodology of including the time-variant impacts when characterizing non-stationary radio propagation channels through the geometrical channel modelling approach. We analyze the statistical properties of the proposed channel model including the local time-variant autocorrelation function (ACF) and the space cross-correlation functions (CCFs). We show that the model developed in this paper for non-stationary scenarios includes the existing one-ring wide-sense stationary channel model as its special case.

A Novel MIMO Channel Model for Vehicle-to-Vehicle Communication System on Narrow Curved-Road Environment

This paper presents a generalized statistical multiple-input multiple-output (MIMO) fading channel model for a vehicle-to-vehicle (V2V) non-line of sight mobile communication system on narrow curved-road environments. The MIMO channel model captures the propagation effect that occurs when vehicles move towards a junction with a side road and corner scatterings. In this paper, both single- and double-bounced scattering mechanisms are considered and it is assumed that the scatterers are uniformly distributed in the form of narrow arcs outside the annular road. Our geometry-based channel model takes the exact relationship between the angle-of-arrival and the angle-of-departure into account. Thereafter, the statistical properties of the model are studied under the assumption of non-isotropic scattering. Analytical expressions of different parameters, such as the space---time-frequency cross-correlation function, Doppler power spectral density, and MIMO channel capacity are provided. Furthermore, the influence of model parameters on the performance of V2V communication system has been analyzed. The study provides a design layout of MIMO V2V communication systems with a wide-band spatial channel model enabling the performance analysis of new high-data-rate transmission schemes for narrow curved-road propagations.

Second-Order Statistics Channel Model for 5G Millimeter-Wave Mobile Communications

Millimeter waves (mmWs) are considered as one of the most promising technologies for future 5G networks. The current study presents a three-dimensional (3D) geometry-based channel model for a fixed-to-mobile non-isotropic Ricean mmW scattering environment. According to this 3D reference model, the mmW complex faded envelope impulse response has been derived. This impulse response has been employed in estimating the second-order statistics of the mmW channel model. These statistics comprise both the 3D faded envelope level crossing rate (LCR) and the average fade duration (AFD). As a consequence, these statistics may contribute to the 5G network planning and engineering, especially for studying the phenomenon of fading with time, the 5G system characteristics, the handoff scenarios, and the relationship between the mobile user velocity and the fading rate. Furthermore, this study also provides a stochastic sum-of-sinusoids mmW channel simulator for comparison with analytical results. Numerical results validated the proposed analytical model and revealed the effect of channel parameters on both LCR and AFD in the mmW bands.

A Geometry-Based Channel Model to Simulate an Averaged-Power-Delay Profile

Wireless communications or navigation is heavily influenced by electromagnetic wave propagation. The power-delay profile (PDP) characterizes the propagation channel by simple statistics. In this communication, we propose a channel model to simulate a given wideband averaged PDP obtained by measurements or theoretical considerations, enabling to test, develop, and design radio links. The channel model is based on a geometrical stochastic approach, allowing to simulate the space-variant channel impulse response for a moving receiver. Furthermore, the appearance and disappearance of multipath components are geometrically taken into account by an angular pattern. We verify the proposed methodology by simulations.

HOSVD based multidimensional parameter estimation for massive MIMO system from incomplete channel measurements

The dominant multipath components for massive multiple-input multiple-output systems can be described using geometry-based channel models with R-dimensional (R-D) parameters. These parameters are crucial for channel correlation acquisition, which is a prerequisite for many technical challenges. In this paper, we consider higher-order singular value decomposition based R-D channel modeling parameter estimation from incomplete measurements. Incomplete higher-order orthogonality iteration algorithm can be utilized to solve the problem, which simultaneously achieves tensor recovery and tensor decomposition. After obtaining the signal or noise subspace, the parameters of interest can be estimated by using subspace methods.