Geometry-based Stochastic Channel Model Research Articles

Geometry-Based Stochastic Channel Model for Two-Story Lobby Environment at 10 GHz

This paper presents a complete parametrization for a three-dimensional (3-D) geometry-based stochastic radio channel model (GSCM) at 10.1 GHz based on a measurement campaign. The radio channel measurements were carried out with a vector network analyzer over a 500 MHz bandwidth in a two-story lobby environment. The measurements were conducted with $9 \times 324$ dual polarized virtual antenna arrays in line-of-sight (LOS) and non-LOS propagation conditions. The recorded data was postprocessed using the estimation of signal parameters via rotation invariance algorithm. The statistical analysis was carried out to provide full 3-D parametrization for the GSCM. The parametrization was verified by radio channel simulations. Multiple-input multiple-output (MIMO) channel is reconstructed from the estimated propagation paths and equivalently the channel simulations are performed by quasi-deterministic radio channel generator using our measurements-based parameters. The channel capacity, Demmel condition number, and relative condition numbers are used as the verification metrics. The results show that the reconstructed MIMO channel matches well the simulated MIMO channel.

5-GHz Vehicle-to-Vehicle Channel Characterization for Example Overpass Channels

The overpass is a special over-road structure for vehicular travel, constituting one type of roadway intersection. Real-time communications between on- and under-overpass vehicles can contribute to effective vehicle-to-vehicle (V2V) communications, including, for example, optimal route selection and overpass accident warning messaging. Ensuring effective communication requires a quantitative characterization of the overpass propagation channel. In this paper, we provide measurement and analytical results for V2V propagation path loss and root-mean-square delay spread, and from these results, we develop tapped-delay line channel models that are applicable to the 5-GHz band for two example overpasses. These two example overpasses are termed i) one-lane metal-bottom overpass and ii) two-lane metal-bottom overpass. Due to the unique structure of the overpasses, we divide the radio propagation space around the overpass into four different areas: a two-ray area, a short-term partial-shadowing area, a (full) shadowing area, and a long-term partial-shadowing area. In the two-ray area, a line-of-sight (LOS) path and a ground-reflected path are the dominant propagation mechanisms, whereas in the other areas, the overpass body (floor, walls, and columns) attenuates the LOS signal. The accuracy of our measurement results and the developed channel model are verified by a geometry-based stochastic channel modeling approach, in which the height dimension is first introduced to characterize the diffraction phenomenon in V2V communication. The actual measurement and simulation results show good consistency.

A geometry-based stochastic approach to emulate V2V communications’ main propagation channel metrics

In order to evaluate a communication system, we need to model the propagation channel of the relevant environments pertaining to that communication. In this paper, we propose a Geometry-Based Stochastic Channel Modeling approach to build up propagation channel simulations to assess the performance of vehicle-to-vehicle wireless communications. Our methodology allows the simulation of dynamic scenarios, with an electromagnetic simulator, to emulate typical propagation environments (rural, highway and urban-like propagation channels). Simple metallic plates are used to represent scatterers in the simulated geometric configurations. The common characteristics defining a propagation channel such as delay spread, angle of arrival distribution, and the delay-Doppler spectrum are obtained through adjustment of the number and location of those simple metallic plates.

Empirical Stochastic Modeling of Multipath Polarizations in Indoor Propagation Scenarios

In this contribution, a stochastic modeling approach is proposed for characterizing the polarization status of multipath components (MPCs) in propagation channels. The $2 \times 2$ polarization matrix of each MPC is represented by the geometrical parameters of two ellipses, i.e., the ovality, tilt angle, and size of each ellipse, as well as the rotating direction of electric field intensity along the ellipse. The statistics of these parameters including correlation behaviors among them extracted from measurement data constitute the stochastic polarization model for the propagation scenario of interest. Analytical expressions are presented for the transformation from the ellipse parameters to the $2 \times 2$ polarization matrix, and vice versa. Comparing with conventional polarization models addressing merely the cross-polarization ratios, the new model provides a more complete description for the per-path polarizations in terms of the power imbalance, tilting, and polarization spread. Furthermore, based on multiple-input multiple-output channel measurement data collected with 100-MHz bandwidth and at the center frequency of 5.25 GHz, stochastic polarization models of the proposed structure are extracted for five indoor scenarios. These models are complementary to the existing geometry-based stochastic channel models for generating realistic polarization matrices for MPCs.

Polarization projection for 3D geometry-based stochastic channel model

Comprehensive radiation characteristics of polarized antenna are crucial in creating practical channel coefficients for next generation wireless communication system designs. Being currently supported within 3D geometry-based stochastic channel models (GSCM), field patterns are technically obtained by chamber measurement (or by its best fitting). However, in some channel related performance analysis scenarios, design insight can be crystallized better by starting the derivations with theoretical co-polarization and cross-polarization components. Specifically, these two components are mathematically linked with field patterns through the proposed polarization projection algorithm. In this manuscript, we focus on revealing the transformation criterion of polarization states between the antenna plane and the propagation plane. In practice, it makes retrieving the field patterns by electromagnetic computation possible. Meanwhile, the impact imposed by distinct antenna orientations is geometrically illustrated and consequently incorporated into the proposed algorithm. This will further facilitate flexible performance evaluation of related radio transmission technologies. Our conclusions are verified by the closed-form expression of the dipole field pattern (via an analytical approach) and by chamber measurement results. Moreover, we find that its 2D degenerative case is aligned with the definitions in 3rd generation partnership project (3GPP) technical report 25.996. The most obvious benefit of the proposed algorithm is to significantly reduce the cost on generating channel coefficients in GSCM simulation.

Nested Sparse Approximation: Structured Estimation of V2V Channels Using Geometry-Based Stochastic Channel Model

Future intelligent transportation systems promise increased safety and energy efficiency. Realization of such systems will require vehicle-to-vehicle (V2V) communication technology. High fidelity V2V communication is, in turn, dependent on accurate V2V channel estimation. V2V channels have characteristics differing from classical cellular communication channels. Herein, geometry-based stochastic modeling is employed to develop a characterization of V2V channel channels. The resultant model exhibits significant structure; specifically, the V2V channel is characterized by three distinct regions within the delay-Doppler plane. Each region has a unique combination of specular reflections and diffuse components resulting in a particular element-wise and group-wise sparsity. This joint sparsity structure is exploited to develop a novel channel estimation algorithm. A general machinery is provided to solve the jointly element/group sparse channel (signal) estimation problem using proximity operators of a broad class of regularizers. The alternating direction method of multipliers using the proximity operator is adapted to optimize the mixed objective function. Key properties of the proposed objective functions are proven which ensure that the optimal solution is found by the new algorithm. The effects of pulse shape leakage are explicitly characterized and compensated, resulting in measurably improved performance. Numerical simulation and real V2V channel measurement data are used to evaluate the performance of the proposed method. Results show that the new method can achieve significant gains over previously proposed methods.

A Geometry-Based Stochastic Channel Model for High-Speed Railway Cutting Scenarios

The scattering issue in the channel model for a railway cutting - a man-made trough or valley that carries a railway at its base - that is applicable to high-speed railway is discussed. The scattering components are rich in cutting and can be modeled by a cluster to enhance the accuracy and efficiency of the channel model, which is based upon geometry-based stochastic channel modeling. The channel parameters are extracted from measurement data collected along the Zhengxi high-speed railway. The size of the cluster is determined by the structure of cutting and channel parameters, such as pathloss exponent and Ricean $K$ factor. A constraint condition of the cluster size is derived based upon theoretical analysis and verified by measurement data.

Design of Universal Wireless Channel Generator Accounting for the 3-D Scatter Distribution and Hardware Output

Hardware to generate the wireless channel is indispensable to the tests of wireless equipment. Previous literature always focused on the pure-hardware design, which is difficult or expensive for the small- and medium-sized enterprises. Hence, this paper presents a simple strategy to develop a flexible and low-cost channel generator, where the theoretical derivation and hardware realization are integrated together to save the test-cost and reduce the realization difficulty. In the proposed method, the fading channel is first modeled in the Agilent advanced design systems (ADS) software, and then a conventional signal generator hardware is connected and controlled to output the physical fading signal to wireless equipment waiting for measurements. Meanwhile, to cover a widerange of fading scenarios, we exploit 3-D geometry-based stochastic channel model as well as the autoregressive (AR) modeling technique. In general, for a given nonisotropic 3-D scattering environment, the angle of arrival, autocorrelation function, and level crossing rate are derived first, and then the AR coefficients are obtained by solving the Yule-Walker equation. Finally, the AR coefficients are fed to the ADS software to control the hardware generating channels. In addition, the channel model and the radio frequency parameters can be controlled by the ADS software, yielding a great flexibility. We verify the proposed method via both the computer simulation and the hardware measurement, and the simulation agrees with the theoretical result well. In addition, the physical measurements also demonstrate that the physical fading channels are consistent with the design specifications.

Modeling of Mobile Scatterer Clusters for Doppler Spectrum in Wideband Vehicle-to-Vehicle Communication Channels

This paper presents a general approach for modeling the impact of mobile scattering clusters on the Doppler spectrum in wideband Vehicle-to-Vehicle (V2V) communication channels. In the context of geometry-based stochastic channel models (GSCMs), we develop equal-delay contours for realistic modeling of location of moving scatterers in vehicular environments. Then, we utilize our developed model to simulate the taps? Doppler spectra. Numeric results demonstrate that the Doppler power spectra produced using the presented model is very close to the results obtained from measurements of V2V channels in an expressway oncoming condition. Our model can also be used in different road conditions.

Visualizing Wireless Network Performance Metrics in Space–Time

To evaluate the performance of emerging mobile wireless networks with multihop coverage extensions, spatiotemporal network models are required. These models should include the directional characteristics of network information flows to exploit the spatial domain due to the deployment of advanced antenna systems. Furthermore, the models should be capable of handling nonstationary scenarios with dynamic evolution of mobile nodes. In an attempt to solve these two problems, which have not been fully addressed in the existing literature, and motivated by the useful analogy between classical propagation channels and wireless networks, we propose a novel network modeling framework where the relevant figure of merit (FOM) may be the received signal power, the event detection error exponent, the channel capacity, etc., depending on the network's type. We first formulate the general description methods of the framework, including the double-directional FOM impulse response, the angular spectrum, and the angular dispersion. Subsequently, we propose the ray approaches, including the geometry-based stochastic channel models (GSCMs) and the deterministic ray-tracing techniques, to support and enrich the description methods. The given analytical tools facilitate visualization of wireless network performance metrics in space–time. Due to their stochastic nature, the proposed methodology would be most useful for the design and analysis of networks featured by decentralized, randomized, and dense placement of nodes.

Wideband Measurement-Based Modeling of Inter-Vehicle Channels in the 5-GHz Band

In this paper, we describe a new wideband single-input-single-output (SISO) channel model for vehicle-to-vehicle (V2V) channels, based on an extensive measurement campaign carried out at 5.2 GHz around Helsinki, Finland, in August 2007. Both the currently well-known non-stationary behavior and the measured characteristics of the V2V channel motivate the use of a geometry-based stochastic channel modeling (GSCM) approach rather than a classical tapped delay line (TDL) approach. For the time-variant contributions stemming from discrete scatterers, the propagation distance can be deterministically estimated (i.e., geometrically), whereas the fading can be modeled as the combination of a distance-decaying process and two stochastic small- and large-scale processes. The complete parameterization of the V2V wideband channel model, the recipe for its implementation, and the analysis of its validity are also provided in this paper.

The COST 2100 Channel Model: Parameterization and Validation Based on Outdoor MIMO Measurements at 300 MHz

The COST 2100 channel model is a geometry-based stochastic channel model (GSCM) for multiple-input multiple-output (MIMO) simulations. This paper presents parameterization and validation of the channel model for peer-to-peer communication in the 300 MHz band. Measurements were carried out in outdoor environments for both line-of-sight (LOS) and non line-of-sight (NLOS) scenarios. The COST 2100 channel model is characterized and parameterized based on clusters. The KpowerMeans algorithm and a Kalman filter are used for identifying and tracking clusters from measurements. General issues regarding the parameterization of the channel model are analyzed in detail. A full set of single-link parameters for the channel model is extracted from the measurements. These parameters are used as the input to the channel model validation processes, targeting delay spread, spatial correlation, and singular value distribution as well as antenna correlation. The validation results show good agreement for the spatial correlation and singular value distribution between the channel model simulations and the 300 MHz outdoor measurements. Our findings suggest that the model has potential for modeling 300 MHz channels in outdoor environments, although some modifications are needed for the distribution of cluster delay spreads and the size of cluster visibility regions.

Dynamic Channel Modeling Using Particle Filtering for Wireless MIMO Systems in Urban Environment

MIMO transmission technologies have become an essential component of cellular systems such as Long Term Evolution (LTE) and LTE-Advanced. Recently, evaluating the communication performance of mobile users in cellular MIMO systems has become an urgent requirement. In this paper, we propose dynamic MIMO channel modeling for the urban environment. Our proposal is based on Geometry-based Stochastic Channel Modeling (GSCM). The cluster parameters such as the local scatterer locations around the measurement course are estimated by applying the particle filtering to measured data. We carried out radio propagation measurements in an urban environment at 3.35GHz band, and generated the dynamic channel from the measured data. The experiments showed that both the spreads and auto-correlation of Time of Arrival (ToA), Angle of Arrival (AoA) and Angle of Departure (AoD) were reconstructed within the acceptable error range in our dynamic channel model.

The COST 2100 MIMO channel model

The COST 2100 channel model is a geometry- based stochastic channel model (GSCM) that can reproduce the stochastic properties of MIMO channels over time, frequency, and space. In contrast to other popular GSCMs, the COST 2100 approach is generic and flexible, making it suitable to model multi-user or distributed MIMO scenarios. In this article a concise overview of the COST 2100 channel model is presented. Main concepts are described, together with useful implementation guidelines. Recent developments, including dense multipath components, polarization, and multi-link aspects, are also discussed.

Review of wideband MIMO channel measurement and modeling for IMT-Advanced systems

In October 2005, the next generation mobile communication system was officially named as the International Mobile Telecommunications-Advanced (IMT-Advanced) by the ITU Radiocommunication Sector (ITU-R). Wideband multiple input and multiple output (MIMO) channel models in multiple propagation environments are fundamental for IMT-Advanced systems and such research has been initiated since 2003. The research challenges come from the fact that the wider bandwidth (20–100 MHz) and the advanced multiple antenna technology have been proposed for the IMT-Advanced system, thus leading to higher sampling rates and multiple spatial propagation channels. In this review, four aspects of wideband MIMO channel measurement and modeling are discussed: (1) radio channel measurement procedure and equipment; (2) large scale fading models; (3) small scale fading models; and (4) MIMO channel models. In particular, the large scale fading affected by the carrier frequency is investigated for urban macrocells and it shows that the higher carrier frequency results in greater loss for non-line-of-sight (NLoS) conditions in the cities of China, for which the frequency dependent factor is 32.1. Moreover, the dense and the obviously higher buildings also lead to a larger angle spread (AS) of both the angle of arrival and angle of departure in urban macrocell scenarios. The results indicate that there is the potential to explore the MIMO technique for an IMT-Advanced system with larger ASs, which would lead to the high system capacity. The progress on MIMO models is described and some methods for simplifying geometry-based stochastic channel models (GBSM) are proposed. Finally future research topics on channel measurement and modeling are identified.

Multi-Link MIMO Channel Modeling Using Geometry-Based Approach

Geometry-based stochastic channel models (GSCMs) are extended to support multi-link simulations by applying the concept of common clusters. This novel approach aims to control the correlation between different links, inter-link correlation, by adjusting the amount of power simultaneously propagating via the same clusters in the different links. The behavior of common clusters is analyzed based on dual-link channel measurements, and a multi-link GSCM is developed based on common clusters. In addition, the effects that the common clusters have on inter-link correlation and on sum rate capacity are investigated based on simulations. Finally, comparison between simulations and measurements is done in order to indicate the validity of the proposed multi-link GSCM.

Movement of Equivalent Scatterers in Geometry-Based Stochastic Channel Models

Channel models are widely used to test receiver algorithms and, therefore, should model the propagation behavior as completely as possible. A promising type of channel model is the geometry-based stochastic channel model (GSCM), which represents the propagation channel by placing equivalent scatterers (ES) within a simulated geometry. Each of these ES is associated to a propagation path between the transmitter and the receiver. The propagation length of a modeled path can be calculated in a straightforward manner knowing the ES, the transmitter, and receiver locations by simple distance calculations. If the receiver is moving, an ES may change its location in order to model a propagation path accurately. However, this movement has not been sufficiently taken into account so far. Within this contribution, we show that the movement of an ES lies on a trajectory described by an ellipse or hyperbola when the receiver is in motion. Based on this derivation, a modeling approach for a propagation path resulting from multiple reflections is given, where at least one reflector is geometrically static in its position. Our description supports the simulation of an arbitrary receiver movement. Finally, we provide an example from an outdoor-to-indoor measurement campaign that confirms the movement of the ES.

Geometry-Based Stochastic Modeling for MIMO Channel in High-Speed Mobile Scenario

The geometry-based stochastic channel models are proposed in this paper for the terrain cutting, suburb, and urban scenarios in high-speed railway. First, the special scenarios in high-speed railway are described. And the channel models based on the geometry scenarios are introduced. Some channel parameters are based on measurement data. Then, the space-time correlation functions in analytical form are obtained in suburb and urban scenarios. Finally, the space correlation characteristics in three scenarios are compared.

Modeling the Ultra-Wideband Outdoor Channel: Model Specification and Validation

In this paper we establish a geometry-based stochastic ultra-wideband channel model for gas stations. We statistically describe the two-dimensional spatial location and power of clustered scatterers, and the shape of their visibility and shadowing regions. We also separately model the diffuse part of the impulse response (i.e., the part that cannot be explained by the scatterers' multipath components), and show that its amplitude fading statistics can be best described by a Weibull distribution with a delay dependent beta-parameter. A step-by-step implementation recipe demonstrates how the model can be built. Finally, we validate our model by comparing simulated and measured channel parameters such as the rms delay spread.

A geometry-based stochastic MIMO model for vehicle-to-vehicle communications

Vehicle-to-vehicle (VTV) wireless communications have many envisioned applications in traffic safety and congestion avoidance, but the development of suitable communications systems and standards requires accurate models for the VTV propagation channel. In this paper, we present a new wideband multiple-input-multiple-output (MIMO) model for VTV channels based on extensive MIMO channel measurements performed at 5.2 GHz in highway and rural environments in Lund, Sweden. The measured channel characteristics, in particular the nonstationarity of the channel statistics, motivate the use of a geometry-based stochastic channel model (GSCM) instead of the classical tapped-delay line model. We introduce generalizations of the generic GSCM approach and techniques for parameterizing it from measurements and find it suitable to distinguish between diffuse and discrete scattering contributions. The time-variant contribution from discrete scatterers is tracked over time and delay using a high resolution algorithm, and our observations motivate their power being modeled as a combination of a (deterministic) distance decay and a slowly varying stochastic process. The paper gives a full parameterization of the channel model and supplies an implementation recipe for simulations. The model is verified by comparison of MIMO antenna correlations derived from the channel model to those obtained directly from the measurements.