Non-stationary Channel Model Research Articles

A Non-Stationary Channel Model for 6G Multi-UAV Cooperative Communication

This paper proposes a novel three-dimensional (3D) non-stationary multiple-unmanned aerial vehicle (multi-UAV) cooperative channel model for sixth generation (6G) wireless communication systems. In the proposed multi-UAV cooperative channel model, the channel impulse response (CIR) of sub-channel between each UAV and ground station (GS) is calculated, including line-of-sight (LoS), non-LoS (NLoS), as well as ground reflection transmissions. The relative distance and transmission relationship among sub-channels between multi-UAVs and GS are further modeled and analyzed. To simultaneously capture the cooperative non-stationarity of multi-UAV cooperative channels in space and time domains, a novel cooperation-based space-time (S-T) non-stationary algorithm is developed based on the birth-death (BD) process for the first time. Meanwhile, the UAV-related parameters, e.g., the height and 3D movement of UAVs, are considered. Some important channel statistical properties, such as space-time-frequency correlation function (STF-CF), Doppler power spectral density (DPSD), cooperative time stationary interval, and singular value spread (SVS), are obtained. Based on the simulation results, multi-UAV cooperative channel statistical properties are analyzed. Finally, the simulation results match well with the ray-tracing results, which validates the accuracy of the proposed multi-UAV channel model.

A Non-Stationary Channel Model for Aerial Intelligent Reflecting Surface With 3D Continuously Arbitrary Trajectory

A Non-Stationary Channel Model for Aerial Intelligent Reflecting Surface With 3D Continuously Arbitrary Trajectory

A Non-Stationary Cluster-Based Channel Model for Low-Altitude Unmanned-Aerial-Vehicle-to-Vehicle Communications

Under the framework of sixth-generation (6G) wireless communications, the unmanned aerial vehicle (UAV) plays an irreplaceable role in a number of communication systems. In this paper, a novel cluster-based low-altitude UAV-to-vehicle (U2V) non-stationary channel model with uniform planar antenna arrays (UPAs) is proposed. In order to comprehensively model the scattering environment, both single and twin clusters are taken into account. A novel continuous cluster evolution algorithm that integrates time evolution and array evolution is developed to capture channel non-stationarity. In the proposed algorithm, the link between the time evolution of twin clusters and that of single clusters is established to regulate the temporal evolution trend. Moreover, an improved observable radius method is applied to UPAs for the first time to describe array evolution. Based on the combination of cluster evolution and time-variant channel parameters, some vital statistical properties are derived and analyzed, including space–time correlation function (ST-CF), angular power spectrum density (PSD), Doppler PSD, Doppler spread (DS), frequency correlation function (FCF), and delay spread (RS). The non-stationarity in the time, space, and frequency domain is captured. It demonstrates that the airspeed, density of scatterers within clusters, and carrier frequency have an impact on statistical properties. Furthermore, twin clusters have more flexible spatial characteristics with lower power than single clusters. These conclusions can provide assistance and reference for the design and deployment of 6G UAV communication systems.

A realistic 3D non-stationary channel model for UAV-to-vehicle communications incorporating fuselage posture

A realistic 3D non-stationary channel model for UAV-to-vehicle communications incorporating fuselage posture

A Non-Stationary Model With Time-Space Consistency for 6G Massive MIMO mmWave UAV Channels

In this paper, a novel unmanned aerial vehicle (UAV) space-time-frequency (S-T-F) non-stationary channel model with time-space consistency for sixth generation (6G) massive multiple-input multiple-output (MIMO) millimeter wave (mmWave) wireless communication systems is proposed. In the proposed model, the line-of-sight (LoS) transmission and non-LoS (NLoS) transmission through ground reflection, single-clusters, and twin-clusters are modeled. Meanwhile, the three-dimensional (3D) continuously arbitrary trajectory and the self-rotation of UAV are imitated. To capture the time-space consistency and S-T-F non-stationarity simultaneously, a new UAV-related non-stationary modeling algorithm that integrates the visibility region (VR), frequency-dependent path gain, and survival probability is developed for the first time. In this algorithm, the UAV-related parameters are considered, including UAV’s height, 3D moving velocity, and self-rotation angles. In the proposed model, the calculation of channel impulse response (CIR) is developed, which considers the cluster density index influenced by communication scenarios, frequency, UAV’s height, and the distance between transceivers. Some important channel statistical properties, such as S-T-F correlation function (STF-CF), Doppler power spectral density (DPSD), and stationary interval, are derived. Finally, simulation results match well with ray-tracing-based results, which verifies the utility of the proposed model.

Reconfigurable Intelligent Surface for mmWave Mobile Communications: What If LoS Path Exists?

Reconfigurable intelligent surface (RIS) has been widely discussed owing to its potential in enhancing the communication performance in a low-cost and energy efficient manner. The existing research on RIS-assisted channel modeling is mainly based on the assumption of obstructed line-of-sight (LoS) path between the transceivers. However, what if the LoS path (re)appears in RIS-assisted mobile communications? This letter aims at answering this question by developing a novel non-stationary channel model for RIS auxiliary millimeter wave (mmWave) mobile systems in the presence of alternately disappearing and reappearing LoS path. Based on the proposed channel model, a transmission mode switch scheme at a base station (BS) is developed based on the time-varying location of the receiver. The mapping relationship between BS transmission mode and receiver location is derived. Numerical results are provided to verify our analysis.

A Novel 3D Non-Stationary Channel Model for 6G Indoor Visible Light Communication Systems

The visible light communication (VLC) technology has attracted much attention in the research of the sixth generation (6G) communication systems. In this paper, a novel three dimensional (3D) space-time-frequency non-stationary geometry-based stochastic model (GBSM) is proposed for indoor VLC channels. The proposed VLC GBSM can capture unique indoor VLC channel characteristics such as the space-time-frequency non-stationarity caused by large light-emitting diode (LED) arrays in indoor scenarios, long travelling paths, and large bandwidths of visible light waves, respectively. In addition, the proposed model can support special radiation patterns of LEDs, 3D translational and rotational motions of the optical receiver (Rx), and can be applied to angle diversity receivers (ADRs). Key channel properties are simulated and analyzed, including the space-time-frequency correlation function (STFCF), received power, root mean square (RMS) delay spread, and path loss (PL). Simulation results verify the space-time-frequency non-stationarity in indoor VLC channels. In addition, the influence of light source radiation patterns, receiver rotations, and ADRs on channel characteristics have been investigated. Finally, the accuracy and practicality of the proposed model are validated by comparing the simulation result of channel 3dB bandwidth with the existing measurement data. The proposed channel model will play a supporting role in the design of future 6G VLC systems.

Channel Characterization for Hyperloops Using the Nonstationary Geometry-Based Model

As a novel means of high-speed transportation, the Hyperloop can proceed at an ultra-high speed (more than 1000 km/h) in the long and narrow pipelines. In this paper, the channel characteristic of the Hyperloop wireless communication systems is the main objective. Based on the geometric scattering theories, a novel nonstationary channel model is proposed to investigate the channel characteristics for Hyperloop train-to-ground communications. According to this model, the channel impulse response (CIR) is obtained, and the closed-form expressions of the multi-link spatial-temporal correlation functions, including the spatial cross-correlation function (CCF) and the temporal autocorrelation function (ACF) are derived and analyzed. Simulation results show that a high correlation between the multi-link channels in vacuum tube scenario can be observed. The relevant research results will contribute to the design of future Hyperloop wireless communication system.

Map-Based Channel Modeling and Generation for U2V mmWave Communication

Unmanned aerial vehicle (UAV) aided millimeter wave (mmWave) technologies have a promising prospect in the future communication networks. By considering the factors of three-dimensional (3D) scattering space, 3D trajectory, and 3D antenna array, a non-stationary channel model for UAV-to-vehicle (U2V) mmWave communications is proposed. The computation and generation methods of channel parameters including interpath and intra-path are analyzed in detail. The inter-path parameters are calculated in a deterministic way, while the parameters of intra-path rays are generated in a stochastic way. The statistical properties are obtained by using a Gaussian mixture model (GMM) on the massive ray tracing (RT) data. Then, a modified method of equal areas (MMEA) is developed to generate the random intra-path variables. Meanwhile, to reduce the complexity of RT method, the 3D propagation space is reconstructed based on the user-defined digital map. The simulated and analyzed results show that the proposed model and generation method can reproduce non-stationary U2V channels in accord with U2V scenarios. The generated statistical properties are consistent with the theoretical and measured ones as well.

Time-Domain Nonstationary Channel Emulation in Multiprobe Anechoic Chamber Setups for Over-the-Air Testing

ThThis letter proposes a novel four-dimensional multi-probe anechoic chamber (4D-MPAC) method for emulating time-domain non-stationary channel models of over-the-air (OTA) testing. The proposed method adds time dimension to the 3D-MPAC system, so that the channel model with spatial parameters changing over time can be emulated. In addition, 4D power angular spectrum similarity percentage (4D-PSP) as a figure of merit to evaluate the accuracy of the channel reconstruction is proposed for the first time. Based on the 4D-PSP, genetic algorithm (GA) is designed to reduce the number of active probes and testing cost. Furthermore, a dynamic motion scenario in a street is modeled by ray tracing simulation, where the time-domain non-stationary channel model is reconstructed by the proposed method with a small number of probes.

3D Non-Stationary Wideband UAV-to-Ground MIMO Channel Models Based on Aeronautic Random Mobility Model

A commonly used assumption in the existing unmanned aerial vehicle (UAV) channel models is that the UAV flies along linear trajectories. However, this assumption does not always hold in realistic UAV communication scenarios. In this paper, we relax the linear trajectory restriction and present a temporally non-stationary channel model for UAV-to-ground communication scenario. The temporal non-stationarity of the channel stemming from time-varying heading directions of the UAV is properly modeled. This is achieved by combining a geometry-based stochastic model (GBSM) and an aeronautic random mobility model (RMM), which is introduced to characterize the movement pattern of UAVs. Based on UAV and ground station (GS) trajectories, time-varying model parameters and statistics including space-time-frequency correlation function (STF-CF), Doppler power spectrum density (PSD), delay PSD, and stationary interval are derived. The influences of the RMM-related parameters on the statistics are presented and analyzed. Some of those statistics are verified by measurements, showing the practicability of the model. The work presented in this paper is helpful in designing UAV communication system considering realistic UAV trajectories.

A Non-Stationary Geometry-Based MIMO Channel Model for Millimeter-Wave UAV Networks

Unmanned aerial vehicle (UAV) communications are expected to play a major role in future space-air-ground integrated networks (SAGINs). In this paper, a geometric three-dimensional (3D) non-stationary channel model operating at millimeter-wave (mmWave) band is proposed for wideband UAV multiple-input multiple-output (MIMO) communications based on a multiple-layer cylinder reference model, where both stationary and moving clusters around transmitter (Tx) and receiver (Rx) are considered. Unlike the existing UAV-based GBSMs, the proposed model considers both local and far clusters in the propagation environments. On this basis, a continuous-time Markov model with two states is used to model the dynamic properties of clusters (i.e., clusters appear/disappear with time), and the closed-form expressions of the survival probabilities of clusters are derived. Furthermore, we derive and investigate some significant statistical properties, including space-time-frequency correlation function, quasi-stationary interval, and Doppler power spectrum. Numerical results show that the local mobile cluster (LMC) component leads to higher time correlation compared with the local stationary cluster (LSC) component. In addition, it is found that the LMC component leads to larger quasi-stationary interval compared with the LSC component. Finally, it is found that the motion of transceivers and clusters, and the changes of carrier frequency introduce significant fluctuations in Doppler power spectrum. These observations and conclusions can be considered as a guidance for mmWave UAV MIMO system design.

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.

A 3D Non-Stationary Channel Model for 6G Wireless Systems Employing Intelligent Reflecting Surfaces With Practical Phase Shifts

In this paper, a three-dimensional (3D) geometry-based stochastic model (GBSM) for a massive multiple-input multiple-output (MIMO) communication system employing practical discrete intelligent reflecting surface (IRS) is proposed. The proposed channel model supports the scenario where both transceivers and environments move. The evolution of clusters in the space domain and the practical discrete phase shifts are considered in the channel model. The steering vector is set at the base station for the cooperation with IRS. Through studying statistical properties, the non-stationary properties are verified. We find that IRS plays a role in separating the whole channel and makes the absolute value of time autocorrelation function (ACF) larger than the situation without employing IRS. Time ACF of the case using discrete phase shifts is also compared with the continuous case.

A non-stationary relay-based 3D MIMO channel model with time-variant path gains for human activity recognition in indoor environments

Extensive research showed that the physiological response of human tissue to exposure to low-frequency electromagnetic fields is the induction of an electric current in the body segments. As a result, each segment of the human body behaves as a relay, which retransmits the radio-frequency (RF) signal. To investigate the impact of this phenomenon on the Doppler characteristics of the received RF signal, we introduce a new three-dimensional (3D) non-stationary channel model to describe the propagation phenomenon taking place in an indoor environment. Here, the indoor space is equipped with a multiple-input multiple-output (MIMO) system. A single person is moving in the indoor space and is modelled by a cluster of synchronized moving point scatterers, which behave as relays. We derive the time-variant (TV) channel transfer function (CTF) with TV path gains and TV path delays. The expression of the TV path gains is obtained from the instantaneous total received power at the receiver side. This TV total received power is expressed as the product of the TV power of the RF signal initially transmitted and received by a body segment and the TV received power of the redirected signal. These TV powers are determined according the free-space path-loss model. Also, a closed-form approximate solution to the spectrogram of the TVCTF is derived. Here, we analyse the effect of the motion of the person and the validity of the relay assumption on the spectrogram, the TV mean Doppler shift (MDS), and the TV Doppler shift (DS) of the TVCTF. Simulation results are presented to illustrate the proposed channel model.

Analytical Nonstationary 3D MIMO Channel Model for Vehicle-to-Vehicle Communication on Slope

Vehicle-to-vehicle communication plays a strong role in modern wireless communication systems, appropriate channel models are of great importance in future research, and propagation environment with slope is one special kind. In this study, a novel three-dimensional nonstationary multiple-input multiple-output channel model for the sub-6 GHz band is proposed. This model is a regular-shaped multicluster geometry-based analytical model, and it combines the line-of-sight component and multicluster scattering rays as the nonline-of-sight components. Each cluster of scatterers represents the influence of different moving vehicles on or near a slope, and scatterers are, respectively, distributed within two spheres around the transmitter and the receiver. In this model, it is considered that the azimuth and elevation angles of departure and arrival are jointly distributed and conform to the von Mises–Fisher distribution, which can easily control the range and concentration of the scatterers within spheres to mimic the real-world situation well. Moreover, the impulse response and the autocorrelation function of the corresponding channel is derived and proposed; then, the Doppler power spectrum density of the channel is simulated and analyzed. In addition, the nonstationary characteristics of the presented channel model are observed through simulations. Finally, the simulation results are compared with measurement data in order to validate the utility of the proposed model.

A Trajectory-Driven 3D Non-Stationary mm-Wave MIMO Channel Model for a Single Moving Point Scatterer

This paper proposes a new non-stationary three-dimensional (3D) channel model for a physical millimeter wave (mm-Wave) multiple-input multiple-output (MIMO) channel. This MIMO channel model is driven by the trajectory of a moving point scatterer, which allows us to investigate the impact of a single moving point scatterer on the propagation characteristics in an indoor environment. Starting from the time-variant (TV) channel transfer function, the temporal behavior of the proposed non-stationary channel model has been analyzed by studying the TV micro-Doppler characteristics and the TV mean Doppler shift. The proposed channel model has been validated by measurements performed in an indoor environment using a MIMO radar kit operating at 24 GHz. For the measurement campaign, we used a single swinging pendulum as a model for a moving point scatterer. The trajectory of the pendulum has been captured by an inertial measurement unit attached to the pendulum and by a motion capture camera system. The measured trajectories are fed into the proposed mm-Wave MIMO channel model. The results obtained for the micro-Doppler characteristics show an excellent agreement between the proposed MIMO channel model and real-world measured channels in the presence of a moving point scatterer. We believe that our model can serve as a basis for the development of novel non-stationary MIMO channel models capturing the effects caused by moving objects and people.

A Trajectory-Driven 3D Channel Model for Human Activity Recognition

This paper concerns the design, analysis, and simulation of a 3D non-stationary channel model fed with inertial measurement unit (IMU) data. The work in this paper provides a framework for simulating the micro-Doppler signatures of indoor channels for human activity recognition by using radio-frequency-based sensing technologies. The major human body segments, such as wrists, ankles, torso, and head, are modelled as a cluster of moving point scatterers. We provide expressions for the time variant (TV) speed and TV angles of motion based on 3D trajectories of the moving person. Moreover, we present mathematical expressions for the TV Doppler shifts and TV path gains associated with each moving point scatterer. Furthermore, a model of the non-stationary time variant channel transfer function (TV-CTF) is provided, which takes into account the effects caused by a moving person as well as fixed objects, such as furniture, walls, and ceiling. The micro-Doppler signatures of the moving person is extracted from the TV-CTF by employing the concept of the spectrogram, whose expression is also provided in closed form. Our model is confirmed by channel state information (CSI) measurements taken during walking, falling, and sitting activities. The proposed channel model is fed with IMU data that has been collected. We evaluate the micro-Doppler signature of the model and CSI measurements. The results show a good agreement between the spectrograms and the TV mean Doppler shifts of our IMU-driven channel model and the measured CSI. The proposed model enables a paradigm shift from traditional experimental-based approaches to future simulation-based approaches for the design of human activity recognition systems.

Analytical Non-Stationary Satellite to Aircraft Channel Modeling over Open Area Based on Regular Shaped Geometry-Based Stochastic Model

Channel modeling is crucial to the development and evaluation of modern wireless communication systems including satellite communication system, since there might be critical safty-of-life applications. Also, the channel model is of great importance to the performance evaluation of mobile communication systems. In recent years, encouraged by the widely application of unmanned aerial vehicles, the research on channel modeling for aerial and aeronautical communications attract lots of interests. In the published articles, stationary and non-stationary channel models have been developed for air-to-ground communications based on regular shaped geometry-based stochastic model (RS-GBSM). The modeling of air-to-air or satellite-to-aircraft (S2A) communication is still quite simple or completely lacking. For obtaining more precise model of S2A channel, this paper presents an analytical non-stationary S2A channel mode based on RS-GBSM with considerations on line-of-sight path, specular reflection path, and ground scattering path. Analytical expressions of the channel impulse responses, the transfer functions, the auto-correlation functions, and the Doppler power spectrum density based on 3-path model are derived and simulated. Also, the distributions of the path antennation, the path delay, and the normalized Doppler shift based on uniform distribution of the scatterers are derived, simulated and fitted.

Analysis of Non-Stationary 3D Air-to-Air Channels Using the Theory of Algebraic Curves

Non-stationary channel models play a crucial role in today’s communication systems. Mobile-to-mobile channels are known to exhibit non-stationary behavior caused by the movement of transmitter and receiver. Non-stationarity can be addressed by introducing time-variant stochastic functions such as the time-variant instantaneous Doppler probability density function or time-variant instantaneous characteristic function. An algebraic analysis of the time-variant Doppler probability density function (pdf) in a classical Cartesian coordinate system is only numerically tractable due to trigonometric functions in the resulting expressions. In contrast, it has been shown that by using prolate spheroidal coordinates for 2D vehicle-to-vehicle channels the algebraic analysis becomes analytically tractable. In this paper, the analysis is extended to air-to-air channels. It is shown that the time-variant Doppler pdf can be represented without trigonometric functions. The description of the Doppler frequency in prolate spheroidal coordinates allows describing it as an algebraic curve. This permits the use of algebraic methods to analyze the Doppler frequency and derive the boundaries of the resulting Doppler pdf. Using the developed tools, we have investigated exemplary air-to-air scenarios. However, the methodology can be extended to any air-to-air configuration.