Geometry-based Statistical Model Research Articles

Analytical RS-GBSM-Based Nonstationary Low-Altitude Air-to-Air Channel Modeling over Open Area

Aerial communication is very flexible due to almost no restrictions on geographical conditions. In recent years, with the development and application of the unmanned aerial vehicle, the air-to-air communication attracts dense interests from the researchers. More accurate and precise channel modeling for air-to-air communication is a new hot topic because of its essential role in the performance evaluation of the systems. This paper presents an analytical nonstationary regular-shaped geometry-based statistical model for low-altitude air-to-air communication over an open area with considerations on ground scattering. Analytical expressions of the channel impulse response and the autocorrelation functions based on the three-ray model are derived. Based on the assumption of uniform distribution of the ground scatterers, the distributions of the channel coefficients such as time delay and path attenuation are derived, simulated, compared, and fitted. The nonstationary characteristics of the channel are observed through the time-variant distributions of the channel coefficients as well as the time-variant autocorrelated functions and time-variant Doppler power spectrum density.

Geometry-Based Statistical Modeling of Non-WSSUS Mobile-to-Mobile Rayleigh Fading Channels

In this paper, we present a novel geometry-based statistical model for small-scale non-wide-sense stationary uncorrelated scattering (non-WSSUS) mobile-to-mobile (M2M) Rayleigh fading channels. The proposed model builds on the principles of plane wave propagation to capture the temporal evolution of the propagation delay and Doppler shift of the received multipath signal. This is different from existing non-WSSUS geometry-based statistical channel models, which are based on a spherical wave propagation approach, that in spite of being more realistic is more mathematically intricate. By considering an arbitrary geometrical configuration of the propagation area, we derive general expressions for the most important statistical quantities of nonstationary channels, such as the first-order probability density functions of the envelope and phase, the four-dimensional (4-D) time-frequency correlation function (TF-CF), local scattering function (LSF), and time-frequency-dependent delay and Doppler profiles. We also present an approximate closed-form expression of the channel's 4-D TF-CF for the particular case of the geometrical one-ring scattering model. The obtained results provide new theoretical insights into the correlation and spectral properties of non-WSSUS M2M Rayleigh fading channels.

A Novel Geometrical Model for Non-Stationary MIMO Vehicle-to-Vehicle Channels

A novel geometry-based statistical model for non-stationary multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) Rayleigh fading channels is presented in this paper. The proposed model seeks to provide new insights into the non-stationary characteristics of MIMO V2V channels stemming from the time-varying propagation delays of the received multipath signal. To achieve this goal, the temporal evolution of the propagation delays is characterized following a simple, although theoretically sound, plane-wave propagation approach. The modelling framework presented here allows obtaining generic expressions for the space-time-frequency cross-correlation function of the MIMO V2V channel, unveiling in the process important features of the channel's correlation and stationary properties. The obtained results show that as a consequence of the time-varying character of the propagation delays, the elements of the MIMO channel matrix are non-wide-sense stationary uncorrelated scattering (non-WSSUS) random processes, as well as pairwise jointly non-wide-sense stationary (non-WSS). The particular cases where the proposed MIMO V2V channel model can be considered quasi-WSS are also discussed for the sake of completeness.

Modeling of Non-WSSUS Double-Rayleigh Fading Channels for Vehicular Communications

This paper deals with the modeling of nonstationary time-frequency (TF) dispersive multipath fading channels for vehicle-to-vehicle (V2V) communication systems. As a main contribution, the paper presents a novel geometry-based statistical channel model that facilitates the analysis of the nonstationarities of V2V fading channels arising at a small-scale level due to the time-varying nature of the propagation delays. This new geometrical channel model has been formulated following the principles of plane wave propagation (PWP) and assuming that the transmitted signal reaches the receiver antenna through double interactions with multiple interfering objects (IOs) randomly located in the propagation area. As a consequence of such interactions, the first-order statistics of the channel model’s envelope are shown to follow a worse-than-Rayleigh distribution; specifically, they follow a double-Rayleigh distribution. General expressions are derived for the envelope and phase distributions, four-dimensional (4D) TF correlation function (TF-CF), and TF-dependent delay and Doppler profiles of the proposed channel model. Such expressions are valid regardless of the underlying geometry of the propagation area. Furthermore, a closed-form solution of the 4D TF-CF is presented for the particular case of the geometrical two-ring scattering model. The obtained results provide new theoretical insights into the correlation and spectral properties of small-scale nonstationary V2V double-Rayleigh fading channels.

Geometry-Based Statistical Model for the Temporal, Spectral, and Spatial Characteristics of the Land Mobile Channel

The main drawback of channel models presented in the literature is the lack of physically justified integration of all basic phenomena such as fluctuations, channel dispersion, and selective fading that occur in the actual radio channels. Based on physical premises, presented in this paper, the developed channel model reproduces all basic phenomena that affect the temporal, correlational–spectral, and spatial characteristics of the modelled radio channels. This effect is achieved by the structure of the model, which includes both the geometric channel model and statistical models of the received signal parameters. The geometry used in the model is based on the Parsons–Bajwa multi-elliptical model and the relationship, which describes the Doppler frequency as a function of the spatial position of object. Therefore, this model is called the Doppler multi-elliptical channel model (DMCM). The source of input data that define the geometric and statistical parameters of the model is the power delay profile or the power delay spectrum. This makes sure that DMCM characteristics depend on the properties of the modelled propagation environment. A comparative analysis of the simulation results and the measurements that DMCM can correctly capture the actual transmission properties of real channels.

Modeling Decentralized Wireless Relay Networks: Information Azimuth Spectrum and Relay Network Tomography

A novel representation for a two-hop decentralized wireless relay network (DWRN) is proposed, where the relays operate in a completely distributive fashion. The modeling paradigm applies an analogous approach to the description method for double-directional multipath propagation channels and takes into account finite system spatial resolution and extended relay listening/transmitting time. Specifically, the double- and single-directional information azimuth spectra (IAS) are formulated to provide a compact representation of information flows in the DWRN. The proposed analytical framework is then studied from a geometry-based statistical modeling perspective. Finally, we look into the problem of relay network tomography (RNT), which solves an inverse problem to infer the internal structure of an unknown relay network by using the double-directional IAS recorded at multiple measuring nodes exterior to the relay region. Numerical examples are presented to demonstrate the efficacy of the suggested channel description method and the RNT algorithm.

Statistical Modeling of MIMO Mobile-to-Mobile Underwater Channels

This paper proposes a geometry-based statistical model for wideband multiple-input-multiple-output (MIMO) mobile-to-mobile (M-to-M) shallow-water acoustic (SWA) multipath fading channels. Based on the reference model, the corresponding MIMO time-frequency correlation function, Doppler power spectral density, and delay cross-power spectral density are derived. These statistics are important tools for the design and performance analysis of MIMO M-to-M SWA communication and sonar systems. Finally, the derived statistics are compared with the experimentally obtained channel statistics, and close agreement is observed.

Human respiration rate estimation using ultra-wideband distributed cognitive radar system

It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare, rescue, and security applications. In this paper, we first present a multi-ray propagation model for UWB signal, which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces. A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment. This model enables replication of time-varying multipath profiles due to the displacement of a human chest. Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate. The analytical framework can serve as a basis in the planning and evaluation of future measurement programs. We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture.

Impact of fading correlations on MIMO communication systems in geometry-based statistical channel models

This paper highlights the impact of channel correlations on the capacity and performance of MIMO communications, with a focus on the so-called diagonal correlations. Based on this analysis, the limitations of simplified mathematical representations, such as the Kronecker or the diagonal-decorrelation models, are pointed out. Finally, the correlation properties of popular geometry-based statistical models are studied in order to analyze whether the correlation structure of these models can be adequately represented by simplified mathematical models, as well as to quantify the errors introduced by these simplifications. With respect to channel correlations, neither the Kronecker nor the diagonal-decorrelation assumptions are good representations of the correlation structure of the investigated geometry-based statistical models. When comparing capacity and symbol error probability results, it is found that the diagonal-decorrelation model may yield significant errors on both considered metrics. The Kronecker model generally yields errors less than one order of magnitude on the symbol error rate, but relative errors on ergodic or outage capacity may be more significant.