Channel Stationarity Research Articles

Characterization and modeling of high-speed underwater acoustic communication channels

High-speed mobile underwater acoustic communication (HSM-UAC) is a relatively unexplored terrain, but its importance is expected to increase with the widespread application of flexible underwater mobile platforms such as AUVs and UUVs. Knowledge of HSM-UAC channels is a prerequisite to achieving reliable communication. This work conducted two HSM-UAC channel measurement experiments with a maximum speed of 20knots. The analysis of channel time-varying characteristics demonstrates the shortcomings of traditional consistent Doppler frequency offset channel model. The experimental findings reveal the presence of two non-stationary modes in the HSM-UAC channel. For short moving distances, the changes in channel geometry result in each path experiencing a different Doppler scale, thus observing the multiscale-multilag (MSML) channels. For long moving distances, the alteration in sound ray propagation tracks entirely reshapes the channel impulse response (CIR) structure, leading to a rapid decline in channel time correlation. In further analysis, the correlation coefficient of the power delay profile (PDP) is used to measure channel stationarity. Subsequently, the stationary time and corresponding stationary distance are calculated as characterization parameters for the time-varying channel model. The quantitative evaluation results are helpful for the communication signal design and determining the update frequency of channel state information.

MmWave Channel Stationarity Analysis of V2X Communications in an Urban Environment

Vehicular communication channels are subject to high non-stationarity mainly characterized by the scatterers' and/or transceivers' high mobility. In this sense, this work presents a characterization of the channel quasi-stationarity regions (QSR) in a V2X generic high-dense urban environment at millimeter wave (mmWave) frequencies (28 GHz). Results are extracted from multiple snapshot simulations by means of a three-dimensional ray-launching (3D-RL) algorithm inducing the continuous mobility of the vehicles on the scene and validated with an experimental campaign of measurements in the real scenario. The average power delay profile (APDP) correlation matrix is used as a descriptor of the channel non-stationarity and the mean correlation is outlined for several thresholds. The obtained QSR results are consistent with the related works reported in the literature. Finally, the effects of these QSR in small- and large-scale parameters are assessed as per threshold considerations.

Analysis of Impulse Responses Measured in Motion in a Towing Tank

The growing interest in developing autonomous underwater vehicles (AUVs) and creating underwater sensor networks (USNs) has led to a need for communication tools in underwater environments. For obvious reasons, wireless means of communication are the most desirable. However, conducting research in real conditions is troublesome and costly. Moreover, as hydroacoustic propagation conditions change very significantly, even during the day, the assessment of proposed underwater wireless communication methods is very difficult. Therefore, in the literature, there are considered simulators based on real measurements of underwater acoustic (UWA) channels. However, these simulators make an assumption that, during the transmission of elementary signals, the impulse response does not change. In this article, the authors present the results of the measurements realized in a towing tank where the transmitter could move with a precisely set velocity and show that the analyzed channel was non-stationary, even during the time of the transmission of a single chirp signal. The article presents an evaluation method of channel stationarity at the time of the chirp transmission, which should be treated as novelty. There is also an analysis of the impulse responses measured in motion in a towing tank.

Enhancements on Type-II 5G New Radio Codebooks for UE Mobility Scenarios

This article focuses on potential enhancements of current 5G New Radio (NR) codebooks (CBs) for user equipment (UE) mobility scenarios. An overview of the incremental evolution of the 5G NR Type-II CBs is presented, and its inherent drawbacks in mobility scenarios are discussed. The current Type-II CBs fail to deliver adequate performance when used by moving UEs at medium to high speeds, mainly due to the current channel coherence time-based CSI measurement and reporting. Measured channel data from a number of real-world scenarios are analyzed by means of Doppler power spectrum and delay-Doppler power spectrum to verify the so-called channel stationarity time, which is several-fold higher than the channel coherence time. Based on the presented analysis, conclusions are drawn that for stationarity time-based CSI measurements and reporting, Doppler frequency components in addition to space and delay components can be exploited for Type-II CB enhancements. The enhanced Type-II CB achieves a drastic feedback reduction due to the sparse nature of the channel in the delay-Doppler domain and improved performance compared to the 5G NR Type-II CB.

Dual-Polarized Narrowband MIMO LMS Channel Measurements in Urban Environments

This paper presents the postprocessing results of a dual-polarized multiple-input-multiple-output (MIMO) channel measurement campaign, investigating two land mobile satellite link scenarios in urban environments. Basic channel evaluation metrics are examined to facilitate the selection of the appropriate communication technique. The ergodic channel capacity is found between 4.1 and 6.1 b/s/Hz and varies significantly with the elevation angle. The capacity is highly correlated with the terminal trajectory and signal reception. The cross-polarization discrimination (XPD) is found between 14.2 and 22.5 dB, whereas the cross-polarization isolation (XPI) is found between 12.8 and 21 dB, respectively. Furthermore, the correlation statistics and channel capacities are well approximated by existing stochastic channel models. Finally, from the channel stationarity analysis, large stationarity regions are found, the existence of which is also correlated with the terminal trajectory. The mean quasi-stationarity time is found between 41 and 66 s for different environments.

Air–Ground Channel Characterization for Unmanned Aircraft Systems—Part I: Methods, Measurements, and Models for Over-Water Settings

The use of unmanned aerial systems (UASs), which are also known as unmanned aerial vehicles, and by the term “drones” in the popular press, is growing rapidly. To ensure safety, UAS control and nonpayload communication (CNPC) links must operate very reliably in a variety of conditions. This requires an accurate quantitative characterization of the air–ground (AG) channel, and this channel characterization is the focus of this paper. After providing motivation and background, we describe our methods and modeling approach, followed by a description of our simultaneous dual-band (L-band ∼970 MHz, C-band ∼5 GHz) measurement campaign and the over-water (OW) measurement sites. Example results for path loss and root-mean-square delay spread are provided, as well as the results for channel stationarity distance (SD), used in calculating small-scale Rician $K$ - factor and correlations between the two receiver antennas that we employed in each frequency band. Two distinct SD measures—the power delay profile (PDP) correlation coefficient and the spatial autocorrelation matrix collinearity—were used and found to be of the same order. Path-loss exponents are near that of free space, but significant two-ray cancelation effects for these OW settings warrant more accurate models, which we provide. Delay spreads in the OW channels are also dominated by the two-ray components and are hence typically very small (∼10 ns) but can exceed 350 ns. A third intermittent multipath component (MPC) is also present a nonnegligible fraction of time; hence, we provide statistical wideband AG channel models to represent this. Future papers in this series will report results for the AG channel with ground sites in other types of environments.

Channel measurement and time dispersion analysis for outdoor mobile ultrawideband environment

Ultrawideband (UWB) technology offers short-range high-data transmission rates. Most researchers in recent times have focused on indoor UWB channel measurements and in instances where outdoor cases were reported, they focused on static scenarios. This paper reports on mobile outdoor channel measurements typical of roadway and recreation park Infostation scenarios. It also chronicles the delay spread as well as channel stationarity analysis of the measurement data. We carried out measurements in the 3.1{5.3 GHz frequency range in various line-of-sight scenarios. The results of this research show that the delay spread values generally decrease with increasing mobile speed. Additionally, the degree of variation in the channel statistics show that systems designed with the obtained reference parameter values will perform well on average, but with low resource utilization.

Radio channel measurements and analysis at 2.4/5GHz in subway tunnels

There is an increasing demand on wireless communications in subway tunnels to provide video surveillance and sensory data for security, maintenance and train control, and to offer various communication or entertainment services (e.g., Internet, etc.) to passengers as well. The wireless channel in tunnels is quite unique due to the confined space and the waveguide effects. Therefore, modeling the radio channel characteristics in tunnels is critically important for communication systems design or optimization. This paper investigates the key radio channel characteristics of a subway tunnel at 2.4 GHz and 5 GHz, such as the path loss, root mean square (RMS) delay spread, channel stationarity, Doppler shift, and channel capacity. The field measurements show that channel characteristics in tunnels are highly location-dependent and there exist abundant components in Doppler shift domain. In the straight section of the subway tunnel, the measured path loss exponents are close to 1.6, lower than that in free space.

Rician Modeling and Prediction for Wireless Packet Data Systems

Wireless systems exploiting multi-user diversity require accurate channel state information. In this paper we examine channel prediction as a method to improve the performance of these systems. We model the outdoor channel by the Rician model, which combines diffuse spectra with a single specular component. Prediction accuracy is determined for the Rician model given various ratios (K factors) of specular to diffuse power. Simulation results show that accurate channel prediction further than one wavelength can be achieved at 30 dB SNR when the channel K factor is greater than ten. The predictor was evaluated on measured channels, and the Rician model was found to be appropriate as prediction intervals of the measured data are similar to those of synthetic data with same K factor. Using measurements some results regarding channel stationarity and optimal filter order are presented. We show for a proportionally fair scheduled downlink packet system that the predictor reduces fade margin at fixed packet outage leading to an improvement in throughput.

A Measurement Study of Time-Scaled 802.11a Waveforms Over The Mobile-to-Mobile Vehicular Channel at 5.9 GHz

We have studied the effects of the mobile vehicle-to-vehicle (V2V) channel on scaled versions of the current IEEE 802.11 a standard to investigate how readily they can be applied to vehicular networks. In particular, measured parameters for the V2V channel at 5.9 GHz in suburban, highway, and rural environments are studied in the context of critical parameters for OFDM. Actual performance of scaled OFDM waveforms with bandwidths of 20 MHz (bandwidth of IEEE 802.11 a), 10 MHz (bandwidth of the draft IEEE 802.11 p), and 5 MHz (halved bandwidth of IEEE 802.11 p) are described and interpreted in light of the channel parameters. At 20 MHz the guard interval is not long enough, while at 5 MHz errors increase from lack of channel stationarity over the packet duration. For these choices of the scaled 802.11 a OFDM waveform, 10 MHz appears to be the best choice.

Time-frequency 2-D LMS based long-range channel prediction for wireless OFDM systems

Adaptive modulation can optimize the spectrum efficiency and system performance with the channel state information achieved by the long-range channel prediction. To avoid re-estimating channel correlation function as the channel stationarity varies and to track the channel adaptively, LMS (Least-Mean-Square) based long-range channel prediction is discussed in the existing literature, but it needs long observation interval to reach the convergence. Given that all OFDM (Orthogonal Frequency Division Multiplexing) subcarriers have the identical time-domain correlation and stationarity during the same time interval, this paper proposed a 2-D LMS based predictor which updates the filter weights in both time and frequency domain. The proposed scheme can effectively decrease the observation intervals and significantly speed up the convergence than the conventional LMS and Parallel LMS (PLMS). Complexity analysis and simulation results prove that the proposed scheme can improve the BER (Bit Error Rate) performance and spectrum efficiency with negligible complexity increase.

A Frequency Offset Estimation Technique Based on Frequency Error Characterization for OFDM Communications on Multipath Fading Channels

A novel frequency offset estimation technique based on maximum-likelihood estimation for wireless orthogonal frequency division multiplexing communications on frequency-selective fading channels is proposed. By taking advantage of subcarrier-level differential operation and coherent error characterization, the proposed estimator based on the frequency error characteristics can effectively overcome multipath fading effects. Frequency error characterization is achieved by means of pseudonoise matched filters in the frequency direction; thus, the proposed estimation technique exploits frequency diversity without assistance in the form of accurate timing information. In addition, the proposed technique can combat the rapid time selectivity caused by a wide Doppler spread because it requires channel stationarity for only a short duration due to the exploitation of both a single preamble in its training operation and the following semiblind estimation aided from several pilot subchannels. The proposed technique can easily switch between training mode and semiblind mode by sharing the same system architecture. Extensive simulation results in conjunction with statistical analysis verify the superiority of the proposed technique

A receiver-based variable-size-burst equalization strategy for spectrally efficient wireless communications

Strategies for improving spectral efficiency in wireless communications, while maintaining quality of service, are proposed. The idea is to make the communication system adapt to the encountered environment. To this end, a time-varying channel model explicitly characterizing changing environments is developed. Under this model, methods for tracking channel stationarity are proposed based on analysis of variance and minimum description length. Tracking enables efficient construction of variable-size data bursts for improved equalization at the receiver. The performance is evaluated first in a training-based equalization framework, then extended to a semi-blind situation. In either case, the obtained results demonstrate feasibility of variable-size burst construction for improving spectral efficiency. The proposed methods are applicable to burst-by-burst or block-based equalization systems, without the requirement of feedback.

MIMO Wireless Communication Channel Phenomenology

Wireless communication using multiple-input multiple-output (MIMO) systems enables increased spectral efficiency and link reliability for a given total transmit power. Increased capacity is achieved by introducing additional spatial channels which are exploited using space-time coding. The spatial diversity improves the link reliability by reducing the adverse effects of link fading and shadowing. The choice of coding and the resulting performance improvement are dependent upon the channel phenomenology. In this paper, experimental channel-probing estimates are reported for outdoor environments near the personal communication services frequency allocation (1790 MHz). A simple channel parameterization is introduced. Channel distance metrics are introduced. Because the bandwidth of the channel-probing signal (1.3 MHz) is sufficient to resolve some delays in outdoor environments, frequency-selective fading is also investigated. Channel complexity and channel stationarity are investigated. Complexity is associated with channel-matrix singular value distributions. Stationarity is associated with the stability of channel singular value and singular vector structure over time.

Blind single channel deconvolution using nonstationary signal processing

Blind deconvolution is fundamental in signal processing applications and, in particular, the single channel case remains a challenging and formidable problem. This paper considers single channel blind deconvolution in the case where the degraded observed signal may be modeled as the convolution of a nonstationary source signal with a stationary distortion operator. The important feature that the source is nonstationary while the channel is stationary facilitates the unambiguous identification of either the source or channel, and deconvolution is possible, whereas if the source and channel are both stationary, identification is ambiguous. The parameters for the channel are estimated by modeling the source as a time-varyng AR process and the distortion by an all-pole filter, and using the Bayesian framework for parameter estimation. This estimate can then be used to deconvolve the observed signal. In contrast to the classical histogram approach for estimating the channel poles, where the technique merely relies on the fact that the channel is actually stationary rather than modeling it as so, the proposed Bayesian method does take account for the channel's stationarity in the model and, consequently, is more robust. The properties of this model are investigated, and the advantage of utilizing the nonstationarity of a system rather than considering it as a curse is discussed.

Multichannel restoration of single channel images using a wavelet-based subband decomposition

We present a new matrix vector formulation of a wavelet-based subband decomposition. This formulation allows for the decomposition of both the convolution operator and the signal in the subband domain. With this approach, any single channel linear space-invariant filtering problem can be cast into a multichannel framework. We apply this decomposition to the linear space-invariant image restoration problem and propose a family of multichannel linear minimum mean square error (LMMSE) restoration filters. These filters explicitly incorporate both within and between subband (channel) relations of the decomposed image. Since only within channel stationarity is assumed in the image model, this approach presents a new method for modeling the nonstationarity of images. Experimental results are presented which test the proposed multichannel LMMSE filters. These experiments show that if accurate estimates of the subband statistics are available, the proposed multichannel filters provide major improvements over the traditional single channel filters.