A Correlation-Based Stochastic Model for Massive MIMO Channel

In this paper,the channel impulse response matrix(CIRM)can be expressed as a sum of couplings between the steering vectors at the base station(BS)and the eigenbases at the mobile station(MS).Nakagami distribution was used to describe the fading of the coupling between the steering vectors and the eigenbases.Extensive measurements were carried out to evaluate the performance of this proposed model.Furthermore,the physical implications of this model were illustrated and the capacities are analyzed.In addition,the azimuthal power spectrum(APS)of several models was analyzed.Finally,the channel hardening effect was simulated and discussed.Results showed that the proposed model provides a better fit to the measured results than the other CBSM,i.e.,Weichselberger model.Moreover,the proposed model can provide better tradeoff between accuracy and complexity in channel synthesis.This CIRM model can be used for massive MIMO design in the future communication system design.

Statistical Channel Modeling for Indoor VLC Communications Based on Channel Measurements

Visible light communication(VLC)has attracted much attention in the research of sixthgeneration(6G)systems.Furthermore,channel modeling is the foundation for designing efficient and robust VLC systems.In this paper,we present extensive VLC channel measurement campaigns in indoor environments,i.e.,an office and a corridor.Based on the measured data,the large-scale fading characteristics and multipath-related characteristics,including omnidirectional optical path loss(OPL),K-factor,power angular spectrum(PAS),angle spread(AS),and clustering characteristics,are analyzed and modeled through a statistical method.Based on the extracted statistics of the above-mentioned channel characteristics,we propose a statistical spatial channel model(SSCM)capable of modeling multipath in the spatial domain.Furthermore,the simulated statistics of the proposed model are compared with the measured statistics.For instance,in the office,the simulated path loss exponent(PLE)and the measured PLE are 1.96and 1.97,respectively.And,the simulated medians of AS and measured medians of AS are 25.94°and 24.84°,respectively.Generally,the fact that the simulated results fit well with measured results has demonstrated the accuracy of our SSCM.

Simple analytical model for depth-averaged velocity in meandering compound channels

A simple but applicable analytical model is presented to predict the lat- eral distribution of the depth-averaged velocity in meandering compound channels. The governing equation with curvilinear coordinates is derived from the momentum equation and the flow continuity equation under the condition of quasi-uniform flow. A series of experiments are conducted in a large-scale meandering compound channel. Based on the experimental data, a magnitude analysis is carried out for the governing equation, and two lower-order shear stress terms are ignored. Four groups of experimental data from different sources are used to verify the predictive capability of this model, and good predictions are obtained. Finally, the determination of the velocity parameter and the limitation of this model are discussed.

A Non-Stationary Beam-Enabled Stochastic Channel Model and Characterization over Non-Reciprocal Beam Patterns

The multiple-input multiple-output(MIMO)-enabled beamforming technology offers great data rate and channel quality for next-generation communication.In this paper,we propose a beam channel model and enable it with time-varying simulation capability by adopting the stochastic geometry theory.First,clusters are generated located within transceivers'beam ranges based on the Mate?rn hardcore Poisson cluster process.The line-of-sight,singlebounce,and double-bounce components are calculated when generating the complex channel impulse response.Furthermore,we elaborate on the expressions of channel links based on the propagation-graph theory.A birth-death process consisting of the effects of beams and cluster velocities is also formulated.Numerical simulation results prove that the proposed model can capture the channel non-stationarity.Besides,the non-reciprocal beam patterns yield severe channel dispersion compared to the reciprocal patterns.

A Hybrid Cybersecurity Algorithm for Digital Image Transmission over Advanced Communication Channel Models

The efficient transmission of images,which plays a large role inwireless communication systems,poses a significant challenge in the growth of multimedia technology.High-quality images require well-tuned communication standards.The Single Carrier Frequency Division Multiple Access(SC-FDMA)is adopted for broadband wireless communications,because of its low sensitivity to carrier frequency offsets and low Peak-to-Average Power Ratio(PAPR).Data transmission through open-channel networks requires much concentration on security,reliability,and integrity.The data need a space away fromunauthorized access,modification,or deletion.These requirements are to be fulfilled by digital image watermarking and encryption.This paper ismainly concerned with secure image communication over the wireless SC-FDMA systemas an adopted communication standard.It introduces a robust image communication framework over SC-FDMA that comprises digital image watermarking and encryption to improve image security,while maintaining a high-quality reconstruction of images at the receiver side.The proposed framework allows image watermarking based on the Discrete Cosine Transform(DCT)merged with the Singular Value Decomposition(SVD)in the so-called DCT-SVD watermarking.In addition,image encryption is implemented based on chaos and DNA encoding.The encrypted watermarked images are then transmitted through the wireless SC-FDMA system.The linearMinimumMean Square Error(MMSE)equalizer is investigated in this paper to mitigate the effect of channel fading and noise on the transmitted images.Two subcarrier mapping schemes,namely localized and interleaved schemes,are compared in this paper.The study depends on different channelmodels,namely PedestrianAandVehicularA,with a modulation technique namedQuadratureAmplitude Modulation(QAM).Extensive simulation experiments are conducted and introduced in this paper for efficient transmission of encrypted watermarked images.In addition,different variants of SC-FDMA based on the Discrete Wavelet Transform(DWT),Discrete Cosine Transform(DCT),and Fast Fourier Transform(FFT)are considered and compared for the image communication task.The simulation results and comparison demonstrate clearly that DWT-SC-FDMAis better suited to the transmission of the digital images in the case of PedestrianAchannels,while the DCT-SC-FDMA is better suited to the transmission of the digital images in the case of Vehicular A channels.

The variation in basal channels and basal melt rates of Pine Island Ice Shelf

In recent years,there has been a significant acceleration in the thinning,calving and retreat of the Pine Island Ice Shelf(PIIS).The basal channels,results of enhanced basal melting,have the potential to significantly impact the stability of the PIIS.In this study,we used a variety of remote sensing data,including Landsat,REMA DEM,ICESat-1 and ICESat-2 satellite altimetry observations,and Ice Bridge airborne measurements,to study the spatiotemporal changes in the basal channels from 2003 to 2020 and basal melt rate from 2010 to 2017 of the PIIS under the Eulerian framework.We found that the basal channels are highly developed in the PIIS,with a total length exceeding 450 km.Most of the basal channels are ocean-sourced or groundingline-sourced basal channels,caused by the rapid melting under the ice shelf or near the groundingline.A raised seabed prevented warm water intrusion into the eastern branch of the PIIS,resulting in a lower basal melt rate in that area.In contrast,a deepsea trough facilitates warm seawater into the mainstream and the western branch of the PIIS,resulting in a higher basal melt rate in the main-stream,and the surface elevation changes above the basal channels of the mainstream and western branch are more significant.The El Ni?o event in 2015–2016 possibly slowed down the basal melting of the PIIS by modulating wind field,surface sea temperature and depth seawater temperature.Ocean and atmospheric changes were driven by El Ni?o,which can further explain and confirm the changes in the basal melting of the PIIS.

Novel Sum-of-Sinusoids Simulation Channel Modeling for 6G Multiple-Input Multiple-Output Vehicle-to-Everything Communications

In this paper,a statistical cluster-based simulation channel model with a finite number of sinusoids is proposed for depicting the multiple-input multiple-output(MIMO)communications in vehicleto-everything(V2X)environments.In the proposed sum-of-sinusoids(SoS)channel model,the waves that emerge from the transmitter undergo line-of-sight(LoS)and non-line-of-sight(NLoS)propagation to the receiver,which makes the model suitable for describing numerous V2X wireless communication scenarios for sixth-generation(6G).We derive expressions for the real and imaginary parts of the complex channel impulse response(CIR),which characterize the physical propagation characteristics of V2X wireless channels.The statistical properties of the real and imaginary parts of the complex CIRs,i.e.,autocorrelation functions(ACFs),Doppler power spectral densities(PSDs),cross-correlation functions(CCFs),and variances of ACFs and CCFs,are derived and discussed.Simulation results are generated and match those predicted by the underlying theory,demonstrating the accuracy of our derivation and analysis.The proposed framework and underlying theory arise as an efficient tool to investigate the statistical properties of 6G MIMO V2X communication systems.

Detecting DNS Covert Channels Using Stacking Model

A covert channel is an information channel that is used by the computer process to exfiltrate data through bypassing security policies.The DNS protocol is one of the important ways to implement a covert channel.DNS covert channels are easily used by attackers for malicious purposes.Therefore,an effective detection approach of the DNS covert channels is significant for computer systems and network securities.Aiming at the difficulty of the DNS covert channel identification,we propose a DNS covert channel detection method based on a stacking model.The stacking model is evaluated on a campus network and the experimental results show that the detection based on the stacking model can detect the DNS covert channels effectively.Besides,it can identify unknown covert channel traffic.The area under the curve(AUC)of the proposed method reaches 0.9901,which outperforms existing detection methods.

Degree of Freedom Analysis for Holographic MIMO Based on a Mutual-Coupling-Compliant Channel Model

Degree of freedom(DOF)is a key indicator for spatial multiplexing layers of a wireless channel.Traditionally,the channel of a multiple-input multiple-output(MIMO)half-wavelength dipole array has a DOF that equals the antenna number.However,recent studies suggest that the DOF could be less than the antenna number when strong mutual coupling is considered.We utilize a mutual-coupling-compliant channel model to investigate the DOF of the holographic MIMO(HMIMO)channel and give a upper bound of the DOF with strong mutual coupling.Our numerical simulations demonstrate that a dense array can support more DOF per unit aperture as compared with a half-wavelength MIMO system.

Parametric SNR Estimation Based on Auto-Regressive Model in AWGN Channels

Signal-to-noise ratio（SNR）estimation for signal which can be modeled by Auto-regressive（AR）process is studied in this paper.First,the conventional frequency domain method is introduced to estimate the SNR for the received signal in additive white Gauss noise（AWGN）channel.Then a parametric SNR estimation algorithm is proposed by taking advantage of the AR model information of the received signal.The simulation results show that the proposed parametric method has better performance than the conventional frequency doma in method in case of AWGN channel.

SNS model for providing social network channels through queries

Users can obtain the information through a basic web searching and find the answer to the questions directly,but maybe the expected answer does not exist.Besides,we do not know the update of new information in time.The online social networking services spread quickly and store many user data,but these data are worth less and may be unreliable answer to users’ questions.Users can obtain the simple answer but can not expect more additional information in knowledge question-answering(QA)system.In this paper,we design the system with the advantages of knowledge QA system,web searching and characteristics of social networking service for providing social network channel based on the query and answer without users’ contact network.The user can obtain real-time answers by the user network interested in users’ querires through the network channel of this system,get the additional information effectively and share it with others in the social network channel in this system.

ESTIMATION OF BASIS EXPANSION MODELS FOR DOUBLY SELECTIVE CHANNELS

By analyzing the relationship between Basis Expansion Model (BEM) and Doppler spectrum, this letter proposed a quasi-MMSE-based BEM estimation scheme for doubly selective channels. Based on the assumption that the basis coefficients are approximately independent and have the same variance for the same channel tap, the quasi-MMSE estimation shows approximately optimal performance and is robust to noise. Moreover, it can avoid a high Peak-to-Average Power Ratio (PAPR) by using continuous pilots. Performance of the proposed estimation scheme has been shown with computer simulations.

Evaluating Two-Layer Models for Velocity Profiles in Open-Channels with Submerged Vegetation

For submerged vegetated flow, the velocity profile has two distinctive distributions in the vegetation layer in the lower region and the surface layer in the upper non-vegetated region. Based on a mixing-layer analogy, different analytical models have been proposed for the velocity profile in the two layers. This paper evaluates the four analytical models of Klopstra et al., Defina & Bixio, Yang et al. and Nepf against a wide range of independent experimental data available in the literature. To test the applicability and robust of the models, the author used the 19 datasets with various relative depths of submergence, different vegetation densities and bed slopes (1.8 × 10?6 - 4.0 × 10?3). This study shows that none of the models can predict the velocity profiles well for all datasets. The three models except Yang’s model performed reasonably well in certain cases, but Yang’s model failed in most the cases studied. It was also found that the Defina model is almost the same as the Klopstra model, if the same mixing length scale of eddies (λ) is used. Finally, close examination of the mixing length scale of eddies (λ) in the Defina model showed that when λ/h = 1/40(H/h)1/2, this model can predict velocity profiles well for all the datasets used.

3D non-stationary geometry-based stochastic model for unmanned aerial vehicle air-to-ground multi-input multi-output channels

A three-dimensional non-stationary geometry-based stochastic model for unmanned aerial vehicle(UAV)air-to-ground multi-input multi-output(MIMO)channels is proposed.The scatterers surrounding the UAV and ground station are assumed to be distributed on the surface of two cylinders in the proposed model.The impact of UAV rotations and accelerated motion is considered to describe channel non-stationarity.The computational methods of the corresponding time-variant parameters,such as UAV antenna array angles,time delays,and maximum Doppler frequencies,are theoretically deduced.The model is then used to derive channel statistical properties such as space-time correlation functions and Doppler power spectral density.Finally,numerical simulations are run to validate the channel s statistical properties.The simulation results show that increasing the UAV and ground station accelerations can reduce the time correlation function and increase channel non-stationarity in the time domain.Furthermore,the UAV s rotation significantly influences the spatial correlation function,with rolling having a greater influence than pitching.Similarly,the different directions of UAV movement significantly impact the Doppler power spectral density.

An Improved Non-Geometrical Stochastic Model for Non-WSSUS Vehicle-to-Vehicle Channels

A novel non-geometrical stochastic model(NGSM)for non-wide sense station ary uncorrelated scattering(non-WSSUS)vehicle-to-vehicle(V2V)channels is proposed.This model is based on a conventional NGSM and employs a more accurate method to reproduce the realistic characteristics of V2V channels,which successfully extends the existing NGSM to include the line-of-sight(LoS)component.Moreover,the statistical properties of the proposed model in different scenarios,including Doppler power spectral density(PSD),power delay profile(PDP),and the tap correlation coefficient matrix are simulated and compared with those of the existing NGSM.Furthermore,the simulation results dem onstrate not only the utility of the proposed model,but also the correctness of our theoreti cal derivations.

NUMERICAL INVESTIGATION OF THREE-DIMENSIONAL VISCOUS INCOMPRESSIBLE FLOWS IN DIVERGENT CURVED CHANNELS AND TURBULENT MODEL STUDY

In order to make the numerical calculation of viscous flows more convenient for the flows in channel with complicated profile governing equations expressed in the arbitrary curvilinear coordinates were derived by means of Favre density-weighted averaged method, and a turbulent model with effect of curvature modification was also derived. The numerical calculation of laminar and turbulent flown in divergent curved channels was carried out by means of parabolizeil computation method. The calculating results were used to analyze and investigate the aerodynamic performance of talor cascades in compressors preliminarily.

River channel flood forecasting method of coupling wavelet neural network with autoregressive model

Based on analyzing the limitations of the commonly used back-propagation neural network （BPNN）, a wavelet neural network （WNN） is adopted as the nonlinear river channel flood forecasting method replacing the BPNN. The WNN has the characteristics of fast convergence and improved capability of nonlinear approximation. For the purpose of adapting the timevarying characteristics of flood routing, the WNN is coupled with an AR real-time correction model. The AR model is utilized to calculate the forecast error. The coefficients of the AR real-time correction model are dynamically updated by an adaptive fading factor recursive least square（RLS） method. The application of the flood forecasting method in the cross section of Xijiang River at Gaoyao shows its effectiveness.

A Novel 3D Non-Stationary UAV-MIMO Channel Model and Its Statistical Properties

The wireless communication systems based on Unmanned Aerial Vehicles(UAVs) have found a wide range of applications recently. In this paper, we propose a new three-dimensional(3 D) non-stationary multiple-input multiple-output(MIMO) channel model for the communication links between the UAV and mobile terminal(MT). The new model originates the traditional geometry-based stochastic models(GBSMs) but considers the non-stationary propagation environment due to the rapid movements of the UAV, MT, and clusters. Meanwhile, the upgrade time evolving algorithms of time-variant channel parameters, i.e., the path number based on birth-death processes of clusters, path delays, path powers, and angles of arrival and departure, are developed and optimized. In addition, the statistical properties of proposed GBSM including autocorrelation function(ACF), cross-correlation function(CCF), and Doppler power spectrum density(DPSD) are investigated and analyzed. Simulation results demonstrate that our proposed model provides a good agreement on the statistical properties with the corresponding derived theoretical ones, which indicates its usefulness for the performance evaluation and validation of the UAV based communication systems.

3D Geometry-Based UAV-MIMO Channel Modeling and Simulation

A more general narrowband regular-shaped geometry-based statistical model(RS-GBSM) combined with the line of sight(LoS) and single bounce(SB) rays for unmanned aerial vehicle(UAV) multiple-input multiple-output(MIMO) channel is proposed in this paper. The channel characteristics, including space-time correlation function(STCF), Doppler power spectral density(DPSD), level crossing rate(LCR) and average fade duration(AFD), are derived based on the single sphere reference model for a non-isotropic environment. The corresponding sum-of-sinusoids(SoS) simulation models including both the deterministic model and statistical model with finite scatterers are also proposed for practicable implementation. The simulation results illustrate that the simulation models well reproduce the channel characteristics of the single sphere reference model with sufficient simulation scatterers. And the statistical model has a better approximation of the reference model in comparison with the deterministic one when the simulation trials of the stochastic model are sufficient. The effects of the parameters such as flight height, moving direction and Rice factor on the characteristics are also studied.

Channel Modeling and Performance Analysis for UAV Relay Systems

In this paper, a multi-hop relay channel model based on unmanned aerial vehicles(UAVs) is established by taking into account of the propagation loss, shadowing, and multi-path fading. Based on the proposed channel model, the cascaded propagation loss of relay link and the cascaded probability density function(PDF) of channel fading are derived. Moreover, the theoretical performance of the UAV-based relay system, i.e., the outage probability, bit error rate(BER), and channel capacity, is also analysed and derived. Simulation results show agreement with theoretical results for the hill, mountain, and sea scenarios, indicating the accuracy of both the simulations and derivations.