Level Crossing Rate Research Articles

MDE and LLM Synergy for Network Experimentation: Case Analysis of Wireless System Performance in Beaulieu-Xie Fading and κ-µ Co-Channel Interference Environment with Diversity Combining.

Channel modeling is a first step towards the successful projecting of any wireless communication system. Hence, in this paper, we analyze the performance at the output of a multi-branch selection combining (SC) diversity receiver in a wireless environment that has been distracted by fading and co-channel interference (CCI), whereby the fading is modelled by newer Beaulieu-Xie (BX) distribution, and the CCI is modelled by the κ-µ distribution. The BX distribution provides the ability to include in consideration any number of line-of-sight (LOS) useful signal components and non-LOS (NLOS) useful signal components. This distribution contains characteristics of some other fading models thanks to its flexible fading parameters, which also applies to the κ-µ distribution. We derived here the expressions for the probability density function (PDF) and cumulative distribution function (CDF) for the output signal-to-co-channel interference ratio (SIR). After that, other performances are obtained, namely: outage probability (Pout), channel capacity (CC), moment-generating function (MGF), average bit error probability (ABEP), level crossing rate (LCR), and average fade duration (AFD). Numerical results are presented in several graphs versus the SIR for different values of fading and CCI parameters, as well as the number of input branches in the SC receiver. Then, the impact of parameters on all performance is checked. From our numerical results, it is possible to directly obtain the performance for all derived and displayed quantities for cases of previously known distributions of fading and CCI by inserting the appropriate parameter values. In the second part of the paper, a workflow for automated network experimentation relying on the synergy of Large Language Models (LLMs) and model-driven engineering (MDE) is presented, while the previously derived expressions are used for evaluation. Due to the aforementioned, the biggest value of the obtained results is the applicability to the cases of a large number of other distributions for fading and CCI by replacing the corresponding parameters in the formulas for the respective performances.

Finite-state Markov modeling of Gamma-Gamma fading FSO links with pointing errors

The knowledge of atmospheric channel is quite imperative for free-space optical (FSO) communications. To capture the time-varying essence of intensity fluctuations in an FSO connection, we propose a finite-state Markov (FSM) model for FSO links affected by Gamma-Gamma distributed atmospheric turbulence and pointing errors. First, the level crossing rate (LCR) of the unified intensity fluctuation is derived considering the non-generic channel autocorrelation characteristics, based on which the state transition probability (STP) matrix of the FSM model is calculated. Then, numerical simulations are presented for different strength parameters and frequency parameters of the channel. The results show that the misalignment strength does not affect the ratio of the level where the LCR reaches its maximum to the mean level. Finally, a series of well-designed experiments are carried out to verify the theory. As a result, the theoretical predictions conform to the experimental data, with averaged STP relative errors below 6.7%.

A Simulation Framework for Cooperative Reconfigurable Intelligent Surface-Based Systems

We present a simulation framework for evaluating the performance of cooperative reconfigurable intelligent surface (RIS) based systems, which may ultimately deploy an arbitrary number of RISs to overcome adverse propagation-related effects, such as cascaded fading. The physical model underlying the proposed framework considers the (optional) presence of a dominant signal path between the source and RIS, and then between each subsequent stage of the communication link to the destination. Accompanying the dominant signal component is a non-isotropic scattered signal contribution, which accounts for angular selectivity within the cascaded RIS stages between the source and destination. The simulation of the time-correlated scattered signal, reflected by the illuminated reflective elements, is achieved using autoregressive modelling. As a by-product of our analysis, significant insights are drawn which enable us to characterize the amplitude and phase properties of the received signal, and the associated complex autocorrelation functions (ACFs) for the product of multiple Rician channels. For both single and cooperative RIS systems, the outage probability (OP), and important second-order statistics, such as the level crossing rate (LCR) and average outage duration (AOD), are analyzed for a variety of system configurations, accounting for practical limitations, such as phase errors. It is shown that by using multiple RISs cooperatively, the AOD is reduced at a lower signal-to-noise-ratio (SNR) compared to single RIS-assisted transmission under the same operating conditions. Lastly, increased channel variations (i.e., higher maximum Doppler frequencies) are shown to decrease the AOD in the case of absent phase errors; yet, this improvement is not observed when phase errors are present.

Experimental study on low-altitude UAV-to-ground propagation characteristics in campus environment

In recent years, unmanned aerial vehicle (UAV)-to-ground wireless channels have become focused areas. Thus a better understanding of UAV-to-ground wireless channel characterizations is critical. The large-scale fading characterization is widely analyzed in many research works. Nevertheless, the small-scale fading characterization of low-altitude UAV-to-ground propagation has not been fully modeled. In this work, the close-in (CI) free space and floating-intercept (FI) path loss models are implemented to characterize large-scale fading. The large-scale parameters, i.e., path loss exponent (PLE), shadow fading standard deviation (STD), and shadow fading correlation coefficient, are carefully extracted, analyzed, and compared. Regarding small-scale fading, Akaike’s Information Criteria (AIC) is used to find the most suitable fading distribution. In addition, fade depth (FD), level crossing rate (LCR), and average fade duration (AFD) are also calculated. The quantitative results and comparisons show a noticeable difference with ground propagation. The parameterized models are helpful for further understanding and deployment of UAV-to-ground wireless communication systems.

Measurements and Characteristics Analysis of 6G Ultra-Massive MIMO Wireless Channels With Different Antenna Configurations and Scenarios

In this paper, ultra-massive multiple-input multiple-output (MIMO) channel measurements at 5.3 GHz are conducted, including different antenna array configurations and different measurement scenarios. The antenna array configurations include uniform linear array (ULA) and distributed uniform linear array (DULA). The measurement scenarios include single-user fixed-to-fixed (F2F), multi-user F2F, and single-user fixed-to-mobile (F2M) measurement scenarios. The statistical properties of ultra-massive MIMO channels are studied, including delay power spectral density (DPSD), space cross-correlation function (SCCF), angle cross-correlation function (ACCF), frequency correlation function (FCF), root mean square (RMS) delay spread (DS), RMS angle spread (AS), singular value spread (SVS), scalar product (SP), level crossing rate (LCR), average fading duration (AFD), Doppler power spectral density (PSD), etc. The specific ultra-massive MIMO channel characteristics are investigated and validated by channel measurements, including spatial non-stationarity, spherical wavefront behavior, channel hardening, and sparse properties in the angle domain. In addition, channel capacities are investigated. The channel measurement results will be a great importance for ultra-massive MIMO communication system deployments.

A Novel UAV-Assisted Multi-Mobility Channel Model for Urban Transportation Emergency Communications

With the increasing requirements for unmanned aerial vehicle (UAV) communication in various application scenarios, the UAV-assisted emergency communication in urban transportation scenario has received great attention. In this paper, a novel UAV-assisted UAV-to-vehicle (U2V) geometry-based stochastic model (GBSM) for the urban traffic communication scenario is proposed. The three-dimensional (3D) multi-mobilities of the transmitter (Tx), receiver (Rx), and clusters are considered by introducing the time-variant acceleration and velocity correspondingly. The velocity variation of the clusters is used to simulate the motion of vehicles around the Rx. Moreover, to describe the vehicles’ moving states, Markov chain is adopted to analyze the changes in cluster motion states, including survival, death, dynamic, and static states. By adjusting the scenario-specific parameters, such as the vehicle density (ρ) and dynamic–static ratio (Ω), the model can support various urban traffic scenarios. Based on the proposed model, several key statistical properties, namely the root mean square (RMS) delay spread, temporal autocorrelation function (ACF), level-crossing rate (LCR), power delay profile (PDP), and stationary interval, under different clusters and antenna accelerations are obtained and analyzed. The accuracy of the proposed model is verified by the measured data. The results demonstrate the usability of our model, which can be provided as a reference for the design, evaluation, and optimization of future communication networks between UAV and vehicles in urban transportation emergency communications.

Combining Receiver Damaged by Beaulieu-Xie Fading and Rician Co-Channel Interference with a Purpose of Machine Learning QoS Level Prediction

In this paper, a wireless system is considered impacted by Beaulieu-Xie (BX) fading and Rician co-channel interference (CCI). A selection diversity combining technique is used to combat multi-path fading and CCI effects. The expression for the level crossing rate (LCR) is formulated for the receiver with more input branches, and the corresponding curves that have dependence on the signal-to-interference ratio (SIR) are drawn. On the basis of the presented graphs, we quantify the amount of LCR affected by the presence of fading and interference. Additionally, we propose a classification-based predictive model which leverages the previously calculated LCR value as one of inputs among other variables (number of users, base station, the day of the week) with the aim of Quality of Service (QoS) level prediction.

Channel Modeling for UAV-to-Ground Communications With Posture Variation and Fuselage Scattering Effect

Unmanned aerial vehicle (UAV)-to-ground (U2G) channel models play a pivotal role in reliable communications between UAV and ground terminal. This paper proposes a three-dimensional (3D) non-stationary hybrid model including large-scale and small-scale fading for U2G multiple-input-multiple-output (MIMO) channels. Distinctive channel characteristics under U2G scenarios, i.e., 3D trajectory and posture of UAV, fuselage scattering effect (FSE), and posture variation fading (PVF) are incorporated into the proposed model. The channel parameters, i.e., path loss (PL), shadow fading (SF), path delay, and path angle, are generated incorporating machine learning (ML) and ray tracing (RT) techniques to capture the structure-related characteristics. In order to guarantee the physical continuity of channel parameters such as Doppler phase and path power, the time evolution methods of inter- and intra- stationary intervals are proposed. Key statistical properties, including temporal auto-correction function (ACF), power delay profile (PDP), level crossing rate (LCR), average fading duration (AFD), and stationary interval (SI), are analyzed with the impact of the change of fuselage and posture variation. It is demonstrated that both posture variation and fuselage scattering have crucial effects on channel characteristics. The validity and practicability of the proposed model are verified by comparing the simulation results with the measured ones.

Wireless Communication System Performance in M2M Nakagami-m Fading Channel

In this paper, we investigate a wireless mobile communication system with a cooperative network operating over a mobile-to-mobile (M2M) fading channel in the presence of co-channel interference. Since there is no direct line of sight between the source (S) and the destination (D) due to various obstacles, the signal transmission takes place by using a relay (R). We modeled and represented the desired signal and co-channel interference by using the Nakagami-m fading distribution from the source (S) to the relay (R), as well as from the relay (R) to the destination (D). As the popularity of M2M communication has increased in 5G cellular networks, the performance analysis of the proposed system is of great importance. We derived closed-form expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the signal-to-interference ratio (SIR) at the input of the destination station. Based on the cumulative distribution function (CDF), we also evaluated the outage probability (Pout) of the proposed communication system. In addition, we derived a closed-form approximate expression for the level crossing rate (LCR) by using the Laplace approximation formula for the three-fold integral. Validity of the derived theoretical results we approved by Monte Carlo simulations.

Second-Order Statistics for IRS-Assisted Multiuser Vehicular Network With Co-Channel Interference

In this paper, we consider a downlink multi-user vehicular communication network empowered by an intelligent reflecting surface (IRS) with the base station (BS) employing the orthogonal frequency division multiple access (OFDMA) scheme. The performance of the considered system is evaluated in terms of second-order statistics (SOS) in the presence of multiple co-channel interferers with varying powers and speeds. In particular, we develop the analytical expressions of level crossing rate (LCR) and average outage duration (AOD) of the received signal envelope at a desired vehicle by considering a generalized fading model as - distribution. The impact of various system and channel parameters such as number of reflecting elements, amplitude of reflection coefficients, number of interferers, Doppler frequencies of desired and interfering vehicles, and different channel fading environments has been shown on the LCR and AOD performances. Moreover, we derive an expression for asymptotic LCR under high transmit power conditions. It has been shown that the asymptotic LCR is independent of the threshold and transmit power. In addition, we consider a stop and wait automatic repeat request (SW-ARQ) protocol for reliable data packet transmission and derive the expressions for packet error rate (PER) and throughput by utilizing the finite-state Markov channel (FSMC) model. The optimal packet length is also determined which maximizes the throughput under SW-ARQ protocol. The impact of various system parameters is also shown on the PER and throughput performances.

On the second order statistics of the ratio of two Fisher-Snedecor random variables and its application to interference limited communications

The paper investigates the higher order statistics of the ratio of two Fisher-Snedecor F (FS-F) random variables (RVs) and its application to wireless communications in the presence of co-channel interference. Namely, the work provides novel expressions for probability density function (PDF), cumulative density function (CDF), level crossing rate (LCR) and average fade duration (AFD) of the ratio of two FS-F RVs. Numerical examples of the analytically derived statistical measures in terms of FS-F multi-path and shadowing parameters are shown and examined. Moreover, the impact of the number of interferes on the considered measures are further presented and examined.

Geometry-Based Stochastic Model and Statistical Characteristic Analysis of Cell-Free Massive MIMO Channels

Cell-free massive multi-input multi-output (MIMO) systems exhibit many characteristics that differ from those of traditional centralized massive MIMO systems, and there are still research gaps in the modeling of cell-free massive MIMO channels. In this paper, a geometry-based stochastic model (GBSM) that combines the double-ring model and hemisphere model to comprehensively consider the distribution of scatterers in the environment was proposed for cell-free massive MIMO channels. Combined with the line-of-sight (LoS) path, single scattering path, and double scattering path components, the channel matrix between the access points (APs) and the user was derived. The proposed model fully considers geometric parameters such as the arrival/departure direction, elevation angle, time delay, and distance, which can accurately characterize the channel. Then, we proved that the traditional channel model, standard block-fading model, and spatial basis expansion model (SBEM) adopted in a cell-free massive MIMO system could not describe the nonstationarity in the space, time, and frequency domains, whereas the proposed GBSM could. Statistical characteristics of the channel were analyzed, including the space cross-correlation function (CCF), time autocorrelation function (ACF), Doppler power spectral density (PSD), level crossing rate (LCR), and average fade duration (AFD). Then, we investigated the proposed model by simulating the space CCF, time ACF, Doppler PSD, LCR, and AFD under the conditions of two different scatterer densities. Through simulations and analyses, some new features of cell-free massive MIMO channels were identified, providing a theoretical basis for in-depth research on cell-free massive MIMO systems. Finally, the measurement-based scenario and the WINNER II channel model are compared to demonstrate that the GBSM is more practical to characterize real cell-free massive MIMO channels.

Defect Size Evaluation of Cylindrical Roller Bearings with Compound Faults on the Inner and Outer Races

Faults in cylindrical roller bearings are one of the main contributors to major faults in rotating machinery. The development of bearing fault diagnosis technologies is key to measuring the performance, status, and risk of failure of rolling-element bearings and has attracted extensive attention from industry and academia. When faults arise, they are often not a single fault but a compound fault, such as the simultaneous failure of the inner and outer races. In this paper, a method for evaluating the size of compound faults on the inner and outer races of cylindrical roller bearings is proposed. The dynamic modeling method developed by Gupta is employed to create a dynamic model for compound faults on the inner and outer rings of rolling bearings that allows the time domain signal of the vibration responses of compound faults on the inner and outer races to be obtained. Adopting an improved continuous harmonic wavelet packet decomposition method for the decomposition and reconstruction of the compound fault signal, we arrive at the corresponding single-point fault signal. The relationship between defect size and key metrics of the vibration, such as root mean square acceleration (RMS), peak, crest factor (CF), kurtosis, and level crossing rate (LCR), is investigated. The results show that there is a strong linear correlation between LCR and defect size, which can be used to evaluate the size of the defect. Experimental data for cylindrical roller bearings with compound faults on the inner and outer races are examined to verify the results.

A 3D MIMO Channel Model for a High-Speed Train Millimeter Wave Communication System under Cutting and Viaduct Environments

Incorporating MIMO technology with 3D geometry-based stochastic models (GBSM) is a promising channel modeling technique for 5G and beyond. These models could be extended to high-speed train (HST) environments at mmWave bands. In this paper, the proposed 3D MIMO model is composed of the line of sight component (LOS), the non-line of sight component (NLOS) from one sphere, and multiple stochastic confocal elliptic cylinders. The model is applied in the viaduct and cutting environments with a time-varying Rician K-factor. The local channel statistical properties such as the auto correlation function, stationarity distance, and the level crossing rate (LCR) are derived and thoroughly investigated at the 41GHz frequency. These properties are compared with the corresponding measured results at the same wave frequency for an HST wireless channel. There is a strong correlation between the results from the derived model and the measured results. Therefore, this model can be extended to be used for viaduct and cutting channel modeling at the mmWave band.

Features and Always-On Wake-Up Detectors for Sparse Acoustic Event Detection

The need to understand and manage our surroundings has led to increased interest in sensor networks for the continuous monitoring of events and processes of interest. To reduce the power consumption required for continuous monitoring, dedicated always-on wake-up detectors have been designed, with an emphasis on their low power consumption, simple and robust design, and reliable and accurate detection. An especially interesting application of these wake-up detectors is in detecting acoustic signals. In this paper, we present a study on the features and detectors applicable for the detection of sporadic acoustic events. We perform a state-of-the-art acoustic detector analysis, grouping the detectors based on the features they utilize and their implementations. This analysis shows that acoustic wake-up detectors predominantly utilize spectro-temporal (56%) and temporal features (36%). Following the state-of-the-art analysis, we select two detector architecture candidates for a case study on passing motor vehicle detection. We utilize our previously developed spectro-temporal decomposition detector and develop a novel level-crossing rate detector. The results of the case study shows that the proposed level-crossing rate detector has lower component count (44 compared to 70) and power consumption (9.1 µW compared to 34.6 µW) and is an optimal solution for SNRs over 0 dB.

A stochastic confocal ellipsoid channel model for high speed railway MIMO communication systems

This paper investigates the channel model for multiple-input multiple-output (MIMO) communication systems in high speed railway (HSR) networks. Specially, a three-dimensional (3D) confocal stochastic geometry ellipsoid model is proposed for modeling the MIMO channels. Normalized space–time correlation function(ST CF), Spatial cross correlation function (CCF) and level crossing rate (LCR) of both theoretical and simulation model are have been derived and analyzed. As a 3D GBSM, the proposed confocal ellipsoid model has lower correlation in spatial cross-correlation function (CCF) compared with that of the corresponding two-dimensional (2D) ellipse model. Measurement data of different HSR scenarios verify the applicability of the confocal ellipsoid model.

Second Order Statistics of -Fisher-Snedecor Distribution and Their Application to Burst Error Rate Analysis of Multi-Hop Communications

An advantage of using the composite fading models (CFMs) is their ability to concurrently address the impact of multi-path and shadowing phenomena on the system performance in wireless communications. A Fisher-Snedecor (FS) F CFM has been recently proposed as an experimentally verified and tractable fading model that can be efficiently applied for 5G and beyond 5G wireless communication systems. This paper provides second-order (s-order) performance analysis of the product of N independent but not identically distributed (i.n.i.d) FS F random variables (RVs). In particular, accurate and closed-form approximations for level crossing rate (LCR) and average fade duration (AFD) of the product of N i.n.i.d FS F ( N-FS F) RVs are successfully derived by exploiting a general property of a Laplace approximation method for evaluation of the N-folded integral-form LCR expression. Based on the obtained s-order statistical results, the burst error rate and maximum symbol rate of the N-FS F distribution are addressed and thoroughly examined. The numerical results of the considered performance measures are discussed in relation to the N-FS F multi-path and shadowing severity parameters. Moreover, the impact of the number of hops ( N) of the N-FS F CFM on the s-order metrics, the burst error rate and maximum symbol rate are numerically evaluated and investigated. The derived s-order statistical results can be used to address the cooperative relay-assisted (RA) communications for vehicular systems. Monte-Carlo (M-C) simulations for the addressed statistical measures are developed in order to confirm the provided theoretical results.

LCR and AFD of the Products of Nakagami-m and Nakagami-m Squared Random Variables: Application to Wireless Communications Through Relays

The paper considers level crossing rate (LCR) and average fade duration (AFD) of the product of independent and identically distributed (i.i.d) Nakagami-m (NM) and double NM squared (also known as gamma-gamma) random variables (RVs). The derived statistics are then directly applied to the radio-frequency (RF) - free space optical (FSO), dual-hop (DH), amplify-and-forward (AF) relaying system over non turbulent-induced-fading channels (nTIFCs) and turbulent-induced-fading channels (TIFCs). The obtained results for LCR and AFD of DH-AF, RF-FSO system over TIFCs and nTIFCs are numerically evaluated and graphically presented for various system model parameters.

Performance Analysis of RIS-Assisted FSO Communications over Fisher–Snedecor F Turbulence Channels

The Fisher–Snedecor (F-S) F distribution has recently been introduced as a tractable turbulence-induced (TI) fading model that fits well with the experimental data. This paper provides a performance evaluation of a free-space optical (FSO) re-configurable intelligent surface (RIS)-assisted communications (ACs) link over the F-S F TI fading channels, assuming the intensity modulation–direct detection (IM–DD) technique. In particular, novel and closed-form (C-F) analytical expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the end-to-end signal-to-noise ratio (SNR) in terms of Gaussian hyper-geometric functions are efficiently derived. Capitalizing on the obtained results, novel C-F analytical expressions for the moment generating function (MMGF), outage probability (OP), average bit error rate (BER) and ergodic channel capacity (Cγ) of the FSO RIS-ACs system over the F-S F TI fading channels are provided and numerically evaluated under the various TI fading severity conditions. Furthermore, the second-order (S-O) statistical expressions for the level crossing rate (LCR) and average fade duration (AFD) are obtained and thoroughly examined for various FSO RIS-ACs system model parameters.

Power Control for Body Area Networks: Accurate Channel Prediction by Lightweight Deep Learning

Recent advances in the Internet of Things (IoT) are reforming the health care industry by providing higher communication efficiency, lower costs, and higher mobility. Among the many IoT applications, wireless body area networks (BANs) are a remarkable solution caring for a rapidly growing aged population. Predictive transmit power control schemes improve BAN communications’ reliability and energy efficiency through long-term optimal radio resources allocation that supports consistent pervasive healthcare services. Here, we propose LSTM-based neural network (NN) prediction methods that provide long-term accurate channel gain prediction of up to 2 s over nonstationary BAN on-body channels. An incremental learning scheme, which enables the LSTM predictor to operate online, is also developed for dynamic scenarios. Our main contribution is a lightweight NN predictor, “LiteLSTM,” that has a compact structure and higher computational efficiency than other variants. We show that LiteLSTM remains functional under an incremental learning scheme, with only marginal performance degradation when implemented on hand-held devices. For optimal power allocation, we develop an interquartile range (IQR)-based power control for our channel prediction. When extensively tested using empirical channel measurements at different sampling rates, our proposed methods outperform the existing state-of-the-art methods in terms of prediction accuracy, power consumption, level crossing rate (LCR), and outage probability and duration.