Channel Simulation Research Articles

Improving Gaussian channel simulation using nonunity-gain heralded quantum teleportation

Gaussian channel simulation is an essential paradigm in understanding the evolution of bosonic quantum states. It allows us to investigate how such states are influenced by the environment and how they transmit quantum information. This makes it an essential tool for understanding the properties of Gaussian quantum communication. Quantum teleportation provides an avenue to effectively simulate Gaussian channels, such as amplifier channels, loss channels, and classically additive noise channels. However, implementations of these channels, particularly quantum amplifier channels and channels capable of performing Gaussian noise suppression, are limited by experimental imperfections and nonideal entanglement resources. In this work, we overcome these difficulties using a heralded quantum teleportation scheme that is empowered by a measurement-based noiseless linear amplifier. The noiseless linear amplification enables us to simulate a range of Gaussian channels that were previously inaccessible. In particular, we demonstrate the simulation of nonphysical Gaussian channels otherwise inaccessible using conventional means. We report Gaussian noise suppression, effectively converting an imperfect quantum channel into a near-identity channel. The performance of Gaussian noise suppression is quantified by calculating the transmitted entanglement. Published by the American Physical Society 2024

Shallow water communication with an object buried in bottom sediments

Underwater acoustic communications (UAC) in shallow water applications is a very difficult task. This task becomes even more difficult when there is a need to ensure reliable communication with an object buried in bottom sediments. The article presents a simulation of an acoustic transmission channel in conditions of strong multi-path propagation to an object buried in bottom sediments. The impulse response method was used, supported by a technique derived from the ray tracing image source method. Simulation results are presented for both narrowband and broadband signals with LFM frequency modulation. Based on the simulation, the conditions that should be met by the transmission signals to ensure correct communication were determined. Examples of data transmission to an object buried in bottom sediments in a simulated shallow channel with multi-path propagation were also presented.

Flow channel simulation and optimization design of pervaporation membrane pool based on heat-mass-flow coupling

Pervaporation (PV), recognized as a separation technology with vast potential, is highly dependent on the fluid flow patterns within the membrane module, which play a critical role in local mass transfer processes on the membrane surface. In this study, computational fluid dynamics (CFD) was employed to simulate two different flow channel designs for a PV membrane module, with experimental verification of the model’s accuracy. The results indicated that the parallel inlet–outlet and wavy flow channel design (Mode II) significantly improved the feed-side concentration and temperature distribution, leading to a 3.7 % increase in feed-side flow velocity. Further investigation into the effects of three membrane pool structural parameters on separation performance revealed that pressure drop was most significantly influenced by the inlet radius, while the wavy length-to-height ratio (L:H) has the greatest impact on separation performance. After optimization, the optimal membrane module structure was determined to be the baffle depth of 4 mm, the inlet radius of 1 mm, and the L:H of 1:1. Based on this optimized structure, the effects of operating conditions on separation performance were further explored. The study showed that increasing feed flow rate significantly enhanced separation performance, while increasing feed temperature and concentration intensified temperature and concentration polarization on the membrane surface. Through multi-objective optimization, the optimal operating conditions were determined to be the feed flow rate of 20 L·h-1, feed temperature of 55 °C, and feed concentration of 3 wt%. This study provides valuable theoretical insights and technical references for the design of PV membrane pool flow channels and the selection of operational conditions.

Turbulent stratified open channel flow with solar heating up to Pr=7 using Direct Numerical Simulation

This paper investigates the turbulent structure of stratified open-channel flow subjected to a radiative volumetric heat source modelled by the Beer–Lambert law, for Prandtl numbers (Pr) varying from 0.07 to Pr=7. Direct Numerical Simulation (DNS) was employed to model the open-channel flow. To overcome the increased computational resources required to resolve the thermal fields when Pr>1, a multi-resolution method using quadratic interpolation was employed to resolve the temperature and momentum fields on different spatial and temporal resolutions. This scheme was implemented in an in-house computational fluid dynamics (CFD) code. To further reduce the computation cost, the DNS of Pr=2.2 and 7 fluids were initialised using the outputs of minimal channel simulations. The simulations were conducted for Pr=0.07, 0.22, 0.71, 2.2, and 7 under neutral (λ=0), near-neutral (λ=0.1), and stable (λ=0.5) thermal stratification. The results demonstrate that Pr significantly affects the flow structure and turbulence characteristics of stratified flows, particularly near the free surface. This includes higher velocity, temperature gradient, and buoyancy effects for Pr=7 compared to lower Pr values. For stratified Pr=7 flow, examination of the Reynolds stresses and turbulent heat flux reveals significant damping of turbulence near the surface, with flow displaying near-laminar behaviour.

Investigations on Millimeter-Wave Indoor Channel Simulations for 5G Networks

Due to the extensively accessible bandwidth of many tens of GHz, millimeter-wave (mmWave) and sub-terahertz (THz) frequencies are anticipated to play a significant role in 5G and 6G wireless networks and beyond. This paper presents investigations on mmWave bands within the indoor environment based on extensive simulations; the study considers the behavior of the omnidirectional and directional propagation characteristics, including path loss exponents (PLE) delay spread (DS), the number of clusters, and the number of rays per cluster at different frequencies (28 GHz, 39 GHz, 60 GHz and 73 GHz) in both line-of-sight (LOS) and non-LOS (NLOS) propagation scenarios. This study finds that the PLE and DS show dependency on frequency; it was also found that, in NLOS scenarios, the number of clusters follows a Poisson distribution, while, in LOS, it follows a decaying exponential distribution. This study enhances understanding of the indoor channel behavior at different frequency bands within the same environment, as many research papers focus on single or two bands; this paper considers four frequency bands. The simulation is important as it provides insights into omnidirectional channel behavior at different frequencies, essential for indoor channel planning.

Advancements in Underwater Optical Wireless Communication: Channel Modeling, PAPR Reduction, and Simulations With OFDM

Advancements in Underwater Optical Wireless Communication: Channel Modeling, PAPR Reduction, and Simulations With OFDM

Multi-Cluster Approaches to Radio Sensor Array Channel Modeling and Simulation.

In this paper, we explore the physical propagation environment of radio waves by describing it in terms of distant scattering clusters. Each cluster consists of numerous scattering objects that may exhibit certain statistical properties. By utilizing geometry-based methods, we can study the channel second-order statistics (CSOS), where each distant scattering cluster corresponds to a CSOS, contributes a portion to the Doppler spectrum, and is associated with a state-space multiple-input and multiple-output (MIMO) radio channel model. Consequently, the physical propagation environment of radio waves can be modeled by summing multiple state-space MIMO radio channel models. This approach offers three key advantages: simplicity, the ability to construct the entire Doppler power spectrum from multiple uncorrelated distant scattering clusters, and the capability to obtain the channels contributed by these clusters by summing the individual channels. This methodology enables the reconstruction of the radio wave propagation environment in a simulated manner and is crucial for developing massive MIMO channel models.

Neural Network SNR Prediction for Improved Spectral Efficiency in Land Mobile Satellite Networks

The use of satellites to cover remote areas is a promising approach for increasing communication availability and reliability. The satellite resources, however, can be quite costly, and developing ways to optimize their usage is of great interest. Optimizing spectral efficiency while keeping the transmission error rate above a certain threshold represents one of the crucial aspects of resource optimization. This paper provides a novel strategy for adaptive coding and modulation (ACM) employment in land mobile satellite networks. The proposed solution incorporates machine learning techniques to predict channel state information and subsequently increase the overall spectral efficiency of the network. The Digital Video Broadcasting Satellite Second Generation (DVB-S2X) satellite protocol is considered as the use case, and by using the developed channel simulator, this paper performs an evaluation of the proposed machine learning solutions for channels with various characteristics, with a total of 90 different observed channels. The results show that a convolutional neural network with a modified loss function consistently achieves an improvement (over 100% in some scenarios) of spectral efficiency compared to the state-of-the-art ACM implementation while keeping the transmission error rate under 0.01 for single channel evaluation. When observing two channels, an improvement of more than 300% compared to the outdated information spectral efficiency was obtained in multiple scenarios, showing the effectiveness of the proposed approach and allowing optimization of the handover strategy in satellite networks that allow user-centric handover executions.

Large-scale control in turbulent flows over surface riblets

The drag reduction efficacy of a large-scale flow control over a rough surface is studied via direct numerical simulations of turbulent channels (at friction Reynolds numbers Reτ=180) by combining together wall riblets and streamwise counter-rotating swirls. In particular, the height of triangular riblets is h+≈10 (+indicating wall units), while the number of riblets (NRib in the range 1–56) along the periodic spanwise direction is varied to find the optimum. The swirls are generated by the spanwise opposed wall-jet forcing (SOJF) in the Navier–Stokes equation, whose controlling parameters follow the optimal ones as for the smooth wall. In total, 12 cases of combined SOJF and riblets are performed to investigate the coupling effects between the two methods. We find a range of NRib=7–14 (with the spanwise width z+≈140−280) yields the largest drag reduction (up to 20%) for Reτ=180, much higher than riblets control only (about 3%). Compared to SOJF control only, riblets suppress the secondary swirls of SOJF hence decreasing drag, while the lateral and down washing motions of SOJF impinging on riblets would increase drag—the opposite two effects thus giving rise to an optimal. Through examinations on coherent structures, we elucidate that the attenuation of both large-scale coherent motions and small-scale random fluctuations leads to the net drag reduction. We conclude that large-scale control is a robust approach in the cases of rough surfaces, and the parameters can be selected for maximum drag reduction in each particular situation.

Quantifying the performance of bidirectional quantum teleportation

Bidirectional teleportation is a fundamental protocol for exchanging quantum information between two parties by means of a shared resource state and local operations and classical communication (LOCC). In this paper, we develop two seemingly different ways of quantifying the simulation error of unideal bidirectional teleportation by means of the normalized diamond distance and the channel infidelity, and we prove that they are equivalent. By relaxing the set of operations allowed from LOCC to those that completely preserve the positivity of the partial transpose, we obtain semi-definite programming lower bounds on the simulation error of unideal bidirectional teleportation. We evaluate these bounds for several key examples: when there is no resource state at all and for isotropic and Werner states, in each case finding an analytical solution. The first aforementioned example establishes a benchmark for classical versus quantum bidirectional teleportation. Another example consists of a resource state resulting from the action of a generalized amplitude damping channel on two Bell states, for which we find an analytical expression for the simulation error that is in agreement with numerical estimates (up to numerical precision). We then evaluate the performance of some schemes for bidirectional teleportation due to (Kiktenko et al., Phys. Rev. A 93, 062305 (2016)) and find that they are suboptimal and do not go beyond the aforementioned classical limit for bidirectional teleportation. We offer a scheme alternative to theirs that is provably optimal. Finally, we generalize the whole development to the setting of bidirectional controlled teleportation, in which there is an additional assisting party who helps with the exchange of quantum information, and we establish semi-definite programming lower bounds on the simulation error for this task. More generally, we provide semi-definite programming lower bounds on the performance of bipartite and multipartite channel simulation using a shared resource state and LOCC.

Experimental study on the transmission performance of an ultraviolet and visible light communication system under an artificial fog channel.

In this work, the visible light communication (VLC) and deep ultraviolet light communication (DUVLC) systems under an artificial fog channel are established, into which a fog channel simulator based on an acrylic box connected to a fog generator through a pipe is introduced. The VLC and DUVLC systems are based on line-of-sight (LOS) channel and non-line-of-sight (NLOS) channel with a large receiving angle about 90°, respectively. Under the influence of fog concentration, the transmission performance of the VLC and DUVLC systems is further analyzed and compared, including path loss, received signal quality and bit error rate (BER). Both VLC and DUVLC links were applied, and the BER of the integrated system was experimentally collected. The results show that the lower the fog concentration, the better the transmission performance of the VLC system, while the transmission performance of the DUVLC system is worse. Furthermore, the transmission distance and received angle should be considered for the NLOS-based DUVLC system, which can achieve communication at a distance of 10 cm and a receiving angle of 100° under the influence of dense fog. Moreover, the two links, DUVLC and VLC, are simultaneously applied for information transmission, which verifies that the dual-band integrated system can be well adapted to a fog environment. This study not only provides experimental support for the application of the VLC and DUVLC composite system but also demonstrates the possibility of applying the dual-band system in fog environments to a variety of complex outdoor scenarios.

Investigating Rising Bubbles in Air-nanofluid Two-phase Flow: A Vertical Channel Simulation Approach

Investigating Rising Bubbles in Air-nanofluid Two-phase Flow: A Vertical Channel Simulation Approach

Statistical channel modeling for low-elevation in LEO satellite communication

Channel modeling plays a crucial role in measuring wireless communication performance. This paper describes statistical channel modeling for a recorded signal from a ground station in an urban area in Tehran. This signal was recorded from the GRBALPHA satellite at 170–180° elevation and fixed azimuth. The three-state Markov channel modeling is used for this case. Markov models are often used for Land Mobile Satellite Channels (LMSC) because when the user is moving at different speeds between different environments, this causes, Variety in received power. By analyzing the communication channel in the lower elevations, the link budget can be designed with a suitable margin by considering the channel specification and its limitations. In addition to increasing communication time, reducing the bit error rate (BER), lowering costs, etc., this causes a more accurate channel analysis from the beginning to the end of the satellite passage.This work presents a statistical model for channel simulation using the Markov multi-state chain, estimating the Markov channel model between a fixed ground station and a Low Earth Orbit (LEO) Satellite at low elevations. The comparison of simulation data with recorded data demonstrates the proposed approach's effectiveness in modeling the channel.

Thresholds for the distributed surface code in the presence of memory decoherence

In the search for scalable, fault-tolerant quantum computing, distributed quantum computers are promising candidates. These systems can be realized in large-scale quantum networks or condensed onto a single chip with closely situated nodes. We present a framework for numerical simulations of a memory channel using the distributed toric surface code, where each data qubit of the code is part of a separate node, and the error-detection performance depends on the quality of four-qubit Greenberger–Horne–Zeilinger (GHZ) states generated between the nodes. We quantitatively investigate the effect of memory decoherence and evaluate the advantage of GHZ creation protocols tailored to the level of decoherence. We do this by applying our framework for the particular case of color centers in diamond, employing models developed from experimental characterization of nitrogen-vacancy centers. For diamond color centers, coherence times during entanglement generation are orders of magnitude lower than coherence times of idling qubits. These coherence times represent a limiting factor for applications, but previous surface code simulations did not treat them as such. Introducing limiting coherence times as a prominent noise factor makes it imperative to integrate realistic operation times into simulations and incorporate strategies for operation scheduling. Our model predicts error probability thresholds for gate and measurement reduced by at least a factor of three compared to prior work with more idealized noise models. We also find a threshold of 4×102 in the ratio between the entanglement generation and the decoherence rates, setting a benchmark for experimental progress.

Consistent Eccentricities for Gravitational-wave Astronomy: Resolving Discrepancies between Astrophysical Simulations and Waveform Models

Detecting imprints of orbital eccentricity in gravitational-wave (GW) signals promises to shed light on the formation mechanisms of binary black holes. To constrain the formation mechanisms, distributions of eccentricity derived from numerical simulations of astrophysical formation channels are compared to the estimates of eccentricity inferred from GW signals. We report that the definition of eccentricity typically used in astrophysical simulations is inconsistent with the one used while modeling GW signals, with the differences mainly arising due to the choice of reference frequency used in both cases. We also posit a prescription for calculating eccentricity from astrophysical simulations, by evolving ordinary differential equations obtained from post-Newtonian theory and using the dominant (ℓ = m = 2) mode’s frequency as the reference frequency; this ensures consistency in the definitions. On comparing the existing eccentricities of the binaries present in the Cluster Monte Carlo catalog of globular cluster simulations with the eccentricities calculated using the prescription presented here, we find a significant discrepancy at e ≳ 0.2; this discrepancy becomes worse with increasing eccentricity. We note the implications this discrepancy has for existing studies and recommend that care be taken when comparing data-driven constraints on eccentricity to expectations from astrophysical formation channels.

Machine learning-based detection of the man-in-the-middle attack in the physical layer of 5G networks

Fifth generation communication networks (5G) has received a great deal of attention from academia and industry alike, which will enable a wide variety of vertical applications by connecting heterogeneous devices and machines. Assessing availability and reliability in many circumstances and environments is critical. Researchers have recently focused on investigating and analyzing new multimedia networks with artificial intelligence (AI) technologies to achieve higher data rates and secure communication traffic between parties. User information privacy and security are of vital importance and of growing concerns that present evolving challenges to overcome in preventing attacks. Man-in-the-middle (MITM) attack is considered one of the most common attacks, where an attacker can impersonate one of the parties in a communication system to steal user data or forge the malicious data. Due to the limitation of using conventional cryptographic techniques for mobile networks and similar systems, new methods have been introduced to validate and authenticate transmitted signals dynamically, depending on the physical layer. In this paper, we present the distance-time directional delay (DTDD) model to detect the MITM attack in a variety of contexts and scenario. Indoor hotspots (InH) and urban micro-cellular (UMi) propagation environments were investigated to verify the reliability of the proposed approaches using realistic 5G millimeter-wave configurations and system setups. Simulations have been constructed based on the mmWave 5G channel simulator tool NYUSIM, in conjunction with a collection of machine learning algorithms (ML) including the extreme gradient boosting (XGBoost) and light gradient boosting machine (LGBM) as the core of the presented models and methodologies. Numerical simulations results produced a detection accuracy approaching 100% in the InH environment scenario, whereas for UMi environment scenario, a detection accuracy approaching 99% was attained.

Improving the Representation of Moisture and Convective Instability in Baroclinic-Wave Channel Simulations

Abstract We present an improved approach to generating moist baroclinically unstable background states for f-plane-channel simulations via potential vorticity (PV) inversion. Previous studies specified PV distributions with constant values in the troposphere and the stratosphere, but this produces unrealistic static-stability profiles that decrease sharply with height in the troposphere. Adding moisture to such environments can yield unrealistically large values of convective available potential energy (CAPE) even for reasonable relative humidity (RH) distributions. In our modified approach, we specify a PV distribution that increases with height in the troposphere and the stratosphere, yielding background states with more realistic values of static stability and CAPE. This modification produces environments that are better suited for representing moist processes, namely, deep convection, in idealized extratropical-cyclone simulations. Also, we present a method for introducing moisture that preserves a specified RH distribution while maintaining hydrostatic balance. Our approach allows for a large degree of control over the initial conditions, as background states with different jet strengths and shapes, average temperatures, moisture contents, or horizontal shears can easily be obtained without changing the underlying PV formula and inadvertently producing unreasonable values of static stability or CAPE. We demonstrate the characteristics of idealized extratropical cyclones developing in our background states by adding localized perturbations that represent an upper-level trough passing over a low-level frontal zone. In particular, we illustrate the impacts of horizontal shear, moisture, and grid spacing on baroclinic-wave development.

On the Detection of Vulnerable Road Users—Simulating Limits of an FMCW Radar

The complexity of urban traffic environments poses unique challenges for automotive radar sensors. Limited range and Doppler resolution hinder the ability to distinguish closely spaced objects and detect vulnerable road users, particularly pedestrians. Therefore, it is important to know the limits of FMCW radars. To assess these limitations, the WinProp channel simulator is used to model and simulate traffic scenarios regarding the detection of the range, velocity, and SNR of targets. To validate WinProp as a simulation tool for traffic scenarios, a real traffic scenario is configured and the simulation results compared to the measurement results in order to demonstrate the suitability of WinProp for simulating traffic scenarios and evaluating radar detection performance. The close agreement between the simulation and measurement results provides validation for WinProp’s accuracy in modeling detections and signal processing within traffic scenarios. To showcase the limitations of FMCW radars, two scenarios with challenging detection conditions are simulated: an occluded pedestrian between parked vehicles and a densely populated road. A monostatic setup with a single patch antenna and a 16 × 16 patch antenna array is evaluated, using chirp bandwidths of 1 GHz and 4 GHz. The simulations have shown that although it is feasible to detect an occluded pedestrian by multipath propagation, there is still a need in improving the detection performance when there is no multipath from an occluded pedestrian. Furthermore, the results indicate that higher bandwidth improves target separation but is insufficient for occluded pedestrian detection without multipath. However, with some targets, even the range resolution at 4 GHz was not sufficient, which required a separation in the Doppler dimension, emphasizing the need for overall resolution improvement of FMCW radars. Future work should focus on developing more complex road user models and simulating a broader range of scenarios to comprehensively evaluate radar performance in road traffic environments.

Experimental and numerical simulation research on shock wave rock-breaking by high voltage electric pulse

High-voltage electric pulse(HVEP) drilling technology has the advantages of high rock-breaking efficiency, green and non-polluting. Aiming at the importance of HVEP drilling technology in generating plasma channels, plasma shock waves, and rock-breaking pits, this paper carries out multi-physics field numerical simulations and indoor electric pulse breakdown experiments. This paper first constructs a two-dimensional numerical model of rock electric breakdown. The simulation of HVEP rock breaking, plasma channel and plasma shock wave is realized from the five-field coupling and combined with the wave control equations. The effects of different electrode shapes on the plasma channel, breakdown channel and shock wave are analyzed. Then, this paper designed an indoor HVEP rock-breaking experiment to investigate the influence of different electrode shapes on rock breakdown and plasma shock waves. The simulation and experimental results show that the indoor electric pulse breakdown experiment results are consistent with the simulation results; The plasma channels are formed by the ‘electrical damage’ through each other, and the secondary plasma channel is often generated inside the rock. The generation of the secondary plasma channel means that the rock fragmentation depth and the fragmentation area will be increased; The larger the contact area of the electrode bit with the rock, the larger the radius (volume) of the plasma channel and the smaller the amplitude of the plasma shock wave; The quadrangular electrode bits have the best rock-breaking effect and are recommended; The conical electrode bit has the most excellent dispersion in the statistical analysis of the electric pulse rock-breaking effect, and the stability of the rock-breaking effect is poor, so it is recommended to use it together with the composite drill bit; The cylindrical electrode bit has the best aggregation degree of electric pulse rock-breaking and the most stable rock-breaking effect.

3D Simulation of an Extreme SAID Flow Channel

AbstractSpace‐based observations of the signatures associated with STEVE show how this phenomenon might be closely related to an extreme version of a SAID channel. Measurements show high velocities (>4 km/s), high temperatures (>4,000 K), and very large current density drivers (up to 1 μA/m2). This phenomena happens in a small range of latitudes, less than a degree, but with a large longitudinal span. In this study, we utilize the GEMINI model to simulate an extreme SAID/STEVE. We assume a FAC density coming from the magnetosphere as the main driver, allowing all other parameters to adjust accordingly. We have two main objectives with this work: show how an extreme SAID can have velocity values comparable or larger than the ones measured under STEVE, and to display the limitations and missing physics that arise due to the extreme values of temperature and velocity. Changes had to be made to GEMINI due to the extreme conditions, particularly some neutral‐collision frequencies. The importance of the temperature threshold at which some collision frequencies go outside their respective bounds, as well as significance of the energies that would cause inelastic collisions and impact ionization are displayed and discussed. We illustrate complex structures and behaviors, emphasizing the importance of 3D simulations in capturing these phenomena. Longitudinal structure is emphasized, as the channel develops differently depending on MLT. However, these simulations should be viewed as approximations due to the limited observations available to constrain the model inputs and the assumptions made to achieve sensible results.