Channel Parameters Research Articles

Research on Automatic Wavelength Calibration of Passive DOAS Observations Based on Sequence Matching Method

Passive differential optical absorption spectroscopy (DOAS) is widely used to monitor the three-dimensional distribution of atmospheric pollutants. However, the observational and retrieval accuracy of this technique is significantly influenced by the precise wavelength calibration of solar spectra. Current calibration methods face challenges in automation when dealing with complex remote-sensing conditions. We introduce a novel automatic wavelength calibration algorithm for passive DOAS based on sequence-matching technology to estimate the spectral parameters of the spectrometer channels, integrating advanced processing measures such as feature structure enhancement and sub-pixel interpolation. These measures significantly reduce the dependency on reference spectrum resolution and accurately correct even minor spectral shifts. We perform sensitivity experiments using synthetic spectra to determine optimal retrieval configurations, followed by field tests at four cities on the Yangtze River Delta, China, to calibrate and compare passive DOAS instruments of various resolutions. Comparative verification in these field studies demonstrated that our algorithm was suitable for rapid spectral calibration within a wider resolution range of 0.03 nm to 0.1 nm with a wavelength inversion error < 0.01 nm. This highlights the applicability and calibration precision of our algorithm.

First investigation on the isomeric ratio in multinucleon transfer reactions: Entrance channel effects on the spin distribution

The multinucleon transfer (MNT) reaction approach was successfully employed for the first time to measure the isomeric ratios (IRs) of 211Po isomer (25/2+) and its ground state (9/2+) at the IGISOL facility using a 945 MeV 136Xe beam impinged on 209Bi and natPb targets. The dominant production of isomers compared to the corresponding ground states was consistently revealed in the α-decay spectra. Deduced IR of 211Po populated through the 136Xe+natPb reaction was found to have an enhancement of ≈1.8-times than that observed for the 136Xe+209Bi. State-of-the-art Langevin-type model calculations have been utilized to estimate the spin distribution of an MNT residue. The computations qualitatively corroborate with the considerable increase in the IRs of 211Po produced from 136Xe+natPb compared to 136Xe+209Bi. Theoretical investigations indicate a weak dependence of target spin on the IRs. The enhancement of the 211Po isomer in the 136Xe+natPb over 136Xe+209Bi can be attributed to the different proton (p)-transfer production routes. Estimations demonstrate an increment in the angular momentum transfer, favorable for isomer production, with increasing projectile energy. Comparative analysis reveals the two entrance channel parameters, projectile mass and p-transfer channels, strongly influencing the population of the high-spin isomer of 211Po (25/2+). This letter reports the first experimental and theoretical study on the IRs of nuclei formed from two different p-transfer channels via two independent MNT reactions.

Blind recognition of channel codes based on a multiscale dilated convolution neural network

Channel coding is an essential part of communication. In a non-cooperative communication system, the receiver has to recover the signal without any priori knowledge. Therefore, it is important to recognize channel code types and parameters. At present, only a few studies focus on channel code type recognition. In this paper, a multiscale dilated convolution neural network (MSDCNN) is proposed to achieve fine-grained recognition of seven commonly used channel code types. MSDCNN has three multiscale modules. Based on the characteristics of each channel code type, the first two identical modules are designed to extract the overall features of codewords with unit convolution and three parallel regular convolution layers. To lower complexity, the third module uses dilated convolution instead of regular convolution to extract features between codewords. Simulation results show that MSDCNN has higher average recognition accuracy than other neural networks. More importantly, MSDCNN lowers complexity, making it more suitable for deployment so that it can be applied in practical non-cooperative receivers.

Multi-antenna dual-blind deconvolution for joint radar-communications via SoMAN minimization

In joint radar-communications (JRC) applications such as secure military receivers, often the radar and communications signals are overlaid in the received signal. In these passive listening outposts, the signals and channels of both radar and communications are unknown to the receiver. The ill-posed problem of recovering all signal and channel parameters from the overlaid signal is termed as dual-blind deconvolution (DBD). In this work, we investigate DBD for a multi-antenna receiver. We model the radar and communications channels with a few (sparse) continuous-valued parameters such as time delays, Doppler velocities, and directions-of-arrival (DoAs). To solve this highly ill-posed DBD, we propose to minimize the sum of multivariate atomic norms (SoMAN) that depend on unknown parameters. To this end, we devise an exact semidefinite program using theories of positive hyperoctant trigonometric polynomials (PhTP). Our theoretical analyses show that the minimum number of samples and antennas required for perfect recovery is logarithmically dependent on the maximum of the number of radar targets and communications paths rather than their sum. We show that our approach is easily generalized to include several practical issues such as gain/phase errors and additive noise. Numerical experiments show the exact parameter recovery for different JRC scenarios.

Two-way communications empowered by reconfigurable intelligent surfaces and direct link: Outage analysis under hardware impairments and Nakagami-m fading

In this article, we consider a two-way communication system empowered by a reconfigurable intelligent surface (RIS), consisting of N passive reflective elements, in the presence of transceiver hardware impairments (HIs). To exploit the existence of a direct link between the end communication nodes, we utilize two time slots for their information exchange. We particularly analyze the instantaneous end-to-end signal-to-noise-plus-distortion-ratios (SNDRs) under HIs. The exact distribution of the magnitude of the end-to-end channel coefficients of the studied RIS-empowered communication system is derived under HIs and Nakagami-m fading channels. Using different settings for the level of HIs and the transmit powers at the end nodes, we also deduce novel exact and upper bound analytical expressions for the overall outage probability (OOP). For the high signal-to-noise ratio regime, an asymptotic OOP analysis is derived, which unveils the system’s diversity order. The presented numerical and simulation results corroborate our derived analytical findings, and demonstrate the impact of different system and channel parameters on the system’s OOP performance.

Coherence Bandwidth of Rice Channels for Millimeter Wave and Sub-Terahertz Applications

6G research in the millimeter wave and sub-Terahertz domain is targeting very wideband systems with significantly higher data throughput than for 5G systems. Multipath propagation under shadowing conditions is affecting radio propagation, where multipath propagation results in frequency-selective fading, which is characterized by the coherence bandwidth and the time variation by the coherence time. In these frequency ranges shadowing can be overcome by additional means in the network deployment such as reflectors, RIS arrays or repeaters, which provide at the receiver a channel impulse response with a strong component (Rice type channel). Coherence bandwidth and coherence time are well-known for Rayleigh channels. However, both parameters for Rice channels versus the Rice factor K′ are not available. This paper is investigating the coherence bandwidth and time for Rice channels based on an approximative approach for the fading statistics. With the proposed correlation criterion, the coherence bandwidth and time tend to infinity from a Rice factor around K′≥4=ˆ6 dB. These relations are provided by approximative functions for K′≥0 starting at the Rayleigh channel.

Suppressing the degeneration of quantum resources through coupling auxiliary qubits

The nonlocal advantage of quantum coherence (NAQC), quantum coherence (QC), and quantum entanglement are promising quantum resources to achieve various quantum information tasks. However, the decoherence of quantum resource is detrimental to the implementation of quantum information processing, and it brings enormous challenge to the application of quantum resource. Here, consider that Alice and Bob possess a two-qubit X state, and the two-qubit X state is composed of two atoms. Bob’s atom interacts with a reservoir, and Alice's atom is subjected to the influence of amplitude damping channel. We design an effective scheme by coupling auxiliary qubits with reservoir, and this scheme can significantly suppress the dissipation of the NAQC, QC, and quantum entanglement. The results reveal that the NAQC, QC, and quantum entanglement degenerate with the increase of time t in the strong coupling regime or weak coupling regime when absenting auxiliary qubits. If one adds some auxiliary qubits in the reservoir, these quantum resources can be strengthened both in the strong coupling regime and weak coupling regime. Auxiliary qubits can help us effectively resist the dissipation of these quantum resources. In comparison with the QC and quantum entanglement, the NAQC is most fragile and it is most vulnerable to the influences of reservoir and noise channel. One needs introduce more auxiliary qubits to suppress the dissipation of the NAQC, especially in the scenarios of the weak coupling regime and strong channel parameter. In this sense, our investigations may provide a potent technique for restraining decoherence and offer a new platform for quantum resource application.

A nozzle design for mitigating particle slowing in the bow shock region during micro-cold spray of 8 YSZ films

During micro-cold spray deposition, also referred to as the aerosol deposition method or vacuum kinetic spraying, performed with conventional nozzles, the particle impact velocities decrease drastically with particle size for fine particles <500 nm in diameter due to slowing in the stagnation region. A new design for a nozzle that contains pressure relief channels is proposed that allows the pressure in the stagnation region downstream of the bow shock to be reduced. This reduced stagnation pressure results in less particle slowing compared to conventional nozzle geometries, particularly for smaller or less dense particles. The effects of the channel geometry on the particle impact velocity are systematically investigated by independently varying the channel parameters. Calculations show that the impact velocities for 100 and 200 nm yttria stabilized zirconia particles is increased by 111% and 31%, respectively, for a selected pressure relief channel nozzle when compared to a comparable conventional nozzle. Although impact velocities are increased, a tradeoff exists with this nozzle design in that the particle focusing in the nozzle is decreased and some of the particles may be removed from the aerosol by the channels. Experiments using a nitrogen as a carrier gas at ∼40 kPa upstream pressure show that, despite the loss of larger particles into the relief channels, the deposition efficiency is improved by 300% when depositing films from fine 8 YSZ powder with the pressure relief nozzle compared to a conventional nozzle.

Single shot detection of alterations across multiple ionic currents from assimilation of cell membrane dynamics

The dysfunction of ion channels is a causative factor in a variety of neurological diseases, thereby defining the implicated channels as key drug targets. The detection of functional changes in multiple specific ionic currents currently presents a challenge, particularly when the neurological causes are either a priori unknown, or are unexpected. Traditional patch clamp electrophysiology is a powerful tool in this regard but is low throughput. Here, we introduce a single-shot method for detecting alterations amongst a range of ion channel types from subtle changes in membrane voltage in response to a short chaotically driven current clamp protocol. We used data assimilation to estimate the parameters of individual ion channels and from these we reconstructed ionic currents which exhibit significantly lower error than the parameter estimates. Such reconstructed currents thereby become sensitive predictors of functional alterations in biological ion channels. The technique correctly predicted which ionic current was altered, and by approximately how much, following pharmacological blockade of BK, SK, A-type K+ and HCN channels in hippocampal CA1 neurons. We anticipate this assay technique could aid in the detection of functional changes in specific ionic currents during drug screening, as well as in research targeting ion channel dysfunction.

Joint estimation model for FSO channel parameters and performance evaluation based on CNNs.

Free space optical (FSO) communication systems experience turbulence-induced fading. As a possible solution, adaptive transmission, which adjusts transmitter parameters based on instantaneous channel state information (CSI), can be used. Most of the existing channel estimation methods ignore the impact of detection noise at the receiver, which will lead to additional estimation errors. In this paper, a joint estimation model based on convolutional neural networks (CNNs) is proposed to estimate detection noise and turbulence fading parameters. We obtained turbulence channel simulation data sets considering the background of detection noise based on the edge probability distribution function of the receive signal. The training of the CNN estimator is carried out through maximum pooling, adaptive learning rate, and regularization, ultimately accurately estimating channel characteristics based on the optimal output results of the network. The simulation results show that the proposed CNN joint estimator performs better in high-detection-noise environments compared with traditional maximum likelihood estimators, and it has better generalization ability in different real atmospheric environments.

Channel parameter optimization of one-strand slab induction heating tundish with double channels

Abstract A generalized three-dimensional mathematical model is built to study the influences of channel parameters (channel angle, channel section diameter, and channel distance) on the molten steel flow, heat transfer, and inclusion removal in the induction heating tundish. The results demonstrate that as the channel angle increases, the flow of molten steel in the discharging chamber gradually slows down. When the channel angle is 6°, the temperature of the discharging chamber is slightly lower than when the channel angles are 2° and 4°. When the channel angle is 2°, the inclusion removal rate is lower than when the channel angles are 4° and 6°, while the latter two have little difference. As the channel section diameter increases, the flow of molten steel in the discharging chamber gradually slows down. When the channel section diameter is 100 mm, the temperature distribution in the discharging chamber is uneven. While the temperature distributions of the discharging chamber are even and similar, when the channel section diameters are 150 and 200 mm. As the channel section diameter increases, the removal rate of inclusion gradually decreases. The variation of channel distance has little effect on the temperature distribution of the discharging chamber. When the channel distance is 600 mm, the removal rate of inclusion is lower than when the channel distances are 1,000 and 1,400 mm. Moreover, for the latter two, the removal rates of inclusions have little difference. For this model, the best channel angle is 4°, the best channel section diameter is 150 mm, and the best channel distance is 1,000 mm.

Dual-repetitive pilot aided parameter estimation for underwater orthogonal frequency division multiplexing acoustic communications in the presence of strong composite noise

In this work, a novel design of signaling parameters and pilot placement is proposed for supporting robust underwater orthogonal frequency division multiplexing acoustic communications in the presence of strong composite noise. The proposed design allows for high-resolution estimation of various channel parameters that are essential to successful symbol recovery. Receiver processing algorithms are developed by exploring special properties of the received signal that hold valid despite complicated channel and noise effects. These algorithms are efficient since they reuse the same set of pilot symbols for multiple tasks of estimation that often require separate sets of pilots. They are also extremely effective because they largely avoid the effects of noise even when the noise is composite. The performance of these algorithms is evaluated via both extensive simulations and an at-sea experiment.

Design of Proton Exchange Membrane Hydrogen Fuel Cell Control System Based on Response Speed and Uncertainty Characteristics

In an effort to settle the issue of poor control accuracy caused by external interference (such as environment and load changes) in the control process of hostage switch film fuel cell, a PEMFC control channel design method based on response speed and uncertainty characteristics was proposed in this study. The channel structure model and parameter model of PEMFC operate channel are established, and its response speed and uncertainty characteristics are analyzed. The proportional integral-differential (PID) operate method is used to obtain the signal model of the current vector data under the optimal operate state, and the AC coupling of the capacitor is used to suppress the loss. The simulation results show that this method can improve the stability and convergence of PEMFC, effectively correct the error, and the operate accuracy reaches 99%.

Received Signal and Channel Parameter Estimation in Molecular Communications

Received Signal and Channel Parameter Estimation in Molecular Communications

Proficient Secret Key Generation using Derivates of the Transform Function for the Internet of Things

Secured data transfer over the internet of things enables communication devices is a very challenging task. Due to the limitation of computational resources, classical cryptography algorithms are vulnerable to cyber threats and loss of integrity and information. Recently, physical layer secret key generation has played a vital role in secured communication on the internet of things. The physical layer key generation approach provides an alternate means of information security using the signal reciprocity of wireless communication. This paper proposed proficient dynamic secret key generation using derivates of transform functions. The derivates of transform functions such as DCT, DWT, DWPT, and many more light transform functions the physical layer key generation employs RSSI channel parameters in conjunction with the discrete wavelet transform to generate low computational secret keys for the authentication of IoT-enabled communication devices. The proposed algorithm is very efficient and reduces the bit disagreement of the key. We use MATLAB software defined radios to conduct the experiment, and we then evaluate the effectiveness of our post-processing techniques. Our approach is helpful for safeguarding future IoT devices since it enhances the ability of targeted nodes to establish matching secret keys while reducing the risk of an eavesdropper. The experimental results of key generation methods suggest that the proposed algorithm is very efficient instead of DCT and DWT.

Research on the Evaluation and Prediction of V2I Channel Quality Levels in Urban Environments

The present manuscript introduces a method for evaluating and forecasting the quality of vehicle-to-infrastructure (V2I) communication channels in urban settings. This method precisely classifies and predicts channel quality levels in V2I scenarios based on long-range (LoRa) technology. This approach aims to accurately classify and predict channel quality levels in V2I scenarios. The concept of channel quality scoring was first introduced, offering a more precise description of channel quality compared to traditional packet reception rate (PRR) assessments. In the channel quality assessment model based on the gated recurrent unit (GRU) algorithm, the current channel quality score of the vehicular terminal and the spatial channel parameters (SCP) of its location are utilized as inputs to achieve the classification of channel quality levels with an accuracy of 97.5%. Regarding prediction, the focus lies in forecasting the channel quality score, combined with the calculation of SCP for the vehicle’s following temporal location, thereby achieving predictions of channel quality levels from spatial and temporal perspectives. The prediction model employs the Variational Mode Decomposition-Backoff-Bidirectional Long Short-Term Memory (VMD-BO-BiLSTM) algorithm, which, while maintaining an acceptable training time, exhibits higher accuracy than other prediction algorithms, with an R2 value reaching 0.9945. This model contributes to assessing and predicting channel quality in V2I scenarios and holds significant implications for subsequent channel resource allocation.

Performance evaluation of the new Sysmex XR-Series haematology analyser

BackgroundThe new XR-Series haematology analyser from Sysmex provides increased throughput and automation, along with a new reagent in WDF channel for optimised WBC differential. MethodsAn analytical performance study for the XR analyser was conducted to evaluate the WDF channel parameters in comparison to the instrument specifications. Additionally, 7460 samples were measured on XR and XN analysers to compare selected parameters and flags, and 930 randomly selected samples were further evaluated with microscopy. ResultsAll investigated aspects of the analytical performance study for the XR fell within the manufacturer specifications. The correlation coefficients between the two systems for the parameters tested were greater than 0.983 for the main CBC and DIFF parameters, greater than 0.909 for the Extended Inflammation Parameters, and greater than 0.932 for the parameters used in the workflow rulesets of the Extended IPU. Similarly high sensitivities for the detection of abnormal cells were observed for the ‘Blasts/Abn Lympho?’ flag (XN: 100%, XR: 99.0%) and WPC abnormal flags (‘Blasts?’ or ‘Abn Lympho?‘) (XN: 97.0%, XR: 96.0%). XN with WPC channel had a 26% reduction of false positive smears compared to XR with 22% reduction, a statistically non-significant difference. ConclusionThe XR analyser had very good analytical performance, and highly comparable results to the predecessor XN analyser in all investigated parameters, flags and workflow aspects.

Continuous Variable Quantum Teleportation in a Dissipative Environment: Comparison of Non‐Gaussian Operations Before and After Noisy Channel

AbstractThis article explores the relative advantages in continuous‐variable quantum teleportation when non‐Gaussian operations, namely, photon subtraction, addition, and catalysis, are performed before and after interaction with a noisy channel. The resource state for teleporting unknown coherent and squeezed vacuum states is generated using two distinct strategies: i) Implementation of non‐Gaussian operations on two mode squeezed vacuum (TMSV) state before interaction with a noisy channel, ii) Implementation of non‐Gaussian operations after interaction of TMSV state with a noisy channel. The results show that non‐Gaussian operations can enhance teleportation fidelity in a dissipative environment. However, the most advantageous non‐Gaussian operation and appropriate strategy depend on the state and channel parameters. The results suggest that employing such strategies can be advantageous in other non‐Gaussian continuous variable quantum information (QIP) processing tasks in a dissipative environment.

Optimization of variable cross-sectional flow channel parameters for fuel cells: Numerical analysis and distributional uniformity evaluation

The bipolar plates (BPs) are the core component of proton exchange membrane fuel cell (PEMFC) stacks, and its structure has a substantial impact on the performance of the stack. Optimizing the parameters of flow channels of bipolar plates is crucial for enhancing the mass transfer of reacting gas and improving water removal capacity. In this study, three-dimensional numerical models of staggered variable cross-sectional flow channels (VCSFCs) are developed to investigate the impact of cathode humidities, contraction ratios, numbers and lengths on the performance and uniformity of PEMFC. The results show that a cathode humidity of 50 % can maximize the advantages of VCSFCs. A higher contraction ratio leads to a significant increase in pressure drop, a decrease in mass transfer capacity, and a less uniform distribution of current density and temperature compared to different numbers and lengths of variable cross-sectional structures (VCSSs). Increasing the overall gas velocity in flow channels can effectively enhance the uniformity of current density and temperature. A VCSS arrangement with a contraction ratio of 0.25, a number of 1 in each channel, and a length of 6 mm is utilized for channels with a length of 100 mm can achieve optimal results.

Bit error rate analysis of MRC diversity receiver over shadowed Beaulieu‐Xie fading channels for mmWave communications

SummaryThis paper presents the performance of maximum ratio combining (MRC) diversity receiver over shadowed Beaulieu‐Xie (SBX) fading model. The SBX model is used to characterise wireless communication environments that include multiple numbers of line‐of‐sight (LOS) and non‐line‐of‐sight (NLOS) signals. The probability density function (PDF) of the MRC scheme over the SBX channel has been derived. The PDF‐based approach has been used to calculate the outage performance and average bit error rate of several modulation schemes for coherent and non‐coherent signals. It has also been shown how the diversity orders and the fading channel's parameters affect the system's performance. To authenticate the evaluated expressions, Monte‐Carlo simulation results are used for validation. The SBX model is used to characterise wireless communication environments that include multiple numbers of LOS and NLOS signals.