Optimal Waveform Research Articles

Comparative analysis of SWIFT and Grid-SWIFT waveforms for improved ion excitation and isolation resolution

Miniaturized mass spectrometers, with their increasing portability and performance enhancements, play a crucial role in selectively analyzing target compounds within complex mixtures, particularly in situ environments. As part of our ongoing efforts to enhance the analytical capabilities of the custom-built "brick" mass spectrometer, this study compared and optimized methods for ion isolation using Stored Waveform Inverse Fourier Transform (SWIFT) and Grid-SWIFT waveforms. The efficacy of the SWIFT and Grid-SWIFT waveforms in selective ion isolation was investigated, and through optimization of both waveforms, improved ion isolation efficiency, and peak resolution were demonstrated by adjusting waveform duration and amplitude. The results conclusively showed that Grid-SWIFT outperforms traditional SWIFT waveforms in enhancing the isolation of target ions. Additionally, a novel simulation-based approach was developed to simulate the behavior of ion trajectories under the SWIFT and Grid-SWIFT waveforms within LIT to provide a theoretical basis for better performance of the Grid-SWIFT waveforms. Results show that longer waveform durations help reduce energy leakage, providing higher isolation efficiency. Grid-SWIFT waveforms exhibited significantly less energy leakage compared to SWIFT waveforms. Consequently, using Grid-SWIFT as isolation waveforms improved the mass spectra' intensity and resolution.

Joint Design of Transmit Waveform and Altitude for Unmanned Aerial Vehicle-Enabled Integrated Sensing and Wireless Power Transfer Systems

Recently, unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) has received great attention as a promising technology for providing stable power to energy-constrained devices by navigating three-dimensional (3D) space, particularly in challenging environments such as maritime networks and smart cities. Additionally, UAV-enabled radar sensing has gained significant attention as a key technology for future 6G networks, as it enables high-accuracy sensing for various applications, such as target detection and tracking, surveillance, and environmental monitoring, as well as autonomous UAV operation. In this regard, we investigated UAV-enabled integrated sensing and wireless power transfer (ISWPT) systems that combine radar sensing and WPT operations on a unified hardware platform, sharing the same spectrum of resources. In order to accurately sense multiple targets and efficiently transfer power to multiple devices at the same time, we propose a method for jointly designing the transmit waveform and UAV altitude, taking into account the fundamental trade-off between radar sensing performance with the desired beam pattern and WPT performance with the desired harvested power of the devices. We first developed an effective method to obtain the optimal waveform and altitude by solving a challenging non-convex optimization problem. Based on this, we developed another efficient, low-complexity method by exploring a novel transmit waveform and optimizing its parameters to reduce computational complexity and thereby lower power consumption in UAVs. The numerical results verify that the proposed method significantly improves both radar sensing and WPT performance, as well as substantially reduces computational complexity.

Cognitive Radar Waveform Selection for Low-Altitude Maneuvering-Target Tracking: A Robust Information-Aided Fusion Method

In this paper, we introduce an innovative interacting multiple-criterion selection (IMCS) idea to design the optimal radar waveform, aimingto reduce tracking error and enhance tracking performance. This method integrates the multiple-hypothesis tracking (MHT) and Rao–Blackwellized particle filter (RBPF) algorithms to tackle maneuvering First-Person-View (FPV) drones in a three-dimensional low-altitude cluttered environment. A complex hybrid model, combining linear and nonlinear states, is constructed to describe the high maneuverability of the target. Based on the interacting multiple model (IMM) framework, our proposed IMCS method employs several waveform selection criteria as models and determines the optimal criterion with the highest probability to select waveform parameters. The simulation results indicate that the MHT–RBPF algorithm, using the IMCS method for adaptive parameter selection, exhibits high accuracy and robustness in tracking a low-altitude maneuvering target, resulting in lower root mean square error (RMSE) compared with fixed- or single-waveform selection mechanisms.

Photoacoustic Waveform Design for Optimal Parameter Estimation Based on Maximum Mutual Information

Waveform design is a potentially significant approach to improve the performance of an imaging or detection system. Photoacoustic imaging is a rapidly developing field in recent years; however, photoacoustic waveform design has not been extensively investigated. This paper considers the problem of photoacoustic waveform design for parameter estimation under constraints on input energy. The use of information theory is exploited to formulate and solve this optimal waveform design problem. The approach yields the optimal waveform power spectral density. Direct inverse Fourier transform of the optimal waveform frequency spectrum amplitude is proposed to obtain a real waveform in the time domain. Absorbers are assumed to be stochastic absorber ensembles with uncertain duration and location parameters. Simulation results show the relationship between absorber parameter distribution and the characteristics of optimal waveforms. Comparison of optimal waveforms for estimation, optimal waveforms for detection (signal-to-noise ratio) and other commonly used waveforms are also discussed. The symmetry properties of the forward and inverse Fourier Transforms are used to analyze the time and frequency properties and provide a heuristic view of how different goals affect the choice of waveform.

Requirements for Standard and I/O Cell Library Domestic Characterization System Development

The article is devoted to define requirements and discover specific featuresfor domestic standard cell and I/O libraries characterization EDA tool. A general structure of the library characterization system is presented. The basic requirements indicted for the system are considered and analyzed in the article. A comparative analysis of correspondence to these requirements for domestic and foreign characterization tools is done. The specific features the domestic library characterization system should satisfy are formulated. Among the main features the following are outlined in the article: compatibility and support of domestic OS, support of well-known foreign and domestic Spice-simulators, Russian language support for documentation, scalability, ensuring confidence of the output data. A brief review of typical tasks, intrinsic for characterization tool development and corresponding algorithms, required for its resolving is given. The following issues along with appropriate proposals for its solution are mentioned: automated definition of optimal input waveforms for sequential cells initialization, searching for maximum capacitance load for the cell, setup and hold parameters calculation for sequential cells, method of optimal output current PWL approximation for CCS parameters calculation. As a conclusion of the investigation the current status of domestic characterization systems development is analyzed. In the outcome a problem of domestic library characterization tool that aligned with all the requirements and support the specific features defined above has been raised.

Optimal radar ranging pulse to resolve two reflectors

Previous work established fundamental bounds on subwavelength resolution for the radar range resolution problem, called superradar []. In this work, we identify the optimal waveforms for distinguishing the range resolution between two reflectors of identical strength, leveraging results in quantum metrology. We discuss both the unnormalized optimal waveform as well as the best square-integrable pulse and their variants. Using orthogonal function theory, we give an explicit algorithm to optimize the wave pulse in finite time to have the best performance. We also explore range resolution estimation with unnormalized waveforms with multiparameter methods to also independently estimate loss and time of arrival. These results are consistent with the earlier single parameter approach of range resolution only and give deeper insight into the ranging estimation problem. Experimental results are presented using radio pulse reflections inside coaxial cables, showing robust range resolution smaller than a tenth of the inverse bandlimit, with uncertainties close to the derived Cramér-Rao bound. Published by the American Physical Society 2024

High-Resolution Dipole Remote Detection Logging Based on Optimal Nonlinear Frequency Modulation Excitation.

In order to improve the detection range and imaging resolution of dipole remote detection logging, an optimal nonlinear frequency modulation (ONLFM) excitation method is proposed in this paper. In this method, the optimal waveform model of the sound source is designed with objective functions of SNR and resolution to obtain the highest resolution under the condition of the required SNR. This optimal model is a multi-constraint optimization problem, and the simulated annealing method has been used to solve it. Solving the optimal model can obtain the optimal spectrum, and the ONLFM waveform can be designed by using the stationary phase principle. Compared with the electric pulse sound source used in traditional technology, this ONLFM sound source can improve the energy and extend the frequency band range of the reflected wave, which can provide the higher resolution and SNR. The simulation results show that the ONLFM sound source can effectively improve the SNR and resolution of the reflected wave, and the detection range and imaging resolution of dipole shear wave remote detection will be improved.

Enhancing fatigue performance of AA6063-T6 fasteners through novel electromagnetic cold expansion using a double-frequency discharge

Non-contact electromagnetic cold expansion process (EMCE) represents a highly promising way to enhance the fatigue performance of fasteners. However, within the current technological framework, the necessity for dual power supplies and an accurate discharge control system has constrained the development and application of this technique. To address this, a novel EMCE process utilizing a double-frequency discharge is proposed. This process is accompanied by the development of an electromagnetic system with only one set of power supply to generate a current composed of a gradual-ascending and rapid-descending stage. This current induces a significant radially outward Lorentz force, facilitating hole expansion and introducing residual compressive stress around the hole, thus increasing the fatigue life of the fasteners. The experimental results demonstrate a remarkable enhancement in fatigue life for samples treated with the EMCE process when compared to untreated ones, showing an impressive 6.8-fold, 4.9-fold, and 1.6-fold increase at stress loads of 120 MPa, 130 MPa, and 150 MPa, respectively. Microstructural analysis reveals that the processed components exhibit favorable surface integrity, and there is no significant grain refinement near the hole. Moreover, it is found that there existed optimal current waveform to maximize fatigue life. These findings hold significance in understanding the EMCE process and advancing its practical applicability.

Waveform optimization for future wireless communication: numerical simulation under mobile and vehicular scenarios in 5G and beyond

Code Division Multiple Access (CDMA) and Orthogonal Frequency Division Multiplexing (OFDM) are multicarrier regulating systems developed for quick communication. OFDM and its improved multi-carrier regulation technique employ equally distributed orthogonal sub-carriers for the transmission of data. These sub-carriers are modified using a conventional tweak plot, maintaining full information rates comparable to single carrier regulation schemes. The research also compares the two 5G modulation techniques, FBMC and UFMC, to OFDM, the 4G communication modulation technology. To evaluate the benefits of each contender, we compare important characteristics of different modulation approaches. The research compares the 5G modulation techniques FBMC and UFMC to OFDM, focusing on factors like power spectrum density, spectral efficiency, Bit Error rate, and Peak to Average Power Radio. To boost channel capacity and decrease interferences, the approach merges three alternative 5G waveforms under the LTE-V paradigm which is a specialized mode or configuration of Long Term Evolution (LTE) technology designed specifically for vehicular communication. MATLAB simulations show that FBMC performs better in terms of BER and capacity. In scenarios characterized by high interference due to power domain multiplexing and vehicular environment, FBMC demonstrates a maximum capacity that is 3.5 times greater than OFDM. However, in low-interference conditions, FBMC’s capacity exceeds UFMC’s by only a marginal 5%.

A Novel Waveform Optimization Method for Orthogonal-Frequency Multiple-Input Multiple-Output Radar Based on Dual-Channel Neural Networks.

The orthogonal frequency-division multiplexing (OFDM) mode with a linear frequency modulation (LFM) signal as the baseband waveform has been widely studied and applied in multiple-input multiple-output (MIMO) radar systems. However, its high sidelobe levels after pulse compression affect the target detection of radar systems. For this paper, theoretical analysis was performed, to investigate the causes of high sidelobe levels in OFDM-LFM waveforms, and a novel waveform optimization design method based on deep neural networks is proposed. This method utilizes the classic ResNeXt network to construct dual-channel neural networks, and a new loss function is employed to design the phase and bandwidth of the OFDM-LFM waveforms. Meanwhile, the optimization factor is exploited, to address the optimization problem of the peak sidelobe levels (PSLs) and integral sidelobe levels (ISLs). Our numerical results verified the correctness of the theoretical analysis and the effectiveness of the proposed method. The designed OFDM-LFM waveforms exhibited outstanding performance in pulse compression and improved the detection performance of the radar.

Waveform Optimization for the In Vitro Detection of Caffeic Acid by Fast-Scan Cyclic Voltammetry.

Caffeic acid is a polyphenol of critical importance in plants, involved in a variety of physiological processes including lignin formation, cellular growth, stress response, and external signaling. This small molecule also acts as a powerful antioxidant and thus has therapeutic potential for a variety of health conditions. Traditional methods of detecting caffeic acid lack appropriate temporal resolution to monitor real time concentration changes on a subsecond time scale with nM detection limits. Here we report on the first usage of fast-scan cyclic voltammetry with carbon fiber microelectrodes for the detection of caffeic acid. Through the use of flow injection analysis, the optimal waveform for its detection under acidic conditions at a scan rate of 400 V/s was determined to be sawtooth-shaped, from 0 to 1.4 to -0.4 to 0 V. Signal was linear with concentration up to 1 μM with a sensitivity of 44.8 ± 1.3 nA/μM and a detection limit of 2.3 ± 0.2 nM. The stability of its detection was exceptional, with an average of 0.96% relative standard deviation across 32 consecutive injections. This waveform was also successful in detecting other catechol-based plant antioxidants including 5-chlorogenic acid, oleuropein, rosmarinic acid, chicoric acid, and caffeic acid phenethyl ester. Finally, we show the successful use of fast-scan cyclic voltammetry in monitoring the degradation of caffeic acid by polyphenol oxidase on a subsecond time scale via a novel modification of a Ramsson cell. This work demonstrates that fast-scan cyclic voltammetry can be used to successfully monitor real-time dynamic changes in the concentrations of catechol-containing plant polyphenols.

Optimization algorithms for transmit waveform design in radar-centric dual-function radar-communication systems

We study the transmit waveform optimization problem in multiple-input-multiple-output (MIMO) dual-function radar-communication (DFRC) systems. A penalty-based formulation is adopted where engineering concerns on radar and communication are integrated in a weighted manner. We transform the original problem into an unconstrained formulation and propose a novel waveform synthesis algorithm via combination of multiple algorithm updates. The combination operation experimentally reaches a better objective value than without. We develop two combination strategies and invent a shrinkage-expansion line search method for monotonicity maintenance. Numerical experiments show that the proposed algorithm suffices to generate constant modulus waveforms which achieve radar and communication purposes.

Driving waveform optimization of electrowetting displays based on pixel's 2-D model for reducing oil reflux.

Electrowetting displays (EWD) are believed to represent a new generation of electronic paper technology with fast responses, high reflectivity, and low power consumption. Despite their bright market prospects, the luminance stability of displays is still hindered by oil film reflux. So, we presented a combination of simulation and experimentation to enhance the performance of EWD. Firstly, an EWD simulation model was established using the phase field method (PFM). To ensure the accuracy of the model, it was proposed that the use of velocity field parameters could suppress mass non-conservation. During a 10-second simulation process, the total mass decreased by only 7.94x10-6%. Furthermore, the charge accumulation field was introduced to simulate oil film reflux. For the 5-second simulation, the maximum charge accumulation in the DC driving waveform was 2.61x10-5C/m2. Meanwhile, it was demonstrated that the AC driving waveform reduced charge accumulation in the three-phase contact line (TPCL) by 7.62% compared to the DC driving waveform. Based on this simulation model, a driving waveform was proposed, which included a driving waveform with a gradient changing waveform to achieve fast opening, and an alternating current (AC) driving waveform stage to inhibit the charge accumulation. The experimental results indicated that the maximum luminance fluctuation was 8.82, and the luminance data variance was 3.34 by using the proposed driving waveform. Compared to the traditional waveform, the response time was improved by 75.9%, the luminance was improved by 4.70%, and the luminance fluctuation stability improved by 79.34%.

Load Design and Waveform Optimization for Near-Field Wireless Powered Communications Using a Coil Array

Load Design and Waveform Optimization for Near-Field Wireless Powered Communications Using a Coil Array

Synergistic enhancement of pulsed light-induced H2 photoproduction in Chlamydomonas cells by optimal sulfite concentration and light waveform

Pulsed light illumination stands out as a noteworthy technique for photosynthetic H2 production, playing a crucial role in eliminating O2 and activating hydrogenase enzymes. However, further improvements are essential to make H2 photoproduction suitable for future commercial applications. In our study, we observed a distinct enhancement in pulsed light-induced H2 photoproduction in the unicellular green alga Chlamydomonas reinhardtii when treated with the optimal concentration of the mild O2 scavenger Na2SO3. This improvement was a result of reduced O2 content, increased hydrogenase enzyme activity, and suppressed H2-uptake activity. Furthermore, our findings indicate that exposing Na2SO3-treated C. reinhardtii to optimal light waveform continues to significantly boost pulsed light-induced H2 photoproduction, attributed to the alleviation of impaired photosystem II activity. Altogether, the combined application of optimal sulfite concentration and light waveform effectively enhances pulsed light-induced photosynthetic H2 production in the green alga C. reinhardtii.

Waveform Optimization Control of an Active Neutral Point Clamped Three-Level Power Converter System

Currently, the escalating integration of renewable energy sources is causing a steady weakening of grid strength. When grid strength is weak, interactions between inverters or those between inverters and grid line impedance can provoke widespread oscillations in the power system. Additionally, the diverse DC voltage application characteristics of power converter systems (PCS) may lead to over-modulation, generating narrow pulse issues that further impact control of the midpoint potential balance. Existing dead-time elimination methods are highly susceptible to current polarity judgments, rendering them ineffective in practical use. PCS, due to inherent dead-time effects, midpoint potential imbalances in three-level topologies, and narrow pulses, can elevate low-order harmonic content in the output voltage, ultimately distorting grid-connected currents. This is particularly susceptible to causing resonance in weak grids. To enhance the output voltage waveform of PCS, this article introduces a comprehensive compensation control strategy that combines dead-time elimination, midpoint potential balance, and narrow pulse suppression, all based on an active neutral point clamped (ANPC) three-level topology. This strategy gives precedence to dead-time elimination and calculates the upper and lower limits of the zero-sequence available for midpoint potential balance while fully compensating for narrow pulses. By prioritizing dead-time elimination, followed by narrow pulse suppression and finally midpoint potential balance, this method decouples the coupling between these three factors. The effectiveness of the proposed method is validated through semi-physical simulations.

Efficient symbol level precoding design for full-duplex integrated sensing and communication systems

Full-duplex (FD) integrated sensing and communication (ISAC) system attracts much attention because adopting the FD mode can enhance the transmission efficiency and reduce the transmission time of the ISAC system. However, the inevitable self-interference (SI) in FD mode would result in severe performance degradation. This paper considers the FD ISAC system and investigates a symbol-level precoding (SLP) design, which minimizes the Cramér-Rao Bound of target angle estimation while considering the constant-envelope power restraint, SI suppression and the quality of service requirement. Due to the non-convex fractional problem and the unit-modulus constraint, the optimization problem is reformulated by implementing the Schur complement, where the optimal waveform is obtained via the semidefinite programming algorithm. The SLP design that optimizes each symbol vector for all users may suffer high computational complexity of matrix multiplication with high numbers of users. A grouped SLP strategy in which the communication users are divided into several groups on the basis of channel correlation is proposed to reduce the complexity. The proposed grouped SLP design only suppresses group-to-group interference and converts the intra-group interference into a constructive interference, which can reduce the dimension of each precoded signal significantly, resulting in a low computational complexity. Simulation results illustrate that the proposed SLP design can effectively mitigate SI, which can improve the accuracy of target detection. Moreover, the proposed grouped-SLP design can further reduce computational complexity without dramatic performance degradation.

Online Bayesian optimization of vagus nerve stimulation.

Objective.In bioelectronic medicine, neuromodulation therapies induce neural signals to the brain or organs, modifying their function. Stimulation devices capable of triggering exogenous neural signals using electrical waveforms require a complex and multi-dimensional parameter space to control such waveforms. Determining the best combination of parameters (waveform optimization or dosing) for treating a particular patient's illness is therefore challenging. Comprehensive parameter searching for an optimal stimulation effect is often infeasible in a clinical setting due to the size of the parameter space. Restricting this space, however, may lead to suboptimal therapeutic results, reduced responder rates, and adverse effects.Approach. As an alternative to a full parameter search, we present a flexible machine learning, data acquisition, and processing framework for optimizing neural stimulation parameters, requiring as few steps as possible using Bayesian optimization. This optimization builds a model of the neural and physiological responses to stimulations, enabling it to optimize stimulation parameters and provide estimates of the accuracy of the response model. The vagus nerve (VN) innervates, among other thoracic and visceral organs, the heart, thus controlling heart rate (HR), making it an ideal candidate for demonstrating the effectiveness of our approach.Main results.The efficacy of our optimization approach was first evaluated on simulated neural responses, then applied to VN stimulation intraoperatively in porcine subjects. Optimization converged quickly on parameters achieving target HRs and optimizing neural B-fiber activations despite high intersubject variability.Significance.An optimized stimulation waveform was achieved in real time with far fewer stimulations than required by alternative optimization strategies, thus minimizing exposure to side effects. Uncertainty estimates helped avoiding stimulations outside a safe range. Our approach shows that a complex set of neural stimulation parameters can be optimized in real-time for a patient to achieve a personalized precision dosing.

Recurrent Waveform Optimization for Desired Range-Doppler Profile With Low Probability of Interception: A Particle Filter Approach

Recurrent Waveform Optimization for Desired Range-Doppler Profile With Low Probability of Interception: A Particle Filter Approach

A hybrid simulator with novel bicone-wire grid antenna.

The simulator is an indispensable device for the study of high-altitude electromagnetic pulse (HEMP) effects. In order to improve the quality of the electric field waveforms of the HEMP simulator, we carried out simulation and experimental studies for the biconical-wire grid antenna. A new bicone-wire grid antenna HEMP simulator was designed by using skeletonized cones instead of solid cones, which can substantially improve the mobility of the simulator. The effects of different aspect ratios and different cone structures of the simulator on the waveform and distribution characteristics of the electric field were analyzed. The accuracy of the simulation results was verified by testing the bicone-wire grid antenna simulator with the new structure. The results obtained are as follows: First, the simulator can provide a HEMP environment compliant with the International Electrotechnical Commission (IEC) standard in an area of 5 × 6 × 2m3. Second, the simulator possesses optimal waveform quality and working space among simulators with different aspect ratios. Finally, the influence of using skeletonized cones instead of solid cones on the simulator's electric field waveforms is negligible, and the mobility of the new simulator is significantly improved compared to the original simulator.