Frequency Limit Research Articles

Impedance Reshaping Strategy for Battery Energy Storage Systems Based on Partial Power Conversion

To avoid additional component losses while significantly improving the energy conversion efficiency of battery energy storage systems, the application of series-connected partial power converter (S-PPC) technology in battery energy storage systems is investigated in this study. In the S-PPC battery energy storage system configuration, coupling effects exist between the dc-link side and the battery-series side. The impedance modeling of a battery energy storage system is performed while taking these coupling effects into consideration. To address the instability observed during battery discharge conditions, an impedance reshaping control strategy that is suitable for the S-PPC battery energy storage system is proposed. The proposed method focuses on adjusting the input impedance of the load converter within a limited frequency band centered on the system’s oscillation frequency. This targeted approach significantly improves the stability of the system while ensuring ease of implementation and maintaining high reliability. Finally, the experimental results validate the theoretical analysis.

Frequency-independent damping models for a high-rise building with simultaneous horizontal and vertical seismic motions

Recent seismic analyses indicate that the structural damping ratio should be considered frequency-independent, for safe and accurate estimations. In response, damping models like the Wilson–Penzien (WP) damping model, that is one of the modal damping, provide frequency independence across all modes; however, these models require considerable computational resources, especially for large-scale models. While Rayleigh damping is computationally efficient, it maintains a nearly constant damping ratio only within a limited frequency range. To address these limitations, several alternative damping models have been introduced, such as uniform (UN), causal hysteretic (CH), and extended Rayleigh (ER). We use the factor Wξ to represent the frequency range where the damping ratio remains approximately constant, defined as the ratio of maximum to minimum frequencies (fmax/fmin), within a specified tolerance of the target damping ratio. For Rayleigh damping, Wξ = 3.7, while the CH and ER models achieve Wξ values greater than 20. Although the UN model achieves a high Wξ, it demands large computational resources in the implicit analyses, commonly used for seismic response studies. In this study, we address the simultaneously inputting horizontal and vertical seismic motion into a large-scale dynamic analysis model of a high-rise building. In this analysis, horizontal, vertical, and local beam vibration modes spanning a wide frequency range appeared. Considering that these modes require the same damping ratio, damping models with Wξ values of 50 or higher are desirable. However, this threshold considerably exceeds Wξ values achievable with the existing models, rendering these models unsuitable for the intended application. Therefore, we propose and validate the efficiency of two new damping models (ER-W and CH19) that meet this requirement by improving existing models. Using these damping models, it is possible to analyze the horizontal and vertical modes and local vibration modes of the beam, assuming a simultaneous horizontal and vertical input to a high-rise building.

Utilizing Hertzian contact model for a vibro-impact unimorph bistable energy harvester to increase working frequency bandwidth and harvested power

The typical bistable energy harvester (TBEH) systems usually have a limited working frequency bandwidth and low performance in energy conversion. This paper proposed a unilateral vibro-impact piezoelectric cantilever beam energy harvester. The novel vibro-impact bistable energy harvester (VIBEH) improves the drawbacks of a TBEH system. Despite previous research, in this paper, the collision process is modeled by nonlinear Hertzian contact theory. Nonlinear contact law adds strong nonlinearity to the harvester. By using the extended Hamilton principle and Euler-Lagrange equation, the governing equations of the energy harvester are derived and solved numerically. The existing nonlinearities cause frequency leaks and affect the type of motion (inter-well or intra-well motion) by changing the equilibrium points of the system. By applying nonlinear tools like Poincare diagrams, bifurcation plots, and phase portraits, the effects of periodic or chaotic oscillations will be studied on the performance of the VIBEH system. Finally, the effects of barrier stiffness, initial gap, barrier location, and electrical load are determined on the performance of the VIBEH system. The obtained results showed that using the VIBEH system could broaden the working frequency bandwidth by about 71.9%. Furthermore, the optimized values of impacting properties and electrical load are examined.

Neuronal complexity tracks changes of epileptic activity and identifies epilepsy patients independent of interictal epileptiform discharges.

To date, the identification of objective biomarkers of neural epileptic activity (EA) remains challenging. We therefore investigated whether neuronal complexity could serve as an interictal electroencephalographic measure of EA, independent of interictal epileptiform discharges (IEDs). By tapering anti-seizure medication (ASM) during video-EEG (electroencephalography) monitoring (VEM), we studied whether changes in neuronal complexity could reliably indicate the increase in EA and identify patients with epilepsy. The study included 27 patients with unilateral mesial temporal lobe epilepsy (TLE) and 24 control patients with non-epileptic episodes (NEEs) only, each undergoing ASM reduction during VEM. Thirteen additional patients undergoing intracranial recordings during VEM were included to study the relation of surface EEG complexity to intracranial IED. Neuronal complexity was quantified using sample entropy. Delta power served as a control parameter. Receiver-operating characteristic (ROC) analysis was used to evaluate diagnostic performance. As ASM was reduced, patients with epilepsy showed a significant decrease in neuronal complexity over consecutive days (p = .0008). In contrast, patients with NEE showed no significant change in neuronal complexity (p = .78). Delta power in contrast increased and did not differ significantly between patients with TLE and patients with NEE (p = 1). ROC analysis demonstrated that neuronal complexity effectively distinguished between patients with epilepsy and patients with NEE (area under the curve [AUC] = .76), whereas delta power performed at chance level (AUC = .5). Analysis of simultaneously recorded surface and intracranial EEG showed that hippocampal IEDs are followed by an increase in surface EEG delta power (p = 1.8 × 10-18) without any significant change in complexity (p = .39). An increase in EA caused by ASM reduction resulted in a loss of neuronal complexity in surface EEG recordings of patients with epilepsy, independent of IEDs. These findings suggest that neuronal complexity could serve as a potential biomarker to differentiate between epilepsy patients and those with NEEs only. This holds promise for improving the clinical evaluation of EA in epilepsy, addressing the limitations of seizure frequency and IED identification.

Minimally disruptive auditory cues: their impact on visual performance in virtual reality

AbstractVirtual reality (VR) has the potential to become a revolutionary technology with a significant impact on our daily lives. The immersive experience provided by VR equipment, where the user’s body and senses are used to interact with the surrounding content, accompanied by the feeling of presence elicits a realistic behavioral response. In this work, we leverage the full control of audiovisual cues provided by VR to study an audiovisual suppression effect (ASE) where auditory stimuli degrade visual performance. In particular, we explore if barely audible sounds (in the range of the limits of hearing frequencies) generated following a specific spatiotemporal setup can still trigger the ASE while participants are experiencing high cognitive loads. A first study is carried out to find out how sound volume and frequency can impact this suppression effect, while the second study includes higher cognitive load scenarios closer to real applications. Our results show that the ASE is robust to variations in frequency, volume and cognitive load, achieving a reduction of visual perception with the proposed hardly audible sounds. Using such auditory cues means that this effect could be used in real applications, from entertaining to VR techniques like redirected walking.

Floquet analysis on an irradiated nodal surface semimetal with non-symmorphic symmetry

A nodal surface semimetal (NSSM) features symmetry enforced band crossings along a surface within the three-dimensional (3D) Brillouin zone (BZ) and a presence of a nonsymmorphic symmetry there pushes such surfaces to stick to the BZ center or boundaries. The topological robustness of the same does not always come with nonzero Berry fluxes. We consider two such NS, one with zero and another with nonzero topological charges and investigate the effect of light irradiation on them. We find that depending on the state of polarization, one can obtain additional Weyl points/NS in the corresponding Floquet Hamiltonians. Particularly, using a simple two band spinless/spin polarized models with no spin orbit coupling, we emphasize the low energy behavior of the continuum Hamiltonians close to the band crossings and its evolution in a Floquet system in the high frequency limit. In the Floquet system, we also find the NS to perish or new multi Weyl points to get popped up for different polarization scenario or different NSSM Hamiltonians. Our findings open up important avenues on what out of equilibrium NSSM systems can offer in many active fields including quantum computations.

Low noise InGaAs/InP single-photon detector with DC to 1 GHz tunable gate frequency

An InGaAs/InP single-photon detector (SPD) typically operates in gated mode, but the capacitive response of a single-photon avalanche diode introduces spike noise, obscuring the avalanche signal. Most avalanche signal discrimination schemes cannot completely eliminate spike noise, resulting in residual noise. Limited by residual noise, these schemes have large noise and a limited frequency tuning range. However, for applications like quantum key distribution and laser ranging, a low noise, frequency-tunable InGaAs/InP SPD is crucial for enhancing system performance. Here, we propose a (residual noise assisted) discrimination method that aligns the maximum amplitude of the avalanche signal with the peak of the residual noise. This method turns the residual noise from adversity into an advantage for signal discrimination. With this method, we achieve tunable gating frequency from DC to 1 GHz. Additionally, this method enables the discrimination of weak avalanche signals, allowing effective single-photon detection at low avalanche gain. Across the entire tuning range, at a 20% detection efficiency, the dark count rate is approximately 5.0×10−7 per gate, and the afterpulse probability is less than 1.0%, significantly lower than in previous experiments. The proposed SPD exhibits low noise and a wide tunable gating frequency range, providing a reliable foundation for various applications.

A robust error sensing strategy for global active noise control in car cabins.

Global active noise control (ANC) systems reduce noise over the entire car cabin with robust performance even as the human head moves; however, they have not been implemented in real-world applications. A robust error sensing strategy is proposed in this paper that is based on which a feasible global ANC system is realized in an electric car, and real-time ANC experiments demonstrate its effectiveness. Simulations based on measured road noise show that using evenly distributed error sensors is a robust error sensing strategy for different car speeds and the upper limit frequency of 3 dB global control is inversely proportional to the equivalent distance between error sensors. Real-time experiments with a 5-seat A-class sedan demonstrate that an average noise reduction of 3.8 dB was achieved between 50 and 250 Hz with 12 evenly distributed error sensors using the four standard car audio loudspeakers as secondary sources. Virtual sensing techniques can be integrated to constitute a more practical system without obstructing the movement of human heads. The findings in this study establish a benchmark for global noise control in car cabins and can be a starting point for future optimization of the system and implementation of adaptive algorithms.

Four-class ASME BCI: investigation of the feasibility and comparison of two strategies for multiclassing.

The ASME (stands for Auditory Stream segregation Multiclass ERP) paradigm is proposed and used for an auditory brain-computer interface (BCI). In this paradigm, a sequence of sounds that are perceived as multiple auditory streams are presented simultaneously, and each stream is an oddball sequence. The users are requested to focus selectively on deviant stimuli in one of the streams, and the target of the user attention is detected by decoding event-related potentials (ERPs). To achieve multiclass ASME BCI, the number of streams must be increased. However, increasing the number of streams is not easy because of a person's limited audible frequency range. One method to achieve multiclass ASME with a limited number of streams is to increase the target stimuli in a single stream. Two approaches for the ASME paradigm, ASME-4stream (four streams with a single target stimulus in each stream) and ASME-2stream (two streams with two target stimuli in each stream) were investigated. Fifteen healthy subjects with no neurological disorders participated in this study. An electroencephalogram was acquired, and ERPs were analyzed. The binary classification and BCI simulation (detecting the target class of the trial out of four) were conducted with the help of linear discriminant analysis, and its performance was evaluated offline. Its usability and workload were also evaluated using a questionnaire. Discriminative ERPs were elicited in both paradigms. The average accuracies of the BCI simulations were 0.83 (ASME-4stream) and 0.86 (ASME-2stream). In the ASME-2stream paradigm, the latency and the amplitude of P300 were shorter and larger, the average binary classification accuracy was higher, and the average weighted workload was smaller. Both four-class ASME paradigms achieved a sufficiently high accuracy (over 80%). The shorter latency and larger amplitude of P300 and the smaller workload indicated that subjects could perform the task confidently and had high usability in ASME-2stream compared to ASME-4stream paradigm. A paradigm with multiple target stimuli in a single stream could create a multiclass ASME BCI with limited streams while maintaining task difficulty. These findings expand the potential for an ASME BCI multiclass extension, offering practical auditory BCI choices for users.

On computation of finite-part integrals of highly oscillatory functions

In this paper, we propose some methods to compute finite-part integral involving hypersingular and highly oscillatory factors. We first write the integral as the Cauchy principle value integral which is computed based on the variable upper limit integral and frequency parameterization. For computing the nonsingular integral, we use the integration by parts and interpolation. On this basis, we get an asymptotic method and a Filon-type method. In order to test the efficiency of the proposed methods and verify the correctness of the proposed theories, some numerical experiments are performed.

Rumus Umum Pelabelan L(2, 1) pada Graf Koprima Grup Bilangan Bulat Modulo m

Groups are nonempty sets equipped with binary operations and fulfill certain conditions. One example of a group is the group of integers modulo . A coprime graph of a group is a graph whose vertices are elements in and any two vertices in are directly connected if and only if the greatest common factor of the orders x and y are relatively prime. labeling has important applications in wireless telecommunication networks, where there are limited radio frequencies available and adjacent transmitters cannot use the same frequency. To overcome this problem, frequency assignment is done using the concept of labeling, where transmitters are symbolized as vertices connected by edges. labeling is a graph labeling technique that assigns non-negative integer labels to graph vertices with the rule that two directly connected vertices must have a minimum label difference of two, and two vertices that are two apart must have a minimum label difference of one. The purpose of this research is to find out the general formula for the labeling on the coprime graph of the group of integers modulo and the general formula for the minimum value of the largest label of the labeling. The steps taken in this research are to determine the coprime graph form of the group of integers modulo . Then label each vertex with a non-negative label. Then label each vertex with labeling rule. From the result of this research, it can be concluded that the coprime graph of integer group modulo has a labeling with .

AC Magnetometry Using Nano-ferrofluid Cladded Multimode Interferometric Fiber Optic Sensors for Power Grid Monitoring Applications.

The AC magnetic field response of the superparamagnetic nano-ferrofluid is an interplay between the Neel and Brownian relaxation processes and is generally quantified via the susceptibility measurements at high frequencies. The high frequency limit is dictated by these relaxation times which need to be shorter than the time scale of the time varying magnetic field for the nano-ferrofluid to be considered in an equilibrium state at each time instant. Even though the high frequency response of ferrofluid has been extensively investigated for frequencies up to GHz range by non-optical methods, harnessing dynamic response by optical means for AC magnetic field sensing in fiber-optic-based sensors-field remains unexplored. Instead, the incorporation of nano-ferrofluid as sensing materials has been only limited to DC magnetic field sensing, often citing their long response time as a limiting factor to AC field sensing. This work reports the finding of high frequency (up to 15 kHz) AC magnetic field sensing capability of nanomagnetic fluid as the cladding material of a fiber-optic multimode interferometry (MMI) structure optimized for the fourth self-imaging spectral response. The key parameter enabling high frequency response is the short response time (<1 ms) achieved by optimizing both the sensing structure and nano-ferrofluid solution. Focus has been imparted on 60 Hz line-frequency profiles of various current/magnetic fields to test the efficacy of these sensors in metering and monitoring current and current-induced magnetic fields in the electrical power grid systems. The magnetic field sensitivity of 240 mV/Gauss per dBm of transmitted power was achieved for 60 Hz field applied via Helmholtz coil, whereas the 60 Hz AC current sensitivity of 2.83 mV/A was measured due to magnetic field induced by current in a straight conducting wire.

Bioacoustic and Ecoacoustic Data in Audiovisual Core

Audiovisual Core (Audiovisual Core Maintenance Group 2023), is the TDWG standard for metadata related to biodiversity multimedia. The Audiovisual Core Maintenance Group has been working to expand the standard to provide the terms necessary for handling sound recordings. Audiovisual Core can now handle acoustic metadata related to biodiversity from single species (bioacoustics) to the ecosystem scale (ecoacoustics). Bioacoustics The Natural History Museum, London has a significant collection of recorded insect sounds (Ragge and Reynolds 1998) that are often directly linked to museum specimens (Fig. 1). The sound collection has previously been digitised and made available electronically through the BioAcoustica project (Baker et al. 2015). The BioAcoustica platform allows for annotation of audio files with tags including "Call" for deliberate sound made by an organism, "Voice Introduction" for metadata, and "Extraneous Noise." These boundaries are defined by their start and end times (in seconds) relative to the start of the file (Fig. 2). Ecoacoustics Ecoacoustics deals with the sounds present within an entire soundscape or ecosystem. The calls of individual species form the biological part of the soundscape (biophony) alongside sounds produced by non-living natural sources (geophony) and humans (anthropophony). Individual components are often defined by date and time boundaries, and sometimes by upper and lower frequency limits (Fig. 3). Regions of Interest The recently added concept of a "Region of Interest" (ROI) allows for the annotation of sound files, identifying multiple regions within a single recording with time and/or frequency bounds. However, the vocabulary of ROI*1 is not just intended for sounds. Equivalent terms also allow for regions to be specified with images and videos. The use of well-defined annotations has the potential to generate large amounts of training data for machine learning models and provide a standard for generating observation records from these models (e.g., BirdNet, see Kahl et al. 2021), which can be verified by linking them to audio segments within a much larger recording. The development of a metadata standard for regions of interest has several interesting possibilities, including linking multiple observation records to a single soundscape recording (the recording acts similarly to a voucher specimen) and aggregating regions across multiple datasets to create larger corpora for training machine learning models.

A high-response-frequency bimodal network polyacrylate elastomer with ultrahigh power density under low electric field

Dielectric elastomers, used as driver modules, require high power density to enable fast movement and efficient work of soft robots. Polyacrylate elastomers usually suffer from low power density under low electric fields due to limited response frequency. Here, we propose a bimodal network polyacrylate dielectric elastomer which breaks the intrinsic coupling relationship between dielectric and mechanical properties, featuring relatively high dielectric constant, low Young’s modulus, and wide driving frequency bandwidth (~200 Hz) like silicones. Therefore, an ultrahigh power density (154 W kg−1@20 MV m−1, 200 Hz) is realized at low electric field and high resonance frequency, 75 times greater than at 10 Hz. Further, a rotary motor is developed, reaching an impressive speed of 1245 rpm at 19.6 MV m−1 and 125 Hz, surpassing previous acrylate-based motors and entering the high-speed domain of silicone-based motors. These findings offer a versatile strategy to fabricate high-power-density dielectric elastomers for low-electric-field soft actuators.

An adaptive load shedding methodology for renewable integrated power systems

System stability issues regarding frequency and voltage in modern power systems are growing in importance as they incorporate more and more complex components. To ensure a sustainable, pollution-free power generation, modern power systems are designed to incorporate more renewable generation sources than traditional ones. Therefore, in the event of a large-scale disruption event, conventional load-shedding strategies are unable to keep the voltage and frequency limit below the threshold value. The suggested approach takes into account this issue by rating load buses in relation to relevant frequency changes, their voltage stability, system load damping coefficients, and the introduction of green energy sources in place of fossil fuel-based ones. Battery Energy Storage Systems (BESS) are used in the proposed method to minimize load shedding amount required for conventional schemes. After determining the amount, the scheme dynamically chooses feeders as per relative weightage of the stability components (voltage, frequency) to ensure that the overall load shed amount is near to the calculated value. To verify this, the scheme is tested on IEEE 39 bus with python scripted simulation. There are four scenarios considering 250 MW, 500 MW and 1500 MW injection of PV based power generation sources with conventional generation loss of 800 MW and 1000 MW. The threshold frequency is considered 49.10 Hz. The total amount of BESS is 300 MW. For every scenario, it has been found that the methodology successfully maintains the system frequency above 49.10 Hz with a minimal amount of load shedding. Hence, the proposed methodology is able to maintain frequency stability for a modern power system with large-scale PV generation through adaptive feeder selection for load shedding.

A high-frequency, low-power resonant radio-frequency neutron spin flipper for high-resolution spectroscopy.

We present a resonant-mode, transverse-field, radio-frequency (rf) neutron spin flipper design that uses high-temperature superconducting films to ensure sharp transitions between uniform magnetic field regions. Resonant mode allows for low-power, high-frequency operation but requires strict homogeneity of the magnetic fields inside the device. This design was found to efficiently flip neutrons at 96.6 ± 0.6% at an effective frequency of 4MHz in bootstrap configuration with a beam size of 2.4 × 2.5 cm2 and a wavelength of 0.4nm. The high frequency and efficiency enable this device to perform high-resolution neutron spectroscopy with comparable performance with currently implemented rf flipper designs. The limitation of the maximum frequency was found due to the field homogeneity of the device. We numerically analyze the maximum possible efficiency of this design using a Bloch solver simulation with magnetic fields generated from finite-element simulations. We also discuss future improvements of the efficiency and frequency to the design based on the experimental and simulation results.

Low-cost IoT-Based sensors dashboard for monitoring the state of health of mobile harbor cranes: Hardware and software description

A cost-effective IoT-based real-time data acquisition and analysis hardware system was developed to enhance the performance of the mobile harbor cranes using a combination of a cost-effective quality control monitoring sensor dashboard (proximity sensors, angle position sensor, weight sensor, vibration sensor, and wind sensor), embedded microcontroller (Arduino), and embedded computer (Raspberry Pi). Hardware was operated using a specially developed novel Quality Control and Data Acquisition Multiprocessing software (QC-DAS). The QC-DAS can automatically collect and save real-time data of the sensors in a large-capacity SD card, monitor the state of health of the hardware, and transmit the real-time data of the sensors and the working state of the crane to an IoT server. The novelty of the QC-DAS design is that each function is encapsulated in a predefined module that is "immersed" in a message transmission medium. Modules interact by sending and receiving various signals through this medium. Modularity makes system design simpler, faster, and flexible. Thanks to modularity, users may incorporate their data processing modules when new sensors are added to match the system's needs. Thanks to modularity the DC-DAS can operate quality control hardware for any mobile cranes. There are several constraints in the quality control data acquisition system used by the Damietta Port Authority in Damietta, Egypt, SESCO TRANS company which cause the loading and unloading process to be slowed down. As a result, the SESCO TRANS company upgraded its quality control data acquisition system using the QC-DAS. The hardware was deployed for six months, during which the collected data was used to verify the crane's performance. The vibration produced by the slewing of the crane was monitored and compared with the bearing fault frequency limits, during the operation the wind speed was monitored and compared with the critical wind speed to stop the crane operation automatically, and the payloads data of the six months was collected and was used to calculate the working efficiency of the load and unload process of the crane. The results demonstrated that while maintenance costs were decreased, the crane load/unload procedure was improved. The SESCO TRANS company crane operators approved the developed approach and appreciated the achieved results.

Transient Dynamics of a Porous Sphere in a Linear Fluid

This article describes the unsteady translational motion of a porous sphere with slip-surface in a quiescent viscous fluid. Apart from its radius a and density ρs , the particle is characterized by its permeability parameter γ , slip-length l and effective viscosity-ratio ϵ for interior flow. The Reynolds number for the system is assumed to be small leading to negligible convective contribution, though the transient inertia for both the liquid and the solid is comparable to viscous forces. The resulting linearized but unsteady flow-equations for both inside and outside the porous domain are solved in time-invariant frequency domain by satisfying appropriate boundary conditions. The analysis ultimately renders frequency-dependent hydrodynamic friction for the suspended body. The frictional coefficient is computed under both low and high frequency limit for different values of γ, l and ϵ so that the findings can be compared to known results with impermeable surface. Moreover, the parametric exploration shows that the sphere acts like a no-slip body even with non-zero l if aγ ≫ 1/√ϵ . Scaling arguments from a novel boundary layer theory for flow inside porous media near interfaces explain this rather unexpected observation. Also, computed fluid resistance is incorporated in equation of motion for the particle to determine its time-dependent velocity response to a force impulse. This transient response shows wide variability with ρs, γ, l and ϵ insinuating the significance of the presented study. Consequently, the paper concludes that slip and permeability should be viewed as crucial features of submicron particles if unexpected variability is to be explained in nano-scale phenomena like nano-fluidic heat conduction or viral transmission. Thus, the theory and findings in this paper will be immensely useful in modeling of nano-particle dynamics.

Double Deep Q- energy aware Service allocation based on Dynamic fractional frequency reusable technique for lifetime maximization in HetNet-LTE network

The development of mobile communication in heterogeneous networks is incredible in providing various services through wireless cellular communication through advanced long-term evaluation networks. Increasing multi-concern services and frequencies in spectrum channels are highly layered to select the bandwidth to provide the fastest network without interference. Selecting the channel through macro cell selection is essential to improve network communication and provide the quickest service. Most frequency reuse techniques use service optimality and route selection-based protocols to enrich the packet flow. Still, the improper spectrum delights create more delay tolerance due to short-range service optimality due to energy loss by selecting the short spectrum signal to reuse, which doesn't support the lifetime improvement of the LTE network. To resolve these problems, we propose a Double Deep Q- energy-aware Service allocation based on a Dynamic fractional frequency reusable technique for lifetime maximization in the HetNet-LTE network. Initially, the heterogenous communication environment and node deplanement were carried out to construct the LTE network under the WCC. The communication logs are Route Table (RT), and its services are taken by all node LTE Communication Impact Rate (LTE-CIR). Then, the Backhaul Traffic Algorithm (BTA) is applied to predict the interference on traffic rate from the channel frequency margin. Select the balanced node using the Channel Interference Macro Cell Selection (CIMCS) technique. Considering frequency limits with the Double Deep Q- Network (DDQN) approach, energy-aware selects the optimal route to reuse the frequency level using Frequency Domain Packet Scheduling (FDPS) to improve communication. The proposed system improves the overall throughput by up to 97.8 % with adopted channel selection from the macro unit to improve the latency performance. Also, the interference frequency limits are dynamically reused at an energy optimal level with low-level delay tolerance to improve the link stability by up to 98.4 % with higher lifetime maximation in the LTE network.

Advanced Frequency Analysis of Signals with High-Frequency Resolution

In today’s era, it is important to analyze and utilize various signals in industrial or laboratory applications. Measured signals provide critical information about the controlled system, which can be contained precisely within a narrow frequency range. Many methods and algorithms exist to process such signals in both the time and frequency domains. In particular, signal processing in the frequency domain is primary in industrial practice because dominant components within a specific narrow frequency band are sought. The discrete Fourier transformation (DFT) algorithm is the tool used in practice to find these frequency components. The DFT algorithm provides the full frequency spectrum with a higher number of calculation steps, and its spectrum frequency resolution is low. Therefore, research has focused on finding a method to achieve high-frequency spectrum resolution. An important factor in selecting the technique was that such an algorithm should be implementable on a microprocessor-based system under harsh industrial conditions. Research results showed that the DFT ZOOM method meets these requirements. The frequency zoom has many advantages but requires some modification. It is implemented in high-performance analyzers, but a thorough and detailed description of the respective algorithm is lacking in technical articles and literature. This article mathematically and theoretically describes the modified frequency zoom algorithm in detail. The steps of the frequency zoom, from creating an analytical signal through frequency shifting and decimation to the frequency analysis of the signal, are realized. The algorithm allows for the analysis of a signal with high-frequency resolution in a limited frequency band. A significant modification of DFT ZOOM is that of using the Hilbert transform to create an analytic signal. This resolves the aliasing issue caused by the overlap between fundamental and sideband spectra. Results from processing deterministic and stochastic signals using the modified DFT ZOOM are presented. The presented experimental results contribute to a more detailed frequency analysis of the signal. As part of this scientific research, the issues of frequency zoom were thoroughly addressed, solving the partial problems of this algorithm, both in theory and in the context of signal theory.