Radio Frequency Signal Research Articles

Scientific and technical ways of reducing quantitative indicators of false alarms during the operation of an airboard radar station on the background of the underlying surface (earth)

The purpose of the research is development of scientific and technical ways to reduce the quantitative indicators of false alarms when operating an on-board radar station against the background of the underlying surface (earth) against the background of passive interference.Methods. When conducting scientific research, methods of probability theory, mathematical statistics, statistical radio engineering and computational mathematics were used. The study identified a number of methods and technical solutions based on them that make it possible to increase the efficiency of the functioning of airborne radar stations against the background of passive interference. The paper proposes a method for expanding the signal spectrum to 1 GHz by reducing the resolved volume of airborne radar stations. Physically, this is determined by the fact that with a decrease in the resolved volume, the size of the underlying surface area from which the signal is reflected decreases. In order to improve the quality of detection of objects against the background of the underlying surface, a method of using polarization modes is proposed.Results. In the course of the research: a technical solution was proposed based on the method of expanding the signal spectrum to 1 GHz by reducing the resolution volume of airborne radar stations designed to convert radio frequency signals into digital form, using a mixed signal receiver with direct digitization at radio frequency, such as the AD6688 ; a design of a low-baseline radar system has been developed, consisting of two positions, the antennas of which are located within the average width of the lobe of the backscattering diagram of the irradiated object; a feature of the antenna is the ability to receive and emit signals of the same linear polarization, but orthogonal to the polarization of the first position (including . horizontal and vertical polarization signals); an important relation was obtained for a lowbaseline polarization measuring system (MPIS) when the distance between two partial antennas can be much less than the distance to the measured object. Conclusion. The scientific article proposes methods and technical solutions based on these methods to reduce the quantitative indicators of false alarms when operating an on-board radar station against the background of the underlying surface (ground) against the background of passive interference. The proposed approach allows us to move on to the synthesis of a low-baseline polarization measuring system.

Proton bunch monitors for the clinical translation of prompt gamma-ray timing

Objective. Prompt gamma-ray timing is an emerging technology in the field of particle therapy treatment verification. This system measures the arrival times of gamma rays produced in the patient body and uses the cyclotron radio frequency signal as time reference for the beam micro-bunches. Its translation into clinical practice is currently hindered by observed instabilities in the phase relation between the cyclotron radio frequency and the measured arrival time of prompt gamma rays. To counteract this, two proton bunch monitors are presented, integrated into the prompt gamma-ray timing workflow and evaluated.Approach. The two monitors are (a) a diamond detector placed at the beam energy degrader, and (b) a cyclotron monitor signal measuring the phase difference between dee current and voltage. First, the two proton bunch monitors as well as their mutual correlation were characterized. Then, a prompt gamma-ray timing measurement was performed aiming to quantify the present magnitude of the phase instabilities and to evaluate the ability of the proton bunch monitors to correct for these instabilities.Main results. It was found that the two new monitors showed a very high correlation for intermediate proton energies after the first second of irradiation, and that they were able to reduce fluctuations in the detected phase of prompt gamma rays. Furthermore, the amplitude of the phase instabilities had intrinsically decreased from about 700 ps to below 100 ps due to cyclotron upgrades.Significance. The uncertainty of the prompt gamma-ray timing method for proton treatment verification was reduced. For routine clinical application, challenges remain in accounting for detector load effects, temperature drifts and throughput limitations.

A Radio Frequency Interference Screening Framework—From Quick-Look Detection Using Statistics-Assisted Network to Raw Echo Tracing

Synthetic aperture radar (SAR) is often affected by other high-power electromagnetic devices during ground observation, which causes unintentional radio frequency interference (RFI) with the acquired echo, bringing adverse effects into data processing and image interpretation. When faced with the task of screening massive SAR data, there is an urgent need for the global perception and detection of interference. The existing RFI detection method usually only uses a single type of data for detection, ignoring the information association between the data at all levels of the real SAR product, resulting in some computational redundancy. Meanwhile, current deep learning-based algorithms are often unable to locate the range of RFI coverage in the azimuth direction. Therefore, a novel RFI processing framework from quick-looks to single-look complex (SLC) data and then to raw echo is proposed. We take the data of Sentinel-1 terrain observation with progressive scan (TOPS) mode as an example. By combining the statistics-assisted network with the sliding-window algorithm and the error-tolerant training strategy, it is possible to accurately detect and locate RFI in the quick looks of an SLC product. Then, through the analysis of the TOPSAR imaging principle, the position of the RFI in the SLC image is preliminarily confirmed. The possible distribution of the RFI in the corresponding raw echo is further inferred, which is one of the first attempts to use spaceborne SAR data to ‌elucidate the RFI location mapping relationship between image data and raw echo. Compared with directly detecting all of the SLC data, the time for the proposed framework to determine the RFI distribution in the SLC data can be shortened by 53.526%. All the research in this paper is conducted on Sentinel-1 real data, which verify the feasibility and effectiveness of the proposed framework for radio frequency signals monitoring in advanced spaceborne SAR systems.

Two-Dimensional Differential Positioning with Global Navigation Satellite System Signal Frequency Division Relay Forwarding to Parallel Leaky Coaxial Cables in Tunnel

To address the issue of GNSS receivers being unable to function properly in tunnels due to the loss of Global Navigation Satellite System (GNSS) signals, this paper proposes a two-dimensional differential positioning system for tunnel environments based on dual leaky coaxial (LCX) cables with GNSS signal frequency relay forwarding. The system receives mixed GNSS signals from open environments and utilizes the frequency selection capabilities of the MAX2769E chip to separate and generate radio frequency signals at different frequencies corresponding to GPS, BDS, and GLONASS. These signals are then used to drive three ports of the LCX cables, which are laid in parallel within the tunnel. By leveraging the uniform radiation characteristics of the LCX cables, stable GNSS signal coverage is achieved throughout the tunnel. On the receiving end, the GNSS receiver achieves two-dimensional positioning by utilizing inter-satellite pseudorange differences and reference point error correction. The simulation results indicate that the dual T-shaped radiating LCX cables configuration offers excellent positioning accuracy and noise resistance, achieving meter-level positioning accuracy in tunnel environments.

60-GHz Millimeter-Wave over Visible Light Communications for Downlink Wireless Networks

Background and Objective: In this paper, we address potential solution for downlink wireless communications by integrating visible light communications (VLC) with the broadband radio frequency (RF) networks operating at 60 GHz-millimeter wave (mmWave) band. For this hybrid design, the outdoor 60 GHz-mmWave based RF link is utilized to ensure backhaul connectivity for VLC indoor system, while the VLC exploiting the lighting infrastructure that essentially used LEDs as optical source to provide low-cost and high-speed data access. Methods: The hybrid 60 GHz-mmWave/VLC system is analyzed by using 16-QAM OFDM signal, and its performance is investigated by evaluating the signal to noise ratio (SNR) and the received signal power distributions, for regular placement of LEDs and random location of receivers within the room. The impact of the transmitter-receiver parameters, and their orientations and directivities are also considered. Results: Numerical results show the efficiency of the proposed system, which can retransmit RF signals at 60 GHz-mmWave band using visible optical carriers in the indoor environment. Conclusion: The results suggest that the hybrid 60 GHz-mmWave/VLC system is able to provide reliable wireless data transmission, making it an attractive solution for downlink indoor communications.

Optimization algorithm of UAV‐assisted federated learning resources based on wireless energy harvesting

AbstractFederated learning (FL) enhances data privacy and security by enabling multiple terminals to collaboratively train a global model without transferring data to a central location. To tackle the challenges of limited terrestrial communication resources and device energy in FL, a UAV‐assisted federated learning and energy collection resource optimization algorithm is proposed. This algorithm harvests the working energy of FL terminals from radio frequency signals transmitted by the UAV via wireless energy collection. Considering energy causality and limited resources, we formulate a problem aimed at minimizing the completion time of FL training tasks. As this problem is NP‐hard, we initially employ a greedy algorithm to optimize the UAV's position, then decompose it into three sub‐problems: computing resources, power control, and bandwidth allocation. We derive and establish the optimization objective function for computing resources as convex, obtaining the expression for optimal computing resources. The Brent algorithm, based on golden section interpolation, iteratively solves the power distribution sub‐problem, while the Lagrange‐quasi‐Newton algorithm optimizes bandwidth allocation for each user. Simulation results demonstrate that the proposed algorithm effectively reduces training completion time while maintaining training quality.

Permutation Entropy for Signal Analysis

Shannon Entropy is the preeminent tool for measuring the level of uncertainty (and conversely, information content) in a random variable. In the field of communications, entropy can be used to express the information content of given signals (represented as time series) by considering random variables which sample from specified subsequences. In this paper, we will discuss how an entropy variant, the \textit{permutation entropy} can be used to study and classify radio frequency signals in a noisy environment. The permutation entropy is the entropy of the random variable which samples occurrences of permutation patterns from time series given a fixed window length, making it a function of the distribution of permutation patterns. Since the permutation entropy is a function of the relative order of data, it is (global) amplitude agnostic and thus allows for comparison between signals at different scales. This article is intended to describe a permutation patterns approach to a data driven problem in radio frequency communications research, and includes a primer on all non-permutation pattern specific background. An empirical analysis of the methods herein on radio frequency data is included. No prior knowledge of signals analysis is assumed, and permutation pattern specific notation will be included. This article serves as a self-contained introduction to the relationship between permutation patterns, entropy, and signals analysis for studying radio frequency signals and includes results on a classification task.

Design of a pHEMT RF mixer based on compact microstrip diplexer

Abstract This paper presents a new topology for a microwave active mixer using compact microstrip diplexer constituted from two dual-mode open loop resonators. The resonators are tuned to the radio frequency (RF) and local-oscillator (LO) frequencies, respectively, to effectively isolate the two input signals, while the diplexer output port is connected to the gate circuit of a commercial low cost GaAs pHEMT transistor. The drain circuit of the active device is connected to the load via an intermediate-frequency (IF)-modified Chebyshev low-pass filter to remove the unwanted RF and LO signals and reduce other spurious frequencies at the output of the mixer circuit. The circuit has been designed and constructed for an RF of 850 MHz, LO frequency of 1050 MHz, and an IF of 200 MHz. Experimental measurements show that the circuit provides a conversion gain of 18 dB at LO drive power of +2 dBm. It also operates satisfactorily over the RF range from 800 to 900 MHz with good image frequency rejection and stable operation.

Device structural engineering and modelling of emerging III-nitride/β-Ga2O3 nano-HEMT for high-power and THz electronics

Abstract III-nitrides, such as gallium nitride (GaN) and aluminium nitride (AlN), possess a wide bandgap, a high breakdown voltage, and a high thermal conductivity, making them an attractive choice for high frequency and high-power applications. A further benefit of III-nitride-based HEMTs is their high current density, low noise figure, and higher electron mobility, which enable efficient radio-frequency signal amplification. In this research work, the polarization induced graded buffer technique and improved lattice matched β-Ga2O3 substrate is employed to minimize the buffer-related issues in III-Nitride Nano-HEMTs (high electron mobility transistors), such as reduction in the buffer leakage current losses. The polarization-induced doping in buffer region can considerably reduce the buffer leakage current, enhance breakdown voltage and RF characteristics, and bend the conduction band upwardly convex, improving two-dimensional electron gas (2DEG) confinement. A detailed comparison between the graded buffer technique of the HEMT and the HEMT having normal buffer has been conducted. The results demonstrated that the suggested HEMT demonstrated better DC and RF characteristics up to the Tera (1012) hertz range of frequencies. The improved characteristics of the proposed HEMT allow it to be a feasible solution for emerging technologies and cutting-edge communication systems that require efficient signal processing at very high frequencies.

Hybrid FSO/RF and UWOC system for enabling terrestrial-underwater communication: Performance analysis

This work examines the performance of the terrestrial-underwater communication system utilizing hybrid free space optics (FSO)/radio-frequency (RF) and underwater wireless optical communication (UWOC) links. Here, the base station communicates with the underwater vehicle via a decode-and-forward (DF) based relay (buoy) in two phases. In the first phase, a hybrid FSO/RF link is used to transmit signal to the buoy, where the RF link acts as an alternative link to increase the reliability of the system, and in the next phase, the buoy forwards signal to the underwater vehicle through the UWOC link. To enhance the reliability of the RF link, the buoy is deployed with multiple antennas, and it exploits a maximal ratio combining scheme on the received RF signals. The analysis takes into consideration some primary variables that influence the system’s performance, such as atmospheric turbulence, attenuation, temperature gradient, air bubbles, water salinity variations, pointing errors, and detection techniques. Closed-form expressions for the outage probability, system throughput, and average channel capacity in terms of the Meijer-G and bivariate Fox-H functions are derived. Simulation results are presented to validate the analytical expressions and disclose valuable findings.

Influence of Opening Time Interval of Gate Signals on Suppression of Horizontally Polarized Signal of Infrared Pulsed Laser.

Since the beginning of the 21st century, infrared Nd:YVO4 pulsed lasers have been widely applied, especially in some actual industrial processes. In the working process of a laser-aided etching device, the "match-head" effect must be effectively controlled by suppressing the first giant pulse for a solid-state Q-switched laser. In the process of optimizing the infrared Nd:YVO4 pulsed laser by adjusting the slope parameters of the radio frequency (RF) modulation to suppress the first giant pulse, it has been found that an abnormal horizontally polarized emission with a very short time appears before the formal vertically polarized emission when the gate signal is artificially started. Actually, abnormal horizontally polarized emissions will bring some unexpected machining traces during the production process and even greater dangers. The experimental results show that with the increase in the slope duration of an RF signal, the existence time of abnormal output horizontally polarized light will be shortened, and the horizontal giant pulse and vertical giant pulse are well suppressed. When the slope duration is greater than 0.18 ms, both horizontal and vertical giant pulses will disappear. The horizontally polarized light can be thoroughly suppressed when the slope duration is greater than 13.7 ms. Compared with the method of adding a polarizer to eliminate abnormal output horizontally polarized light, this method does not add elements in the laser, ensuring that the laser volume is relatively small, and does not affect the quality of the normal output laser. The research conclusion is thought to be of great practical significance, especially for processing transparent materials.

Fiber-optic radio frequency transfer with enhanced frequency stability using fiber Brillouin amplifiers

The frequency stability of long-distance two-way fiber-optic radio frequency (RF) transfer is directly affected by the optical signal-to-noise ratio (OSNR) of optical amplifiers. In this paper, we have proposed a stimulated Brillouin scattering (SBS)-based optical amplification scheme with high OSNR for two-way fiber-optic RF frequency transfer over single mode fibers (SMF). At the remote and local site, the modulated carrier transferred from the opposite was amplified and then frequency upshifted by Brillouin frequency shift (BFS) for pump generation. This approach can avoid the use of additional pump lasers and phase-locked loops for wavelength stabilization of the pump. The pump was injected into the fiber link and counter-propagated with the signal to amplify the modulated carrier. A 2.2 GHz RF signal transfer with the proposed SBS-based optical amplification schemes was demonstrated over a 100 km fiber link. The experimental results illustrated that the OSNR was increased by 35 dB and 32 dB at the local site and the remote site, respectively, compared to the results obtained with erbium-doped fiber amplifiers (EDFA)-based optical amplification. Benefiting from improved OSNR, the frequency stability was increased by more than one order of magnitude below 1000 s averaging time, and the phase noise was reduced to the noise floor below 0.1 Hz offset frequency. The proposed optical signal amplification approach has a potential application for transferring atomic clocks over long-haul fiber links.

Extending radiowave frequency detection range with dressed states of solid-state spin ensembles

Quantum sensors using solid-state spin defects excel in the detection of radiofrequency (RF) fields, serving various applications in communication, ranging, and sensing. For this purpose, pulsed dynamical decoupling (PDD) protocols are typically applied, which enhance sensitivity to RF signals. However, these methods are limited to frequencies of a few megahertz, which poses a challenge for sensing higher frequencies. We introduce an alternative approach based on a continuous dynamical decoupling (CDD) scheme involving dressed states of nitrogen vacancy (NV) ensemble spins driven within a microwave resonator. We compare the CDD methods to established PDD protocols and demonstrate the detection of RF signals up to ~85 MHz, about ten times the current limit imposed by the PDD approach under identical conditions. Implementing the CDD method in a heterodyne/synchronized protocol combines the high-frequency detection with high spectral resolution. This advancement extends to various domains requiring detection in the high frequency (HF) and very high frequency (VHF) ranges of the RF spectrum, including spin sensor-based magnetic resonance spectroscopy at high magnetic fields.

Optimal Design of Smart Antenna Arrays for Beamforming, Direction Finding, and Null Placement Using the Soft Computing Method

ABSTRACTThe urge of modern communication system is to design and development of the smart antennas with adaptive radiation characteristics. The multifold capabilities of fourth‐dimensional antenna arrays can cater that much needed adaptiveness if properly designed. Compared to the conventional arrays, the fourth‐dimensional arrays have one added advantage as the ‘Time’ of all the switched‐on antenna elements can be managed to generate the required amplitude and phase tapering without even using attenuators and phase shifters. However, one inherent limitation of fourth‐dimensional control parameter is the generation of harmonics or sidebands. This article proposes various means of radiation pattern synthesis in fourth‐dimensional linear antenna arrays with pulse shifting, pulse splitting, and a combination of both. First of all, the pulse splitting and shifting techniques are combinedly proposed by reducing the sidelobe levels and sideband levels of the beamforming antenna arrays to enhance directivities and efficiencies. Then, this mathematical proposition of the direction finding fourth‐dimensional arrays is developed. Finally, broad nulls over a specific angle of arrival region are created for jamming and interference mitigation. For all these cases, the sidelobe level and the unwanted higher‐order sideband levels are suppressed to reduce the unwanted interferences and power losses. The optimal time schemes for all the synthesized patterns are generated by proposing a chaos‐based soft computing algorithm. The radiofrequency signals at each radiating array element are processed by the optimal time schemes proposed for specific applications. The outcomes are validated and compared with other state‐of‐the‐art works of this domain to prove the competency of the proposed work. The qualitative and quantitative comparisons presented for beamforming array is aimed for a good improvement over other reported works by targeting ultralow (less than −40 dB) sidelobe and sideband levels. For direction‐finding array, the proposed idea has also targeted ultralow sidelobes for the main as well as steered beam patterns. Furthermore, the null placement over a region has been aimed to cover more area for jamming and sidelobe reduction for interference mitigation. Overall, the optimal designs proposed for these advanced applications are beneficial for cutting‐edge communication systems.

Simultaneous generation of dual 16-QAM-modulated millimeter-wave signals enabled by precoding-based optical I/Q modulation and single photodetector detection

Integration of quadrature-amplitude-modulation (QAM) modulation and millimeter-wave (mm-wave) technology ensures a concise enhancement of transmission capacity and peak data rates in radio-over-fiber (RoF) systems. Nevertheless, with the continuous development of new-generation mobile applications, higher demands on access flexibility have also been formulated. We propose a novel, to the best of our knowledge, dual 16-QAM-modulated mm-wave signal generation scheme for the simultaneous generation and transmission of two independent 16-QAM signals with different carrier frequencies, enhancing the channel capacity, spectrum efficiency, and access flexibility of the RoF systems. In our proposed scheme, the generation of the optical dual 16-QAM-modulated mm-wave signals is implemented by a precoding-based optical in-phase/quadrature (I/Q) modulator operating at optical carrier suppression (OCS) mode, and their detection is implemented by a single photodetector (PD). At the transmitter side, two independent driving QAM vector radio-frequency (RF) signals with precoding, generated via digital signal process (DSP), are fed into two parallel Mach–Zehnder modulators (MZMs) of an I/Q modulator to implement OCS modulation. The I/Q modulator generates optical carriers carrying both information from different QAM signals simultaneously. After square-law detection in a single PD, we generate the desired dual 16-QAM-modulated mm-wave signals with photonic frequency-doubling and recover the original 16-QAM signals without information distortion. Based on our proposed scheme, we experimentally demonstrate the simultaneous generation and transmission of 2-Gbaud dual 16-QAM-modulated mm-wave signals with carrier frequencies of 26 GHz and 40 GHz, respectively. After transmission over 10-km single-mode fiber (SMF) link and 1.2-m wireless link, the dual 16-QAM signals can be successfully separated and demodulated by a common DSP. Bit-error ratios (BERs) of both recovered 16-QAM signals can reach the hard-decision forward-error-correction (HD-FEC) threshold of 3.8×10−3. Compared with the existing schemes, our scheme only requires one-half of the driving frequency to generate dual 16-QAM-modulated mm-wave signals with the same carrier frequency. The result indicates that our proposed scheme can lower bandwidth requirements for optoelectronics devices, along with implementing better spectral efficiency and receiver sensitivity, which is more applicable to the demands for increased system capacity and multi-frequency access flexibility in future systems.

Identifying Tampered Radio-Frequency Transmissions in LoRa Networks Using Machine Learning.

Long-range networks, renowned for their long-range, low-power communication capabilities, form the backbone of many Internet of Things systems, enabling efficient and reliable data transmission. However, detecting tampered frequency signals poses a considerable challenge due to the vulnerability of LoRa devices to radio-frequency interference and signal manipulation, which can undermine both data integrity and security. This paper presents an innovative method for identifying tampered radio frequency transmissions by employing five sophisticated anomaly detection algorithms-Local Outlier Factor, Isolation Forest, Variational Autoencoder, traditional Autoencoder, and Principal Component Analysis within the framework of a LoRa-based Internet of Things network structure. The novelty of this work lies in applying image-based tampered frequency techniques with these algorithms, offering a new perspective on securing LoRa transmissions. We generated a dataset of over 26,000 images derived from real-world experiments with both normal and manipulated frequency signals by splitting video recordings of LoRa transmissions into frames to thoroughly assess the performance of each algorithm. Our results demonstrate that Local Outlier Factor achieved the highest accuracy of 97.78%, followed by Variational Autoencoder, traditional Autoencoder and Principal Component Analysis at 97.27%, and Isolation Forest at 84.49%. These findings highlight the effectiveness of these methods in detecting tampered frequencies, underscoring their potential for enhancing the reliability and security of LoRa networks.

Wideband microwave frequency response measurement based on optical phase-locked loop

Frequency response measurement, or the forward transmission coefficient (S21) measurement for a two-port network, is the key function of a vector network analyzer (VNA). In this paper, a broadband and high dynamic range (DR) microwave S21 parameter measurement scheme based on an optical phase-locked loop (OPLL) is proposed. By heterodyning two phase-locked hybrid integrated ultra-narrow linewidth lasers, a microwave signal with low phase noise and spurious level is generated as the incident signal and reference signal, and the signal frequency can be easily manipulated over a wide range by tuning the master laser wavelength. In the receiver, the radio frequency (RF) signals are down-converted to intermediate frequency (IF) signals with the phase-locked lasers. By sampling and processing the IF signals the S21 parameter of the DUT can be acquired. A proof-of-concept experiment is performed, and with available photodetectors, phase modulators and phase-locked loops, a measurable range of 2 to 18 GHz is achieved. The demonstrated minimum frequency resolution of the OPLL-based RF signal synthesizer is 10 Hz. The system DR exceeds 68 dB at an equivalent resolution bandwidth of 1 kHz. The S21 parameters of a power divider and a bandpass filter are measured, and the results are well consistent with those of a commercial VNA. The DR and measurable range limit factors and possible extension methods are discussed. The proposed approach offers a high potential way to develop a wideband, high DR, and fully integrated VNA.

Design of Provably Secure and Lightweight Authentication Protocol for Unmanned Aerial Vehicle systems

Drones also called Unmanned Aerial Vehicles (UAVs) have become more prominent in several applications such as package delivery, real-time object detection, tracking, traffic monitoring, security surveillance systems, and many others. As a key member of IoT, the group of Radio Frequency IDentification (RFID) technologies is referred to as Automatic Identification and Data Capturing (AIDC). In particular, RFID technology is becoming a contactless and wireless technique used to automatically identify and track the tagged objects via radio frequency signals. It also has drawn a lot of attention among researchers, scientists, industries, and practitioners due to its broad range of real-world applications in various fields. However, RFID systems face two key concerns related to security and privacy, where an adversary performs eavesdropping, tampering, modification, and even interception of the secret information of the RFID tags, which may cause forgery and privacy problems. In contrast to security and privacy, RFID tags have very limited computational power capability. To deal with these issues, this paper puts forward an RFID-based Lightweight and Provably Secure Authentication Protocol (LPSAP) for Unmanned Aerial Vehicle Systems. The proposed protocol uses secure Physically Unclonable Functions (PUFs), Elliptic-Curve Cryptography (ECC), secure one-way hash, bitwise XOR, and concatenation operations. We use Ouafi and Phan’s formal security model for analyzing security and privacy features such as traceability and mutual authentication. The rigorous informal analysis is carried out which ensures that our proposed protocol achieves various security and privacy features as well as resists various known security attacks. The performance analysis demonstrates that our proposed protocol outperforms other existing protocols. In addition, Scyther and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool simulation results demonstrates that there is no security attack possible within bounds. Therefore, our proposed LPSAP protocol achieves an acceptable high level of security with the least computational, communication, and storage costs on passive RFID tags.

UAV-mounted IRS assisted wireless powered mobile edge computing systems: Joint beamforming design, resource allocation and position optimization

Intelligent reflecting surface (IRS) and unmanned aerial vehicle (UAV) have been recently used in wireless-powered mobile edge computing (MEC) systems to enhance the computation bits and energy harvesting performance. However, in the conventional IRS- and UAV-aided MEC systems, the IRS is installed at fixed locations on a building, which restricts the computation performance. UAV-mounted IRS (UAV-IRS), as a promising technology, combines the advantages of UAV and IRS. Hence, in this work, we study a UAV-IRS wireless-powered MEC system, where multiple UAV-IRSs are considered between Internet of Things (IoT) devices and the base station to improve the computation bits and energy harvesting. The multi-antenna base station first charges the IoT devices via radio frequency signals, and then IoT devices offload their computation tasks to the base station via UAV-IRSs. We formulate a computation bits maximization problem for all IoT devices by jointly determining detection beamforming at IoT devices, active energy beamforming at the base station, power allocation, time slot assignment, CPU frequency, the phase shifts design in the wireless energy transfer (WET) and task offloading, and UAV-IRSs positions. A block coordinate descent (BCD) algorithm by decomposing the introduced problem into four blocks is proposed, while the detection beamforming, active energy beamforming, transmit power, time slot assignment, CPU frequency, and the phase shifts design in the task offloading are derived in closed-form results. Also, the successive convex approximation and semidefinite relaxation (SDR) are adopted to obtain the UAV-IRS positions and the phase shifts in the WET, respectively. The simulation results verify the effectiveness of the presented BCD method compared with the different benchmark schemes.

Multi-channel photonic sampled ADC with hybrid deep-learning for distortion recovery

Analog-to-digital converter (ADC) is indispensable components in modern information systems, and photonic technologies have emerged as promising avenues for overcoming bottlenecks in ADC performance. This paper introduces a novel approach: a photonic sampled ADC integrated with a neural network that combines Convolutional Neural Networks (CNNs) and Transformers for data recovery. The proposed system utilizes a multi-wavelength optical sampling pulse train interleaved in the time domain through fiber dispersion. Sampled signals are quantified in parallel channels by electronic ADC (EADC). Through supervised training, the hybrid deep neural network extracts both local and global features of photonic system defects, enabling the recovery of distorted data. Experimental validation showcases the effectiveness of this architecture, achieving successful reconstruction of radio frequency (RF) signals at a sampling rate of 12 Giga-samples per second (Gs/s) with an effective number of bits (ENOB) of 7.13. The results underscore the potential of the proposed architecture in achieving high conversion accuracy in multi-channel photonic sampled ADCs.