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International audience; The structural and radio frequency (RF) design and optimization of a large deployable faceted reflectarray (RA) generating double polarization contour beam are presented in this work. The issue addressed is the thermoelastic stability of large RAs and the impact of the thermoelastic deformation (TED) under transverse thermal gradient on the RA performances. Finite element TED analysis is conducted on a deployable RA with self-standing structures, demonstrating the detrimental effects of the in-orbit TED impact on the RA performances, estimated to be above 3 dB losses. To this extent, a novel structural solution is proposed, based on the use of reliable mechanical support capable to mitigate the TED. The mechanical design reorientation is contingent on the RF design reformulation. The proposed novel mechanical and RF co-design concept and methodology allows the conception of a low-profile, thermo-structurally stable RA with compliant radiation patterns and high cross-polarization discrimination in the worst case thermal load. This methodology is based on a direct optimization of nine-panel faceted RA composed of advanced high-order Phoenix cells directly optimized to fulfill the contoured beam requirements and by respecting the local periodicity requirements of the layout.

This article analyzes the performance of light fidelity (LiFi)-based device-to-device (D2D) communication in industrial Internet-of-Things (IIoT). We present a comprehensive analysis of mobility management of D2D communication in industrial LiFi networks. Using the semiangle at half illuminance of the AP and D2D transmitting IIoT, a coverage model for the D2D communication range is derived. By adopting stochastic geometry, closed-form expressions for mode selection rate and residence time are derived as functions of the AP density, IIoT density, and velocity. The results have shown that high velocity and denser deployment cause a decrease in the average D2D residence time and an increase in the average D2D transition rate or vice versa. The proposed analytical models are then verified with Monte Carlo simulation results. The results provide system-level design insights.

An overview of the recent operations and the main results of cesium injection in the Source for the Production of Ions of Deuterium Extracted from Rf plasma (SPIDER) negative ion source are described in this contribution. In experiments without cesium injection, all SPIDER plants were tested to verify the basic expectations on the operational parameters (e.g., electron cooling effectiveness of magnetic filter field) and to determine its operational region. For beam properties, it was shown that the current density varies across the beam in the vertical direction. In preliminary cesium experiments, the expected increase of negative ion current and simultaneous decrease of co-extracted electrons were found, along with the influence of the control parameters (polarization of the plasma electrodes, magnetic filter field) on the SPIDER beam uniformity in the horizontal and vertical directions. It was shown that non-Gaussian tails can be identified in the angular distribution on the plane perpendicular to the beam propagation direction. Stray particles, nonhomogeneous beam and large divergence might result in unexpected heat and particle loads over ITER neutral beam injector (NBI) accelerator grids; it is the goal of SPIDER to assess and possibly to identify suitable methods for controlling these beam features. A major shutdown, planned for late 2021, to solve the issues identified during the operation and to carry out scheduled modifications, is outlined. Such improvements are expected to allow SPIDER to pursue the ITER requirements in terms of negative ion current, electron-to-ion ratio, and beam duration.

The aim of the study involves the design of a novel annular seven tooth antenna and comparing its gain, return loss with a circular patch. Totally 38 samples are considered for the analysis which is obtained using the G power tool by fixing the pretrained power and the error rate as 0.811 and 0.051 respectively. The total 38 samples are grouped into two namely novel annular seven tooth antenna with 19 samples and circular patch with 19 samples. The performance of the antennas is analyzed using return loss and gain. The design of novel annular seven tooth antenna produced a high gain of 7.7 dB which is more significant than the gain of circular patch antennas (CPA) for navigation application. It is found that the gain, return loss of the designed novel annular seven tooth antenna is 7.7 dB, -18.1 dB. The gain and return loss of the novel annular seven tooth antenna is improved and it is compared with circular patch. It is more significant as it has a p value less than 0.05.

In fingerprint-based indoor localization, fusing radio frequency (RF) and geomagnetic signals has been shown to achieve promising results. To efficiently collect fingerprints, implicit crowdsourcing can be used, where signals sampled by pedestrians are automatically labeled with their locations on a map. Previous work on crowdsourced fingerprinting is often based on a single signal, which is susceptible to signal bias and labeling error. We study, for the first time, implicit multimodal crowdsourcing for joint RF and geomagnetic fingerprinting. The scheme, termed UbiFin, exploits the spatial correlation among RF, geomagnetic, and motion signals to mitigate the impact of sensor noise, leading to highly accurate and robust fingerprinting without the need for any explicit manual intervention. Using clustering and dynamic programming, UbiFin correlates spatially different signals and filters effectively mislabeled signals. We conduct extensive experiments on our campus and a large multi-story shopping mall. Efficient and simple to implement, UbiFin outperforms other state-of-the-art crowdsourcing schemes to construct RF and geomagnetic fingerprints in terms of accuracy and robustness (cutting fingerprint error by 40% in general).

With the recent advancement in baseband integrated circuits and radio frequency (RF) technology, there is a strong demand to minimize the size of array-based microwave systems. However, array aperture miniaturization often leads to strong mutual coupling in the arrays. To date, mitigating and/or compensating the mutual coupling (nonlinear) effect remains a technical challenge. For instance, realizing microwave orientations in the presence of strong mutual coupling is a challenge. In this paper, we propose a unified electromagnetic machine learning (EMML) technique for overcoming this challenge. Antenna current’s Green function (ACGF) is employed for characterization of the EM response of elements in form of digital signal processing (DSP) module with the inclusion of mutual coupling effect among the elements. An EMML framework is then formulated and combined with the DSP module based on ACGF, to consequently come up with a nonlinear mutual coupling mitigation framework that provides better decoupling capability than the previous linear techniques. EMML is verified by application to a multiple signal classification (MUSIC)-based direction-of-arrival estimation scenario, and compared with the conventional methods. The results obtained show the validity, effectiveness of the EMML method. This method can be further used in coupled array-based beam forming, steering, and nulling applications.

This research paper is proposed to cater the design requirements of phased array antenna with side lobes pertaining for radio frequency (RF) wireless domain applications. As wireless communications have become an inevitable part of our lives as-on- date, designing smaller and lighter mobile terminals is one of the critical requirements for the development of wireless systems. A single antenna gives only a small directivity, whereas in terms of increased directivity an antenna array can be a possible candidate. Considerable optimization methods for synthesizing array pattern have started to emerge thereby achieving a pattern of desired one related to the application we work in. The major factor which drives the far field structure in phased array antenna with an allowable side lobe level is the power distribution among the array of elements. This paper presents a novel method for side lobe level (SLL) suppression in amplitude tapered planar array structure and it is compared with different distribution methods relating to array coefficients with prime focus on Taylor, Chebyshev and Gaussian distributions. CST Microwave Studio software is used to simulate various distributions and it is compared with characteristics such as gain, directivity, beam width and side lobe level suppression.

Battery power has been a popular choice of delivering DC power to many portable RF systems including wireless sensor nodes/internet of Everything (IoE). An autonomously powered RF system of the orders of 100’s of µwatts is becoming increasingly popular in recent times because of integrated solutions in energy harvesting. The minimum sensitivity of an RF energy harvester and the targeted deliverable output voltage for a specific load resistance are dictated by threshold voltage of transistors used and reverse leakage of such transistors. A detailed look into the architectures of rectifiers can help tackle design problems in the RF-DC conversion process. So in this work we focused on the design of integrated RF energy harvesting by studying four important architectures of RF-DC converters. To achieve a fair comparison between these architectures, a matching network operating at 0.8 MHz is designed and applied for simulation. All of these converters are tested in LT-SPICE XVII using the same designed matching network and the rectifiers are implemented in 180 nm CMOS technology.

In this paper a recess gate AlGaN/GaN HEMT on beta gallium oxide (BGO) is designed and analysed using Silvaco ATLAS TCAD software. The DC and RF performance of the device is compared with a schottky gate AlGaN/GaN HEMT on BGO substrate. For optimizing the gate recess depth, three variations with recess depths 6 nm, 12 nm and 20 nm is also simulated. A highest transconductance of 0.4 mS/ µm is observed for recess gate AlGaN/GaN HEMT on BGO substrate with a recess gate depth of 20 nm with a decrease in current density. The radio frequency performance is also highest for the recess gate AlGaN/GaN HEMT with recess gate depth of 20 nm. The device exhibited a maximum oscillation frequency of 2.6 THZ which is highest till reported.

Publisher Copyright: Author This paper focuses on the design aspects of the key components for a scalable phased-array system over the 200 GHz frequency range. A high-gain phase shifter chain for 220 to 240 GHz frequency range and a high-gain power amplifier (PA) with a high output power are designed in a 0.13-μm SiGe BiCMOS technology. The phase shifter chain includes a low-noise amplifier (LNA), a vector modulator phase shifter (PS), and a gain-enhancing amplifier. The LNA is a five-stage cascode design. The vector modulator core is realized by two variable gain amplifiers based on the Gilbert cell architecture. A four-stage cascode design is used for the gain-enhancing amplifier. The phase shifter chain shows a measured gain of 18 dB at 230 GHz with a 360° phase tuning range and more than 10 dB of gain control. The chip achieves a minimum measured noise figure of 11.5 dB at 230 GHz and shows a wideband noise characteristic. The complete phase shifter chain chip consumes a dc power of 153 mW and occupies a 1.41 mm2 area.A high-power PA that is critical for a large phased-array system is designed. This paper presents a unique 4-way power combining technique utilizing a differential quadrature coupler. The realized balanced PA occupies an area of 0.67 mm2 and shows a measured peak gain of 21 dB at 244 GHz. The PA consumes 819 mW of dc power and delivers a maximum saturated output power (Psat) of 7.1 dBm at 244 GHz and more than 4.3 dBm of Psat from 230 to 255 GHz.

Over a last few decennary free space optical communication (FSO) have become more interesting alternative to the radio frequency for communication. The FSO is emanating technic that have been found the applications in different place of shorter & longer distance communication. The any technology, of FSO has been worked that much good in the several applications rather than other. In this paper we will examine FSO from different angles. The analyses this paper accompany of the technology has shown that FSO technologies inherent strengths and it lack the use of in ground cables which make it much expeditious & cheaper to installing, and the facts that will operates in the unlicensed spectrum, it will be removed & installed elsewhere and it has relatively high bandwidth. Specifically, this paper found that because FSO uses air as a communication medium, its performance & reliability are restricted by fog, rain, snow and dust. Maximum range of FSO may be in kilometers only. The applications that FSO technology seems most suited to is clear this pap rather and short distance connection establishment, like interrelation to broadband networks backbone & backbone links bet this papered building in the metropolitan area networks (MAN) or the campus area networks (CAN).

Radio Frequency (RF) based heating application is used in multiple industries like drying cross-laminated woods, food and packaging, melting silicon etc. These industrial RF heating plants operate at frequencies of 6.78 MHz, 13.56 MHz, or 27.12 MHz (ISM band). Historically, the high frequency requirement has forced the industry to rely on vacuum tube based RF generator, which are only 60% efficient. Modern semiconductors like wide bandgap (WBG) devices have achieved the high frequency operation that is required to replace the inefficient vacuum tubes. However, a comprehensive study of load network for an industrial RF heating plant has not been undertaken such that an existing plant can be retrofitted with semiconductor based turn-key solution. In this paper the authors present design equations for an industrial RF dielectric heating load structure and suggest necessary modifications required to replace vacuum tube RF generator with voltage source converter (VSC). A new figure of merit (FOM) is defined that impacts the load structure efficiency. Finally, a small-scale prototype load is manufactured as a case study. The prototype demonstrated an output power of 750 W at 6.76 MHz with an overall efficiency of 90% from DC input to RF load which can not be achieved with a vacuum tube technology.

Stealth aircraft use Stealth Technology in order to evade recognition by utilizing mix of highlights with the goal that Aircraft can invade with RADAR and furthermore decrease the deceivability in “radio frequency (RF) range”, sound and infrared visual. During the most recent decades, stealth technology has demonstrated to be one of the best methodologies to the extent the undertaking to escape radar systems is concerned. Stealth intends to evade the recognition or attempt to cover up, for planes, avoiding radar implied stealth. The idea utilized in the stealth innovation isn’t so difficult. It utilizes the guideline to retain and mirror the radar waves. Airplane redirects the radar waves in different ways and limits the radar waves which return back to radar. Another marvel which permits the air ship maintain completely the incoming radar wavelengths to inhabit the electromagnetic reincorporated energy in various way. The structure and material used to manufacture air ship choose the degree of stealth accomplish via air ship. The thought for the radar radio wire to release Radio energy that is then returned through any item that occurs to recognize. The time taken for the reflection to come is measure by the radar radio wire and it can tell how far off an object is.

RF verilerinin doğru olarak değerlendirilmesi, göndericinin açık olduğu zamanın tam olarak algılanmasından veya bilinmesinden başlar, bu zorluk iki önemli konuyu içerir; kaçınılmaz arka plan gürültüsü gibi gereksiz bilgileri işlemeyi önlemek ki bu işlemi hızlandır ve diğer konu, o gönderenin tam davranışını incelemektir. Bu çalışmada, Akaike Bilgi Kriterini (AIC) kullanılarak Bluetooth sinyalinin geçici olarak başlangıcını otomatik olarak yakalamak için bir yöntem geliştirilmiştir. Önerilen yöntem, en yaygın cep telefonu markalarından farklı yollarla alınan gerçek veriler üzerinde sinyal-gürültü oranının değişimi ile incelenmiştir. AIC algoritması, yüksek genlikli rastgele bir gürültüden etkilenmediğini göstermiştir., The precise interpreting of RF data starts from retrieving or knowing the exact time instant at which moment the sender is turned on, this challenge implies two important issues; prevent manipulating redundant information such as unavoidable background noise which speed up the processing and the other issue is to study the exact behavior of that sender. A method has been developed to automatically catch the onset in transient of Bluetooth signal using of the Akaike Information Criterion (AIC). Present method has been examined on real world data taken from the most common cellular phones brands by different ways with variation of signal to noise ratio. The AIC algorithm shows robustness in the existence of relatively a high-amplitude random noise.

Deep learning methods have been very successful at radio frequency fingerprinting tasks, predicting the identity of transmitting devices with high accuracy. We study radio frequency fingerprinting deployments at resource-constrained edge devices. We use structured pruning to jointly train and sparsify neural networks tailored to edge hardware implementations. We compress convolutional layers by a 27.2x factor while incurring a negligible prediction accuracy decrease (less than 1%). We demonstrate the efficacy of our approach over multiple edge hardware platforms, including a Samsung Gallaxy S10 phone and a Xilinx-ZCU104 FPGA. Our method yields significant inference speedups, 11.5x on the FPGA and 3x on the smartphone, as well as high efficiency: the FPGA processing time is 17x smaller than in a V100 GPU. To the best of our knowledge, we are the first to explore the possibility of compressing networks for radio frequency fingerprinting; as such, our experiments can be seen as a means of characterizing the informational capacity associated with this specific learning task.

This paper presents a digitally programmable bi-directional 7-bit passive phase shifter in a 65 nm CMOS technology. The core of this passive vector-synthesized phase shifter is a hybrid quadrature generator (HQG), an interstage matching network, and a passive vector modulator (PVM). This work proposes a high coupling-factor-based quadrature generator design methodology and demonstrates it with a compact vertical transformer. The interstage matching network between HQG and PVM is proposed to release the bandwidth bottleneck and achieve a 34% fractional frequency bandwidth. Two 6-bit X-type attenuators in the I and Q path form a high-resolution 12-bit controlling word. In 32-40 GHz, this 7-bit 360 ∘ phase shifter achieves a measured 2.8 ∘ step with 0.45-1.6 ∘ RMS phase error and 0.2-0.36 dB RMS magnitude error. With the broadband technique, its 3-dB bandwidth reaches 30.2-42.7 GHz with a 2.8 ∘ RMS phase error. Its in-band 1-dB compression point is 10.2 dBm. With the proposed compact HQG and PVM, this mm-wave passive phase shifter only occupies 220×630 μ m 2 and has no power consumption.

The cell-type continuous electromagnetic radiation system is a demonstration device capable of generating high-power millimeter electromagnetic waves of a specific wavelength and observing their effects on living organisms. It irradiates a biological sample placed in a 30 × 30 × 50 cm3 cell with electromagnetic waves in the 3.15-mm-wavelength region (with an output of ≥1 W) and analyzes the temperature change of the sample. A vacuum electronic device-based coupled-cavity backward-wave oscillator converts the electron energy of the electron beam into radiofrequency (RF) energy and radiates it to the target through an antenna, increasing the temperature through the absorption of RF energy in the skin. The system causes pain and ultimately reduces combat power. A cell-type continuous electromagnetic radiation system consisting of four parts—an electromagnetic-wave generator, a high-voltage power supply, a test cell, and a system controller—generates an RF signal of ≥1 W in a continuous waveform at a 95-GHz center frequency, as well as a chemical solution with a dielectric constant similar to that of the skin of a living organism. An increase of 5 °C lasting approximately 10 s was confirmed through an experiment.

This paper presents novel radiation hardening design techniques to substantially reduce the single event effects (SEE) on high-frequency receivers subject to various radiations when operating in space. A W-band (75-110 GHz) receiver front-end implemented in Global Foundry’s 90 nm SiGe BiCMOS technology is used for studying SEE and investigating the effectiveness of the proposed techniques. Specifically, the mixer is modified to allow for different modes of operation, in addition to introducing matching considerations between the mixer’s gain and switching stages. The receiver includes integrated high frequency signal sources to provide the input radio frequency (RF) and local oscillator (LO) signals for full operation of the proposed millimeter-wave (mmW) receiver. Measurements are taken while the receiver is in normal operation (RF and LO are applied.) The design techniques are carefully analyzed via extensive simulations using equivalent transient current pulses obtained from calibrated Technology Computer-Aided Design (TCAD) simulations. A two-photon-absorption (TPA) pulsed laser experiment is used to induce transient currents in the silicon–germanium heterojunction bipolar transistor (SiGe HBT) circuit. Various devices within the mixer are hit from the back side through a hole in the designed printed circuit board (PCB.) The propagated transients are then captured using a high-speed oscilloscope at the output of the receiver. The measurement results, supported by simulations and analysis, validate the robustness of the proposed radiation hardened receiver to SEE.

In the mm-wave frequency band, the rectifier’s sensitivity is the bottleneck of a wireless-powered IoT transponder’s distance. At a meter’s distance, the received power is weak, and transistors in a front end of a wireless power receiver operate in the weak inversion region. This article presents a mathematical analysis of the mm-wave multi-stage rectifier in the low-power region. A design methodology of a 57–64-GHz fully integrated eight-stage rectifier with a bulk-drain connection in 40-nm CMOS technology is presented. Parasitic effects on a multi-stage rectifier are analyzed. Based on the analysis, an intrinsic threshold voltage modulation is applied to improve the sensitivity. A tree-type power splitter is also proposed for the RF power signal’s phase balance. With this method, the RF signal arrives at each stage with an equal phase, and its suppression at the output is improved by 16 dB. This mm-wave rectifier achieves − 7.1-dBm input sensitivity at 57 GHz with 1-V dc output voltage. The overall sensitivity from 57 to 64 GHz is better than − 4.5 dBm. Compared to other mm-wave silicon-based rectifier state of the arts, the proposed mm-wave rectifier achieves better sensitivity while maintaining a compact size.

Visible light communication (VLC) has recently emerged as an affordable and scalable technology supporting very high data rates for short range vehicle-to-vehicle (V2V) communication. In this work, we advocate the use of vehicular-VLC (V-VLC) for basic safety messages (BSMs) dissemination in lieu of conventional vehicular radio frequency (V-RF) communication in road intersection applications, where the reception performance is affected by interference from the concurrent transmissions of other vehicles. We make use of stochastic geometry to characterize the interference from the same lane as well as the perpendicular lane for various network configurations, i.e., standalone V-VLC, stand-alone V-RF and hybrid V-VLC/V-RF network. Specifically, by modelling the interfering vehicles' locations as a spatial Poisson point process (PPP), we are able to capture a static two-dimensional road geometry as well as the impact of interference due to vehicles clustering in the vicinity of road intersection in terms of outage probability and throughput. In addition to above, the performance of spatial ALOHA and carrier sense multiple access with collision avoidance medium access control (CSMA/CA MAC) protocol for standalone V-VLC, standalone V-RF and hybrid V-VLC/V-RF network configuration for relaying BSMs at road intersection is also compared. The performance metrics such as delay outage rate (DOR) and information outage rate (IOR) are utilized to investigate the impact of latency associated with various network configurations. Our numerical results reveal that our proposed hybrid V-VLC/V-RF leads to significant improvement in terms of outage performance, throughput and latency as compared to stand-alone V-VLC or stand-alone V-RF network.

For distributed sensor systems using neural networks, each sub-network has a different electromagnetic environment, and these recognition accuracy is also different. In this paper, we propose a distributed sensor system using incremental learning to solve the problem of radio frequency fingerprint identification. First, the intelligent representation of the received signal is linearly fused into a four-channel image. Then, convolutional neural network is trained by using the existing data to obtain the preliminary model of the network, and decision fusion is used to solve the problem in the distributed system. Finally, using new data, instead of retraining the model, we employ incremental learning by fine-tuning the preliminary model. The proposed method can significantly reduce the training time and is adaptive to streaming data. Extensive experiments show that the proposed method is computationally efficient, and also has satisfactory recognition accuracy, especially at low signal-to-noise ratio (SNR) regime.\ud

Emergency exit lights in public buildings are necessary for safety and evacuation. International safety standards require such lighting in many public places, like airports, schools, malls, hospitals, and other spaces, to prevent human casualties in emergencies. Emergency exit lights have become an essential part of casualty reduction projects. They can pose several application problems, including fire safety concerns. The issue of providing a safe way and operating emergency exit lights along one side of a long path arises during an emergency. Many studies in this field consider the case in which emergency exit lights’ battery or main power fails. Power failures in dangerous situations such as fires or terrorist attacks make it difficult for people to escape. The lighting in open areas and stairwells during an emergency should be at least 2 lux. This work proposes an innovative technique for wirelessly powering emergency lights using microwave energy. Specifically, the study designed and fabricated a new wirelessly powered emergency lighting prototype. This prototype’s wireless power transfer (WPT) base comprises an RF/DC converter circuit and an RF microwave transmitter station. The device can harvest RF microwave energy to energize the emergency light. This research aimed to develop a compact device that captures maximum RF strength to power emergency lights. As a prototype, the proposed device was designed to provide sufficient microwave energy to power an emergency light at 3 W over a 62 m distance.

Context-sensitive two-point layer 5 pyramidal cells (L5PCs) were discovered as long ago as 1999. However, the potential of this discovery to provide useful neural computation has yet to be demonstrated. Here we show for the first time how a transformative L5PCs-driven deep neural network (DNN), termed the multisensory cooperative computing (MCC) architecture, can effectively process large amounts of heterogeneous real-world audio-visual (AV) data, using far less energy compared to best available 'point' neuron-driven DNNs. A novel highly-distributed parallel implementation on a Xilinx UltraScale+ MPSoC device estimates energy savings up to 245759 $ \times $ 50000 $\mu$J (i.e., 62% less than the baseline model in a semi-supervised learning setup) where a single synapse consumes $8e^{-5}\mu$J. In a supervised learning setup, the energy-saving can potentially reach up to 1250x less (per feedforward transmission) than the baseline model. The significantly reduced neural activity in MCC leads to inherently fast learning and resilience against sudden neural damage. This remarkable performance in pilot experiments demonstrates the embodied neuromorphic intelligence of our proposed cooperative L5PC that receives input from diverse neighbouring neurons as context to amplify the transmission of most salient and relevant information for onward transmission, from overwhelmingly large multimodal information utilised at the early stages of on-chip training. Our proposed approach opens new cross-disciplinary avenues for future on-chip DNN training implementations and posits a radical shift in current neuromorphic computing paradigms.

We have evaluated CTR performance of four different mixed-signal front-end electronic readout configurations with the goal to achieve 100 picoseconds (ps) coincidence time resolution (CTR). The proposed TOF-PET detector elements are based on two 3 × 3 × 10 mm(3) “fast LGSO” crystal segments, side-coupled to linear arrays of 3 × 3 mm(2) silicon photomultipliers (SiPMs), to form a total crystal length of 20 mm. We studied multiple configurations and components for the front-end readout: 1) high speed radio frequency (RF) amplifiers; 2) an ASIC-based discriminator; 3) combination of RF amplifier, balun transformer, and discriminator ASIC; and 4) combination of balun transformer, and discriminator ASIC. Using two 3 × 3 × 10 mm(3) fast LGSO crystals side coupled to a linear array of three SiPMs, coincidence data were experimentally acquired for each readout configuration in combination with a low jitter field programmable gate array (FPGA)-based time to digital converter (TDC). After evaluating timing performance of the three readout schemes, the best CTR value of 99.4 ± 1.9 ps FWHM was achieved for configuration (3), which is more than 20 ps better than the results achieved using configurations (1) and (2).

This paper presents a high-performance radio frequency (RF) power amplifier (PA) module for which an optimum chip-level packaging structure is proposed to reduce the operating temperature of the RF PA monolithic microwave integrated circuit (MMIC). Because the output power (Pout) and the efficiency of a RF PA module are strongly affected by the thermal characteristics of the PA MMIC, various types of heat spreader materials and thermal interface materials have been examined to implement the PA chip-level packaging structure, and the optimum combination is proposed for a performance enhancement of the PA module in this paper. In addition, the optimum form-factor of the heat spreader was suggested based on a thermal simulation. To verify the proposed PA chip-level packaging structure, a 10 W 618 GHz RF PA MMIC using a commercial 0.25-m gallium nitride high electron mobility transistor process was designed and implemented for radar applications. The operating temperature of the PA MMIC on the proposed chip-level packaging structure shows a dramatic reduction of 24.8 C, and accordingly, the average Pout and average power-added efficiency are enhanced by up to 9.2% and 2.8%, respectively, when compared with a PA module using the conventional chip-level packaging structure.

In-band full-duplex (IBFD) technology has the potential to not only double the communication throughput but also enable additional capabilities. The fusion of radar and communication subsystems is an excellent example of how IBFD facilitates integration of radar functionality into a communication system. Developing and analysis of a joint IBFD radar-communication (RadCom) system is at the core of this article. This system derives the range-Doppler image from the state of an adaptive filter, which already exists in a typical IBFD transceiver. Our approach is waveform-independent and reuses the radio frequency (RF) front-end while it requires little additional digital logic. The proposed system is prototyped to assess the modem-radar coexistence in a real-world IBFD communication link budget. Employing the prototyped system, we quantify the additional required logic resources and investigate whether such a RadCom approach dictates a tradeoff between the two intended functionalities. The experimental results show that the proposed solution enables a communication system to detect targets within 20 m while maintaining an IBFD link with another communication node, info:eu-repo/semantics/published

Miniature radar has demonstrated its great potential in smart homes to understand the wellness of the residents and provide ubiquitous interactions. While it has many promising applications, it also results in congested RF (radio frequency) environments as there is an unprecedented amount of traffic in a smart home. To ease the strain on the limited spectrum, we ask the question that, can we reuse the sensing signals for data communication With such a capability, we can improve the spectrum utilization by sharing the spectrum between sensing and communication systems. However, radar signals are customized for the sensing purpose and are incompatible with legacy communication standards. To address this challenge, we have an observation that, non-linearity effect in RF circuits can convert wideband radar signals into a LoRa signal. Based on this observation, in this paper, we present LoRadar, which enables an FMCW (Frequency-Modulated Continuous Wave) radar to carry LoRa signals in sensing waves. We present both the downlink and uplink design, enabling a LoRadar device to communicate with LoRa nodes in a bi-directional way. We implement LoRadar and evaluation results show that LoRadar can achieve home-level coverage with 3:4kbps data rate while it preserves the sensing resolution of the radar.

This paper presents a fully RF-powered wireless transceiver integrating an efficient RF energy harvester (RFEH), a wake-up receiver (WuRx), and a wake-up transmitter (WuTx) on a single CMOS chip. The WuRx is designed to operate with supply voltages as low as 300 mV allowing to be entirely powered up by the RF energy at power levels as low as -26 dBm. The capability of the WuRx to operate without using a power management unit (PMU) enhances the sensitivity and overall conversion efficiency of RFEH system. By utilizing an ultra-low-power ultra-low-voltage envelope detector to obtain the required signal levels, using passive amplification instead of an active low-noise amplifier, and eliminating the voltage regulator removing its power overhead, the transceiver’s input sensitivity has been improved at least by a factor 2 (3 dB) compared to the other previously reported RF-powered transceivers.. The proposed transmitter consists of a fast start-up oscillator and an efficient class E power amplifier, which can be externally tuned for different output powers. Fabricated in TSMC’s 130 nm CMOS process, the measurement results show that the proposed WuRx consuming only 5.7 nW works with input powers as low as -26 dBm, and the proposed transmitter can work with input powers as low as -23 dBm. The WuTx outputs -11 dBm with 51% efficiency at 2.45 GHz using high-Q off-chip components.

Partial discharge (PD) monitoring of electrical substations could provide early warning of insulation failures. Among the various technologies, Radio Frequency (RF) based PD monitoring system could be a promising solution. The RF-based monitoring system detects PD sources in the substation and can also localise the PD sources. The time difference of arrival (TDOA) based PD localisation system primarily require arrival time of the impulsive RF signal. Though many localisation algorithms have been proposed in the recent past to overcome the TDOA estimation errors, less attention has been given to the accurate estimation of RF PD signal arrival time. This paper presents the AT's automatic labelling in the RF PD signal using Bi-Long Short-Term Memory (Bi-LSTM) network applied on the continuous wavelet transformed (CWT) signal. Further, it also shows PD signal augmentation to overcome the problem of limited representative training data set. The behaviour of the radiated RF signals is influenced by many factors and has almost stochastic characteristics. The proposed system has been validated with laboratory-based experimental signals and the data set obtained from different electrical substations. The results show that the improved performance is obtained from the combination of a multilayer Bi-LSTM model and an augmented training set.

In the present thesis, a MatLab simulator originally designed to calculate connections between satellites and ground stations has been expanded to include airplane routes and their respective connections. The goal is to provide an accurate and efficient ground-air-space simulation tool for monitoring air connections, which will allow for improved air traffic efficiency and safety. Air transportation is one of the most widely used modes of transportation worldwide, and its efficiency and safety are of vital importance. Using satellites for monitoring airplanes is of utmost importance due to several reasons, including the ability to provide continuous global coverage, real-time data on aircraft parameters, improved air traffic management, and enhanced safety. The designed tool allows for the simulation of multiple aeroplanes and satellites, and automatically calculates the connections between aircraft and satellites and between satellites and ground stations. In addition, a module has been added to simulate and calculate connections between aircraft and ground stations. This project is part of the PLATHON project of the Polytechnic University of Catalonia, which aims to develop a simulator to study the communications between constellations of cubes and the Earth. The simulator developed in this thesis will be used as a basis for the study of the communication between cubes, airplanes and ground in the PLATHON project. Testing and validation of the simulator have been conducted, and it has been demonstrated to be an effective tool for simulating and monitoring air connections. In conclusion, this project represents a significant advance within the PLATHON project in the monitoring of air connections, and has proven to be a very useful and necessary tool for monitoring aircraft routes across the globe.

Nowadays, smart devices have become a major part of human life, and this need has led to an increase in the demand for these devices, prompting major telecommunications companies to compete with each other to acquire the bulk of this market. This competition led to a significant increase in the number of mobile towers, to expand the coverage area. Each communication tower has transmitters and receivers to connect subscribers within the mobile network and other networks. The receivers and transmitters of each mobile tower operate on radio frequency waves. These waves can cause harm to humans if the body tissues absorb the radiation resulting from these waves. Headache, discomfort, and some other diseases are among the effects resulting from the spatial proximity to the mobile towers. In this paper, a model based on geographic information systems (GIS) software is proposed for the purpose of discovering the area of exposure to radio frequency radiation. This model can assists mitigate the opportunities of exposure to these radiations, thus reducing its danger. Real data of the levels of electromagnetic pollution resulting from mobile towers were analyzed during this study and compared with international safety standards.

We propose and demonstrate a converged optical fronthaul network for RF and data services with scalable silicon photonic switching. A 1.5dB power penalty at a 10-9 BER and over 40dB RF dynamic range are demonstrated.

This paper demonstrates a novel digital radio distribution system able to transmit not only over optical fibres and coaxial cables but also over twisted pair cables. The digitised RF signal is compressed for maximum transmission efficiency in a way that allows for integral self-learning algorithms to be introduced for multi-service applications. © 2013 IEEE.

Radio frequency (RF) wireless energy transfer (WET) is a key technology that may allow seamlessly powering future massive low-energy Internet of Things (IoT) networks. To enable efficient massive WET, channel state information (CSI)-limited/free multi-antenna transmit schemes have been recently proposed in the literature. The idea is to reduce/null the energy costs to be paid by energy harvesting (EH) IoT nodes from participating in large-scale time/power-consuming CSI training, but still enable some transmit spatial gains. In this paper, we take another step forward by proposing a novel CSI-free rotary antenna beamforming (RAB) WET scheme that outperforms all state-of-the-art CSI-free schemes in a scenario where a power beacon (PB) equipped with a uniform linear array (ULA) powers a large set of surrounding EH IoT devices. RAB uses a properly designed CSI-free beamformer combined with a continuous or periodic rotation of the ULA at the PB to provide average EH gains that scale as $0.85\sqrt{M}$, where $M$ is the number of PB's antenna elements. Moreover, a rotation-specific power control mechanism was proposed to i) fairly optimize the WET process if devices' positioning information is available, and/or ii) to avoid hazards to human health in terms of specific absorption rate (SAR). We show that RAB performance even approaches quickly (or surpasses, for scenarios with sufficiently large number of EH devices, or when using the proposed power control) the performance of a traditional full-CSI based transmit scheme, and it is also less sensitive to SAR constraints. Finally, we discuss important practicalities related to RAB such as its robustness against non line-of-sight conditions compared to other CSI-free WET schemes, and its generalizability to scenarios where the PB uses other than a ULA topology., Comment: 12 pages, 10 figures. Accepted for publication in IEEE IoT Journal

Lower efficiencies of power amplifiers and increased path losses at higher frequencies are two reasons why utilizing millimeter-wave frequencies for future wireless communications is challenging. In this article, a high-gain multilens-horn antenna system is presented. The antenna system provides highly effective isotropic radiated power by using only a few high-gain antenna elements, where each element only needs a low transmit power of 26 dBm to reach users at far distances. Moreover, due to channel reciprocity, both down- and uplink benefit from an increased antenna gain. It is shown that a reasonable number of high-gain antennas can provide coverage in a 60° sector with an inter-site distance of 300 m. Based on radio-planning simulations, three horn shapes are identified to provide sufficient coverage. The final optimized dual-polarized multilens-horn design is fabricated and experimentally verified. With a low transmit power at the base station (BS) of 26 dBm, a signal strength of at least -65 dBm is achieved in 98.9% of the sector at 28 GHz under non-line-of-sight conditions for the vertical polarization. For the horizontal polarization, an area of 96.2% is covered.

Owing to the unique electromagnetic response ability, artificial electromagnetic metasurfaces have potential applications in medical, imaging, sensing, and other fields. In this paper, a novel composite THz metasurface integrated by carbon nanotubes (CNTs) resonant metasurface and silicon microfluidic channel has been proposed, which combines the advantages of semiconductor and carbon nanotubes film materials. The absorption characteristics and the refractive index sensing capabilities are investigated comprehensively. Calculation results show that two obvious resonant absorption peaks located at 1.20 THz and 1.85 THz and the absorption is nearly 99.6% and 89.8%, respectively; the device performs a good linear relationship between the position of resonant absorption peaks and the refractive index, and the frequency sensitivity can achieve 492 GHz/RIU. The influence of structural parameters and the offset of the center of the CNTs metasurface on the absorption spectrum demonstrate that the novel composite metasurface has a good reliability and stability and can be used for sensing various materials in other frequency regions range from radio frequency through THz and to the infrared regime. This novel composite metasurface has good biocompatibility and low cost, which widens the application range of terahertz functional devices.

The Internet of Vehicles (IoV), as a development and complement of the Internet of Thing, has attracted extensive attention and is expected to play a crucial role in human society with the matured Space-Air-Ground Integrated Networks (SAGIN). Here, we devote ourselves to establish and investigate a UAV-assisted radio frequency (RF)/free space optical (FSO) communication system under the amplified-and-forward protocol with variable gain. More specifically, we assume the RF link follows κ-μ fading and the FSO link experiences Malaga fading, which can characterize the atmospheric turbulence under weak-to-strong condition excellently. In addition, both the pointing errors impairment and the detection techniques for the FSO link are also taken into account. Novel analytical expressions for the end-to-end system, e.g., the cumulative distribution function, probability density function, and moment generating function, are proposed. By capitalizing on these results, some system metrics of the UAV-assisted relaying system are given with the Meijer’s G function. To providing more insights for this UAV-assisted system for SAGIN, high signal-to-noise approximations of these metrics are also presented. Furthermore, the approximated expressions for the outage probability and average BER are given in presence of non-pointing error effect. Finally, all these analytical results are validated with the Monte-Carlo simulations.

We present a new low-complexity interference management algorithm that exploits reconfigurable antennas, removes most of the interference signal power in a K-user interference channel, and achieves the promised but unrealized gain of interference alignment in low-to-medium signal-to-noise ratio (SNR) range. The reconfigurable antenna includes several elements, each controlled individually using a radio frequency (RF) switch. The antenna has only one RF chain, resulting in simple hardware design and enabling low-complexity algorithms. We exploit space-time diversity to find two separate combinations of activating or deactivating antenna elements to allow for interference neutralization/elimination. Finding such states is a cumbersome task for which we develop novel, efficient algorithms. We further devise simple encoding and decoding with short precoder length to exploit the benefits of our designs. Our implementation does not rely on channel state information at the transmitters; works at finite signal-to-noise ratios, unlike the typical degrees-of-freedom results; and works in slow-fading environments. We calculate the average achievable rates, the minimum number of elements to reach a specific level of interference suppression, and we provide outage analysis of our technique.

Phased array calibration is typically carried out inplane-wave conditions, which requires expensive far-field setups.This letter presents a novel phased array calibration methodbased on measured complex array signal, which works in thecost-effective compact testing setup. The basic principle is toemploy multi-probe antennas in a short measurement distancesuch that we can effectively retrieve the array element patternsin the boresight direction based on the recorded complex signalsat the multiple probes using the interpolation technique. Boththeoretical derivations and measurement validations are providedto demonstrate the effectiveness of the proposed method.

This paper explores the use of ambient radio frequency (RF) signals for human presence detection through deep learning. Using WiFi signal as an example, we demonstrate that the channel state information (CSI) obtained at the receiver contains rich information about the propagation environment. Through judicious pre-processing of the estimated CSI followed by deep learning, reliable presence detection can be achieved. Several challenges in passive RF sensing are addressed. With presence detection, how to collect training data with human presence can have a significant impact on the performance. This is in contrast to activity detection when a specific motion pattern is of interest. A second challenge is that RF signals are complex-valued. Handling complex-valued input in deep learning requires careful data representation and network architecture design. Finally, human presence affects CSI variation along multiple dimensions; such variation, however, is often masked by system impediments such as timing or frequency offset. Addressing these challenges, the proposed learning system uses pre-processing to preserve human motion induced channel variation while insulating against other impairments. A convolutional neural network (CNN) properly trained with both magnitude and phase information is then designed to achieve reliable presence detection. Extensive experiments are conducted. Using off-the-shelf WiFi devices, the proposed deep learning based RF sensing achieves near perfect presence detection during multiple extended periods of test and exhibits superior performance compared with leading edge passive infrared sensors. Comparison with existing RF based human presence detection also demonstrates its robustness in performance, especially when deployed in a completely new environment., Source code and datasets are available at Github: https://github.com/bigtreeyanger/presence_detection_cnn

Phased arrays, commonly used in IEEE 802.11ad and 5G radios, are capable of focusing radio frequency signals in a specific direction or a spatial region. Beamforming achieves such directional or spatial concentration of signals and enables phased array-based radios to achieve high data rates. Designing beams for millimeter wave and terahertz communication using massive phased arrays, however, is challenging due to hardware constraints and the wide bandwidth in these systems. For example, beams which are optimal at the center frequency may perform poor in wideband communication systems where the radio frequencies differ substantially from the center frequency. The poor performance in such systems is due to differences in the optimal beamformers corresponding to distinct radio frequencies within the wide bandwidth. Such a mismatch leads to a misfocus effect in near-field systems and the beam squint effect in far-field systems. In this paper, we investigate the misfocus effect and propose InFocus, a low complexity technique to construct beams that are well suited for massive wideband phased arrays. The beams are constructed using a carefully designed frequency modulated waveform in the spatial dimension. InFocus mitigates beam misfocus and beam squint when applied to near-field and far-field systems.

With the development of wireless communication technology, the electromagnetic environment has become more and more complex. Conventional signal identification methods are difficult to accurately identify illegal devices. However, electromagnetic signals have an unavoidable device-specific characteristic unintentionally generated by a transmitter, appearing in the form of an UnIntentional Modulation (UIM), namely Radio Frequency Fingerprint (RFF). RFFs can be used to uniquely identify an emitter to match a received signal with its source. In this paper, the authors propose a novel RFF scheme to separate UIM part from the original signals from the time and frequency domain, and then utilize non-Gaussian measuring tools to extract a set of dimension-reduced secondary features. Additionally, Singular Value Reconstruction (SVR) is developed to extract UIM in the frequency spectrum. In time domain, a curve-fitting residual method is proposed to extract the UIM on the estimated instantaneous phase based on Maximum Likelihood Estimator (MLE). Various aspects of the proposed method are evaluated, including identification accuracy under various Signal-to-Noise Ratio (SNR) conditions, energy relationships between the UIM and the whole signal, and sensitivity to training set size. Compared with other methods, experimental results based on real-world signals prove that the proposed method has remarkable performance and high practicability.

This article proposes an interleaving switched-capacitor RF digital-to-analog converter (RFDAC) using an edge combiner within the output stage to implicitly triple its effective clock carrier frequency and enable the mm-wave (mmW) operation. Tripling in the output stage allows for increased energy efficiency, which is further improved by employing an edge-combining-based frequency-tripling delay-locked loop (DLL) in the clock generation network. The clock tripling is performed in each slice of the switched-capacitor PA (SCPA), which allows yet another 3x frequency reduction for the global clock distribution. Finally, a new layout structure accounts for transmission-line (TL) effects, due to the large physical size of the passive capacitor array. Implemented in 22-nm FD-SOI, the prototype achieves ${ {{P_{ out}}}>21}$ dBm, drain efficiency >36%, and system efficiency >22% while operating in the Ka-band at 28 GHz. Modulation at 2.4 Gb/s results in 3.3% EVM and 30.8-dBc adjacent channel leakage ratio (ACLR). Science Foundation Ireland [14/RP/I2921]; Microelectronic Circuits Centre Ireland (MCCI) through Enterprise Ireland [TC-2015-0019] Published version This work was supported in part by the Science Foundation Ireland under Grant 14/RP/I2921 and in part by the Microelectronic Circuits Centre Ireland (MCCI) through Enterprise Ireland under Grant TC-2015-0019.

A highly efficient and compact quad-band energy harvester (QBEH) circuit based on the extended composite right- and left-handed transmission lines (E-CRLH TLs) technique is presented. The design procedure based on E-CRLH TLs at four desired frequency bands is introduced to realize a quad-band matching network (QBMN). The proposed QBEH operates at four frequency bands: f1=0.75 GHz,f2=1.8 GHz,f3=2.4 GHz and f4=5.8 GHz. The simulations and experimental results of the proposed QBEH exhibit overall (end to end) efficiency of 55% and 70% while excited at four frequency bands simultaneously with -20 dBm and -10 dBm input power, respectively. Due to applying multi-band excitation technique and radio frequency (RF) combining method in the QBEH circuit, the sensitivity is improved, and sufficient power is generated to realize a self-sustainable sensor (S3) using ambient low-level RF signals. A favorable impedance matching over a broad low input power range of -50 to -10 dBm is achieved, enabling the proposed QBEH to harvest ambient RF energy in urban environments. Moreover, an accurate theoretical analyses based on the Volterra series and Laplace transformation are presented to maximize the output DC current of the rectifier over a wide input power range.

The upgraded European 1-MW, 170-GHz continuous wave (CW) industrial prototype gyrotron (TH1509U) for electron cyclotron resonance heating and current drive in ITER was tested at the Karlsruhe Institute of Technology (KIT). In this work, we report on the major achievements during the experimental campaigns that took place intermittently between October 2020 and July 2021. The upgraded gyrotron clearly surpassed the performance of the previous TH1509 tube. In particular, TH1509U delivered (i) 0.9 MW in 180 s pulses (maximum possible pulse length with the KIT test stand) and (ii) more than 1 MW at a pulse length limited to 40 s, due to an unforeseen problem with the test stand cooling circuit at that time. In addition, it was possible to also demonstrate gyrotron operation at (iii) 0.5 MW in 1600 s pulses. The experiments will be continued at the FALCON test stand at the ecole Polytechnique Federale de Lausanne (EPFL).