Direct downconversion of multiple RF signals using bandpass sampling

In this letter, we consider a case in which only one radio frequency (RF) signal is of interest over multiple RF signals with contiguous spectrums (i.e., these RF signals are adjacent to each other). The minimum valid bandpass sampling range for a desired RF signal over multiple ones is derived under the assumption of contiguous spectrums. The sampling frequency confined by the derived minimum valid sampling range is significantly reduced compared to the case in which all the RF signals are desired. The minimum valid bandpass sampling frequency can be further reduced when the desired RF signal has symmetric double sidebands.

In high density radio frequency (RF) signal environments, receivers usually acquire multiple source signals. These multiple source RF signals may be cochannel and co-duration and cause significant difficulties for the traditional time frequency approach to process them. In this paper, combining graph and projection pursuits techniques, we propose a new time frequency analysis approach for RF signal processing. The proposed approach allows us to separate cochannel and co-duration frequency modulation RF (FMRF) signals with low implementation cost.

Purpose: The aim of this study was to determine whether exposure to radiation from single or multiple radio-frequency (RF) signals at 900 and 2450 MHz would induce effects in the RAW 264.7 cell line.Materials and methods: Cell cultures were exposed to single or combined RF for 4, 24, 48, or 72 h in a GTEM electromagnetic test chamber. At the end of the radiation exposure time, viability and cell growth were analyzed by flow cytometry, nitric oxide (NO) production was measured by colorimetry, the expression of HSP70 and TNF-α was ascertained by qPCR, and the phagocytic activity was observed by microscopy.Results: NO production increased after 48 h exposure at 2450 MHz, compared with controls. The group subjected to the combined interaction of two RFs showed an increase of HSP70 after 48 h exposure and a significant increase of NO and TNF-α after 72 h. The phagocytic activity of macrophages decreased in all groups as exposure time increased.Conclusions: Our results indicated a decrease in phagocytic activity and an increase in inflammatory, cytoprotective, and cytotoxic responses in macrophages after continuous and combined exposure of multiple RF signals. Multiple RF interact in everyday life, the immune response in humans is unknown.

This paper introduces a novel framework, i.e., RFPose-OT, to enable three-dimensional (3D) human pose estimation from radio frequency (RF) signals. Different from existing methods that predict human poses from RF signals at the signal level directly, we consider the structure difference between the RF signals and the human poses, propose a transformation of the RF signals to the pose domain at the feature level based on the optimal transport (OT) theory, and generate human poses from the transformed features. To evaluate RFPose-OT, we build a radio system and a multi-view camera system to acquire the RF signal data and the ground-truth human poses. The experimental results in a basic indoor environment, an occlusion indoor environment, and an outdoor environment demonstrate that RFPose-OT can predict 3D human poses with higher precision than state-of-the-art methods.

Several methods of imaging have been developed to study myocardial characteristics. Echocardiography, computer tomography (CT), and magnetic resonance imaging (MRI) can be used for visualization of cross-sectional images of the heart, but their imaging is restricted to large motion and low frequency components. Vibrations of heart wall with small amplitudes (about ± 100 μm and up to a few hundred Hertz) are superimposed on the large amplitude and low frequency motions (about ± 15mm, several Hertz). Several techniques have been suggested for processing and measuring these vibrations, which need radio frequency (RF) signals to be processed. The aim of this search is to simulate myocardium image formation in ultrasound system and to model its motion in a cardiac cycle. There are different techniques to simulate heart wall and its motion. Here a model of heart with its motion and vibrations is produced in a period, also its RF signals and echocardiography image are gotten. For doing these, Field II software is used. By using this simulation, it is possible to simulate heart diseases and their effects on heart wall vibrations in echocardiography images and its RF signals.

A technique to estimate an incoming radio frequency (RF) signal angle of arrival (AOA) irrespective of the RF signal amplitude is presented. It is based on measuring the DC voltage at the output of two modules where each of them consists of an optical modulator, an optical filter and a photodetector. An RF signal amplitude‐independent AOA can be obtained from the ratio of the two DC voltages. Experimental results are presented that demonstrate 0°–63° AOA measurement with <3° errors for an RF signal with three different power levels of 3.2, −0.3 and −3.6 dBm into the modulator.

Advancement in technology has led to creative and innovative inventions. One such invention includes unmanned aerial vehicles (UAVs). UAVs (also known as drones) are now an intrinsic part of our society because their application is becoming ubiquitous in every industry ranging from transportation and logistics to environmental monitoring among others. With the numerous benign applications of UAVs, their emergence has added a new dimension to privacy and security issues. There are little or no strict regulations on the people that can purchase or own a UAV. For this reason, nefarious actors can take advantage of these aircraft to intrude into restricted or private areas. A UAV detection and identification system is one of the ways of detecting and identifying the presence of a UAV in an area. UAV detection and identification systems employ different sensing techniques such as radio frequency (RF) signals, video, sounds, and thermal imaging for detecting an intruding UAV. Because of the passive nature (stealth) of RF sensing techniques, the ability to exploit RF sensing for identification of UAV flight mode (i.e., flying, hovering, videoing, etc.), and the capability to detect a UAV at beyond visual line-of-sight (BVLOS) or marginal line-of-sight makes RF sensing techniques promising for UAV detection and identification. More so, there is constant communication between a UAV and its ground station (i.e., flight controller). The RF signals emitting from a UAV or UAV flight controller can be exploited for UAV detection and identification. Hence, in this work, an RF-based UAV detection and identification system is proposed and investigated. In RF signal fingerprinting research, the transient and steady state of the RF signals can be used to extract a unique signature. The first part of this work is to use two different wavelet analytic transforms (i.e., continuous wavelet transform and wavelet scattering transform) to investigate and analyze the characteristics or impacts of using either state for UAV detection and identification. Coefficient-based and image-based signatures are proposed for each of the wavelet analysis transforms to detect and identify a UAV. One of the challenges of using RF sensing is that a UAV's communication links operate at the industrial, scientific, and medical (ISM) band. Several devices such as Bluetooth and WiFi operate at the ISM band as well, so discriminating UAVs from other ISM devices is not a trivial task. A semi-supervised anomaly detection approach is explored and proposed in this research to differentiate UAVs from Bluetooth

Low-phase-noise dual-tone radio frequency (RF) signal generation is realized by injecting a low-frequency signal into a dual-passband optoelectronic oscillator (OEO). The dual-passband OEO is realized by paralleling two individual electrical filters with different center frequencies in the oscillation loop, and the injection signal’s frequency equals the frequency difference between the two generated oscillation signals. Due to the modulation nonlinearity of the oscillation loop, the low-frequency injection signal enables mutual frequency conversion between the two oscillation frequencies, leading to sustained mutual injection locking. In a proof-of-concept experiment, two RF signals with frequencies of 10.6637 GHz and 14.0008 GHz are simultaneously generated by injecting a 3.3371-GHz signal into the proposed OEO. The phase noises at a 10-kHz frequency offset of the generated RF signals are −140.06 dBc/Hz and −140.13 dBc/Hz, respectively, and the side-mode suppression ratios are larger than 60 dB.

In this paper, the study on applications of radio frequency nano antenna energy conversion and supercapacitors is presented. Radio Frequency (RF) signals are a form of electromagnetic radiation with wavelengths greater than 3 meters. Initially used in wireless communication devices like radios and walkie-talkies, RF signals have found their way into energy conversion and storage applications. When RF signals are received by an antenna with coupled capacitors and a rectifier circuit, they generate a potential difference of a few millivolts. This potential difference can be used as a stable source of energy to power low-voltage applications through ambient RF radiation, and excess energy can be stored in electrochemical storage systems like supercapacitors and lithium-ion batteries. While this technology is currently limited to low-power applications, it has immense potential in various fields such as medicine, automotive industry, military applications, and more. Researchers are currently working to improve the energy density of supercapacitors by modifying their electrode materials using nanotechnology. One promising material is lignin, derived from wood fibers, which has shown great performance in tests and is expected to be a low-cost solution for high-performance batteries and supercapacitors. As the renewable energy sector continues to advance, we can expect to see more useful applications based on RF nano antennas and micro/nano-sized supercapacitors. The work done & presented in this paper is the result of the mini-project work that has been done by the first sem engineering students of the college and as such there is little novelty in it and the references are being taken from various sources from the internet, the paper is being written by the students to test their writing skills in the starting of their engineering career and also to test the presentation skills during their mini-project presentation. The work done & presented in this paper is the report of the assignment / alternate assessment tool as a part and parcel of the academic assignment of the first year subject on nanotechnology & IoT.

Image quality improvement in single plane-wave imaging using deep learning

Nonlinear transmission lines (NLTL) are gaining extensive research focus as a way to generate high-power radio frequency (RF) signals. NLTLs can be classified into two groups: lumped transmission lines containing L-C sections, and external magnetic field-biased line loaded with continuous ferromagnetic materials known as gyromagnetic lines. Traditionally, without a continuous supply of input excitation, NLTLs cannot produce self-sustaining RF signals. In this regard, the authors present a design and demonstration of a self-sustaining soliton generator. The design is based on a 16-section Schottky diode-based NLTL prototype complemented by a solid-state switch (LDMOS) based 1.5 kW (continuous) rated power amplifier (PA), and a custom-made high voltage (650 V) pulse generator. A closed-loop configuration constructed from these components can produce a continuous stream of RF signals from a single input excitation. The prototype is able to generate a peak pulsed RF power of 2.1 kW across a 50 Ω resistive load. To the best of the authors’ knowledge, solid-state switch-based PA has not been introduced in any NLTL design until now to produce self-sustaining RF signals.

A switchable dual-band binary and single-band quaternary phase-coded microwave signal generator based on a single dual-polarization dual-drive Mach–Zehnder modulator (DP-DDMZM) is proposed. Two radio frequency (RF) signals are first coupled with two bipolar coded signals and then used to drive the DP-DDMZM. When the frequencies of the two RF signals are different, the generator will be in dual-band binary phase-coded mode and a dual-band binary phase-coded signal can be generated. When the frequencies of the two RF signals are the same but their phase difference is adjusted to be 90°, the generator will be in single-band quaternary phase-coded mode and a single-band quaternary phase-coded signal can be obtained. Detailed analysis is carried out to illustrate the mechanism and a proof-of-concept experiment is also performed to demonstrate the feasibility. The dual-band binary and single-band quaternary phase-coded microwave signal are both experimentally generated and their performance is evaluated. The proposed generator features the advantages of simple structure, high flexibility and stable performance, which is promising in the future multifunctional radar systems.

Energy harvesting from the renewable sources has been the main concern in the present scenario. Till now most of the researchers focused on harvesting solar energy and wind energy. However the small amount of energy harvesting without affecting environment is very important. In the recent years mobile communication has become a part of our daily life, extracting energy from the Radio Frequency (RF) signals used everywhere is an attractive solution to the existing energy problem. Another major source of harvesting small amount of energy is from the human body heat. The energy extractions from these sources are emerging as a guaranteed alternative way to substitute the available energy resource to some extent. This paper presents a hybrid model which consists of two sections. First being the harvesting of energy from the RF signals in the range of GSM 4G band (1800-2100 MHz) using a micro-strip patch antenna followed by impedance matching circuit to reduce the dissipated power between load and antenna. Then a rectifier circuit that converts RF into DC signals is used and finally a voltage multiplier circuit is used to boost up the DC voltage. Second section consists of Thermo Electric Generator (TEG) module which converts human body heat into electricity, followed by a voltage booster to increase the level of voltage. The main objective of this work is to find a way to design a hybrid system that can harvest energy from RF signals as well as human body heat and the combined energy that is harvested can be used to power up low voltage implant device.

Wideband photonic microwave channelization and image-reject down-conversion

We demonstrate an optical mixing system for measuring properties of sparse radio frequency (RF) signals using compressive sensing (CS). Two types of sparse RF signals are investigated: (1) a signal that consists of a few 0.4 ns pulses in a 26.8 ns window and (2) a signal that consists of a few sinusoids at different frequencies. The RF is modulated onto the intensity of a repetitively pulsed, wavelength-chirped optical field, and time-wavelength-space mapping is used to map the optical field onto a 118-pixel, one-dimensional spatial light modulator (SLM). The SLM pixels are programmed with a pseudo-random bit sequence (PRBS) to form one row of the CS measurement matrix, and the optical throughput is integrated with a photodiode to obtain one value of the CS measurement vector. Then the PRBS is changed to form the second row of the mixing matrix and a second value of the measurement vector is obtained. This process is performed 118 times so that we can vary the dimensions of the CS measurement matrix from 1×118 to 118×118 (square). We use the penalized ℓ(1) norm method with stopping parameter λ (also called basis pursuit denoising) to recover pulsed or sinusoidal RF signals as a function of the small dimension of the measurement matrix and stopping parameter. For a square matrix, we also find that penalized ℓ(1) norm recovery performs better than conventional recovery using matrix inversion.