Received RF Signal Research Articles

Design and implementation of RF power levels measurement system from indoor to outdoor in Isparta province

This paper presents a novel, low-cost, and portable RF power measurement system, operating in GSM 900 and GSM 1800 frequency bands. This measurement model consists of four basic circuits; microstrip folded dipole antenna (MFDA) that received the ambient RF signals, a power meter that generates DC output voltage according to received RF signal power level, a microprocessor that converts the data's analog to digital, and a computer to record and screen the time-varying data. Seventeen measurements, each for six hours, were performed in nine locations in Isparta for the indoor-to-outdoor scenario. The range between the minimum and maximum power values of the average RF power levels obtained in time-dependent measurements was calculated as approximately 15 dB, 18 dB, and 33 dB for indoor, semi-indoor, and outdoor ambients, respectively. The indoor/semi-indoor/outdoor ambient RF power levels were respectively varied between −55.1 dBm to −4.13 dBm, −43.92 dBm to −6.12 dBm, −44.89 dBm to 0.1 dBm in all measurements.

Displacement Estimation via 3D-Printed RFID Sensors for Structural Health Monitoring: Leveraging Machine Learning and Photoluminescence to Overcome Data Gaps.

Monitoring object displacement is critical for structural health monitoring (SHM). Radio frequency identification (RFID) sensors can be used for this purpose. Using more sensors enhances displacement estimation accuracy, especially when it is realized through the use of machine learning (ML) algorithms for predicting the direction of arrival of the associated signals. Our research shows that ML algorithms, in conjunction with adequate RFID passive sensor data, can precisely evaluate azimuth angles. However, increasing the number of sensors can lead to gaps in the data, which typical numerical methods such as interpolation and imputation may not fully resolve. To overcome this challenge, we propose enhancing the sensitivity of 3D-printed passive RFID sensor arrays using a novel photoluminescence-based RF signal enhancement technique. This can boost received RF signal levels by 2 dB to 8 dB, depending on the propagation mode (near-field or far-field). Hence, it effectively mitigates the issue of missing data without necessitating changes in transmit power levels or the number of sensors. This approach, which enables remote shaping of radiation patterns via light, can herald new prospects in the development of smart antennas for various applications apart from SHM, such as biomedicine and aerospace.

Modeling Method of Multiplexed Sampling Electrical Parameter Characteristics Based on AIOT Sensing Module

Abstract In order to further reduce the errors arising in synchronous sampling, this paper designs a multi-channel hybrid sampling electrical parametric feature modeling method based on an AIOT sensing module in the process of design. The AIOT sensing module is used to process the received RF signals using a transconductance amplifier to improve the digitization and reconfigurability of the RF front-end circuit. The signal is transformed and calculated using the Fast Fourier Transform to obtain electrical parameters such as the amplitude of each harmonic and the power factor. The results show that the variation amplitude of the window function of the design method in this paper is generally maintained between -1.5 and 1.5, the amplitude accuracy of the active power rate is within 3.17555%, and the relative error accuracy is within 0.000951%. It can be seen that the AIOT-based sensing module can significantly improve the calculation accuracy of electrical parameters and can be applied to the process of sampling digital measurements of other power signal characteristics.

Wi-Flex

In this paper, we are interested in startle reflex detection with WiFi signals. We propose that two parameters related to the received signal bandwidth, maximum normalized bandwidth and bandwidth-intense duration, can successfully detect reflexes and robustly differentiate them from non-reflex events, even from those that involve intense body motions (e.g., certain exercises). In order to confirm this, we need a massive RF reflex dataset which would be prohibitively laborious to collect. On the other hand, there are many available reflex/non-reflex videos online. We then propose an efficient way of translating the content of a video to the bandwidth of the corresponding received RF signal that would have been measured if there was a link near the event in the video, by drawing analogies between our problem and the classic bandwidth modeling work of J. Carson in the context of analog FM radios (Carson's Rule). This then allows us to translate online reflex/non-reflex videos to an instant large RF bandwidth dataset, and characterize optimum 2D reflex/non-reflex decision regions accordingly, to be used during real operation with WiFi. We extensively test our approach with 203 reflex events, 322 non-reflex events (including 142 intense body motion events), over four areas (including several through-wall ones), and with 15 participants, achieving a correct reflex detection rate of 90.15% and a false alarm rate of 2.49% (all events are natural). While the paper is extensively tested with startle reflexes, it is also applicable to sport-type reflexes, and is thus tested with sport-related reflexes as well. We further show reflex detection with multiple people simultaneously engaged in a series of activities. Optimality of the proposed design is also demonstrated experimentally. Finally, we conduct experiments to show the potential of our approach for providing cost-effective and quantifiable metrics in sports, by quantifying a goalkeeper's reaction. Overall, our results confirm a fast, robust, and cost-effective reflex detection system, without collecting any RF training data, or training a neural network.

Photonics-Assisted Simultaneous RF Channelization and Self-Interference Cancellation

Both RF channelization and self-interference cancellation are urgently required for modern in-band full-duplex systems. A photonics-assisted RF receiver for simultaneous wideband channelization and self-interference cancellation is proposed and demonstrated. The key is the implementation of dual optical frequency combs (OFCs) followed by microwave photonic image-reject mixers (IRMs) using a dual-output Hartley structure. The received RF signal and the reference signal are modulated to a pair of signal OFCs with orthogonal polarization states, respectively. The microwave photonic IRM is applied on each polarization state, respectively. For each local OFC comb line, two components will be sliced and downconverted from each copy of the optically-carried received RF signal. Meanwhile, another two components will be sliced and downconverted from the optically-carried reference signal. After combining the outputs of the IRMs, the components from the image signal and the self-interference signal will be eliminated simultaneously. Two channels of the signal of interest will be obtained for each local OFC comb line. Experimental results show that an RF signal with an instantaneous bandwidth of 6 GHz (from 7 to 13 GHz) is channelized into 6 channels, each of which has a 1-GHz bandwidth. The isolation of larger than 28 dB between the channels is realized, and the simultaneous self-interference cancellation and image-rejection are achieved.

Single Packet, Single Channel, Switched Antenna Array for RF Localization

Cost-effective and accurate means of localizing radio transmitters has the potential to enable a wide range of applications in the consumer electronics, IoT, and healthcare domains. However, existing multi-antenna localization methods require high-cost synchronized receivers, long integration times, and/or specialized packet structures. This paper proposes using a high-speed RF mux that sequentially connects antennas to a single 2MHz radio receiver and sub-packet switching to determine the Angle of Arrival of individual packets. Importantly, this approach does not need synchronization between the mux and the receiver, reducing cost and system complexity. Our signal processing pipeline recovers both switch timing and the antenna number from the received RF signal. The sub-packet waveforms are used to generate a synthetic reference packet, and our customized Multi-Resolution Beaming and MUSIC algorithms are used to determine the Angle of Arrival. Results show that our real-time system is highly accurate even when the target is moving, with a mean AoA accuracy of 3.4 degrees and a 2D localization accuracy of 36.4 cm. Furthermore, the system is capable of tracking multiple users carrying smartphones in either their hands or pockets. Ultimately this approach enables a single low-cost, low bandwidth commodity RF receiver to be used to create an N-element phased array receiver.

Non-intrusive RF sensing for early diagnosis of spinal curvature syndrome disorders

The recent developments in communication and information ease people’s lives to sit in one place and access any information from anywhere. However, the longevity of sitting and sitting in different postures raises the issues of spinal curvature. It necessitates a physical examination to identify the spinal illness in its early stages. This article aims to develop an intelligent monitoring framework for detecting and monitoring spinal curvature syndrome problems based on Software Defined Radio Frequency (SDRF) sensing and verify its feasibility for diagnosing actual patients. The proposed SDRF-based system identifies irregular spinal curvature syndrome and offers feedback signals when an incorrect posture is identified. We design the system using wireless university software-defined radio peripheral (USRP) kits to transmit and receive RF signals and record the wireless channel state information (WCSI) for kyphosis, Lordosis, and scoliosis spinal disorders. The statistical measures are extracted from the WCSI and apply machine learning algorithms to identify and classify the type of disorders. We record and test the system using 11 subjects with the spinal disorders kyphosis, Lordosis, and scoliosis. We acquire the WCSI, extract various statistical measures in terms of time and frequency domain features, and evaluate machine learning classifiers to identify and classify the spinal disorder. The performance comparison of the machine learning algorithms showed overall and each spinal curvature disorder recognition accuracy of more than 99%.

Simultaneous Angle-of-Arrival and Frequency Measurement System Based on Microwave Photonics

A simultaneous angle-of-arrival (AOA) and frequency measurement system based on microwave photonics is proposed and experimentally demonstrated. The measurement of the AOA and the frequency is realized based on the simultaneous AOA-to-power and frequency-to-time mapping. Using optical pulses and optical dispersion elements, the frequencies of the received RF signals will map to the time intervals of the output electrical pulses. At the same time, by introducing a DPMZM, the received RF signals with the AOA-dependent phase differences interfere in the optical domain, mapping the AOA-dependent phase difference to the power of the interfered optical sidebands, which further maps to the output electrical pulse amplitudes. By measuring the time intervals and the normalized amplitudes of the output electrical pulses, the AOA and the frequency can be obtained simultaneously. In addition, the measurement of multiple RF signals can be realized due to the independence of the output mapping signals in the time domain for different RF frequencies. A proof-of-concept experiment is carried out. The AOA measurement from -70º to 70º with a measurement error of ±2.5º, and the frequency measurement from 5 to 15 GHz with a measurement error of ±12 MHz are successfully achieved simultaneously. The measurements of single-tone and multiple RF signals are experimentally achieved.

Power-fading-mitigation approach in an intensity-modulated radio-over-fiber link using a single integrated micro-ring resonator

In this paper we address the limiting effect of power fading (PF) in fiber optic communication links, due to the fiber’s dispersive properties, and suggest a mitigation approach in intensity-modulated radio-over-fiber (RoF) applications. The proposed method is independent of the length of the optical transmission path. PF is mitigated by employing a simple integrated photonic structure, i.e., a single micro-ring resonator. The latter features a periodic notch-filter response, employed to suppress one of the sidebands in an optical double sideband (ODSB) modulation, reducing the PF of the received RF signal. The suppression ratio measured by the optical spectrum analyzer is 24 dB. In this way we succeeded in reducing the RF signal’s power ripple at the receiving end to 3 dB. The proposed approach promises an economic yet effective solution to overcoming the PF in point-to-multipoint-topology optical networks.

Time-Index Modulation for Integrated Data and Energy Transfer: A Remedy for Time Switching

In order to realise integrated data and energy transfer (IDET), an energy-thirsty communication device may arbitrarily switch between the information decoding and energy harvesting modes in the time domain. However, when the device is in the energy harvesting mode, it cannot decode information carried by the received RF signal, which results in substantial information loss. To compensate for this information loss, a novel time-index modulation (TIM) based IDET system is proposed. A transmission frame includes a range of symbols, which are sequentially sent. Only a single symbol is modulated for wireless data transfer (WDT), while all the others are for wireless energy transfer (WET). The index of the WDT symbol may carry additional information. After investigating the transceiver architecture, we also theoretically analyse the WDT and WET performance of this TIM based IDET. Simulation results demonstrate the advantage of the TIM based IDET system over the traditional time-switching (TS) and power-splitting (PS) approach.

Optimized Reconstruction Procedure of Photoacoustic Imaging for Reflection Artifacts Reduction.

Photoacoustic (PA) imaging technology is of some value in medical diagnoses such as breast cancer detection, vasculature imaging, and surgery navigating. While as most imaging objects are bounded, the received RF signals consist of the direct-arrived signals (DAS) from the PA sources and the boundary-reflected signals (BRS). The undesired BRS will severely impair the quality during the image reconstruction. They will bring in many artifacts and confuse the actual shape and location of the PA sources. We improved the reconstruction procedure by removing the BRS before the regular reconstruction process to suppress those artifacts. To verify our proposed method, we compared the results of the conventional and optimized procedures experimentally. In terms of qualitative observation, the reconstructed images by the optimized procedure illustrate fewer artifacts and more accurate shapes of the PA sources. To quantitatively evaluate the traditional and the optimized imaging procedure, we calculated the Distribution Relative Error (DRE) between each experiment result and its standard drawing of the phantoms. For both phantoms and the ex-vivo sample, the DREs of reconstruction result by the optimized reconstruction procedure decrease significantly. The results suggest that the optimized reconstruction process can effectively suppress the reflection artifacts and improve the shape accuracy of the PA sources.

Improving axial resolution of medical ultrasound images by using noise-robust broadband filter based on singular value decomposition

Improving spatial resolution is a crucial issue in medical ultrasound. One of the improving methods is the post-processing of the received ultrasound RF signal. In the present paper, we proposed a design method for a noise-robust broadband filter based on the singular value decomposition of the received RF signal. To design a noise-robust filter, we proposed a logical method to determine the optimal truncated order of singular values, which was validated by applying the filter to noise-contaminated signals. Furthermore, the proposed filter applied to the wire phantom resulted in a better axial resolution than that obtained without the filter and with our previously designed Wiener filter.

Energizing Low Power Devices by Harvesting Energy from Ubiquitous Electromagnetic Wave Resources

In the recent years most of the devices are designed with low power consumption such as wearable devices, remote monitoring sensors, sensors used in fashionablecities. However, even long lasting batteries have a limited lifespan and must be replaced every few years. Replacements of batteries become costly when there are hundreds of sensors in rural areas.Technologies of Energy harvesting, on the other hand, provide infinite operating life of low-power equipment and avoid the need to replace batteries where it is costly, impractical or hazardous. Energy Harvesting (EH) is a process wherein the sources such as mechanical load, vibrations, temperature gradients and light, etc., serve as the resource from which the energy harvested and transformed to obtain relatively small levels of power in the range of nW-mW. The transducer converts one form of energy to other form usually electrical signal. The output obtained from the RF antenna is sent for power conditioning to ensure the operating frequency, voltage and current. The received RF signal is given to the matching network to provide proper impedance matching between the antenna and the signal conditioning circuit. The received RF signal is rectified and passed through the voltage multiplier circuit. In order to get sufficient output voltage to drive the device voltage quadrupler is used in the proposed system. As electromagnetic wave is available in surplus in our surrounding, it can be an uninterrupted resource for the energy generation for the device. Energy storage device is associated with the energy scavenging circuitry to enable the energy scavenged to be utilized for future purpose. The proposed system meets the state-of-the-art in the field of energy harvesting for low power devices using the RF energy harvesting.

Throughput analysis of dual hop hybrid RF-VLC system with wireless energy harvesting

Abstract In this paper, we study a dual hop hybrid radio frequency-visible light communication (RF-VLC) system with wireless energy harvesting technique. In the proposed model the RF channel and the VLC channel are modelled by generalized-K distribution and lambertian emission model, respectively. A decode and forward relay is used as an intermediate node where power splitting relaying (PSR) protocol is employed to harvest energy from the received RF information signal. The source transmits the information signal towards the relay via RF channel. The relay then decodes the received signal and convert it into corresponding light signal. Simultaneously the energy harvesting circuit at relay harvests the energy from the received RF signal. The relay utilizes the harvested energy to aid the transmission of the light signal towards the user situated inside the building’s room at the destination. Further, the statistics of the instantaneous SNR of the hybrid RF-VLC system at the destination are derived by employing the PSR protocol to obtain an accurate closed form analytical expression for the system’s end-to-end ergodic capacity and achievable throughput in terms of Meijer’s G function. Further, with the help of numerical simulations, we analysed the end-to-end ergodic throughput performance of the hybrid system under the influence of varying channel parameters such as signal to noise ratio, power splitting factor, shadowing parameters, distance between source & relay and source transmitted power.

Towards Spoofing Resistant Next Generation IoT Networks

The potential vulnerability to wireless spoofing attacks is still a critical concern for Next Generation Internet of Things (NGIoT) networks which may result in catastrophic consequences in mission–critical applications. Conventional solutions may impose additional signal processing, protocol, and latency overheads which are inappropriate for NGIoT networks designed to provide high–speed and low–latency connections for a large number of resource–constrained IoT devices. In this paper, we utilize the uniqueness of beam pattern features in mmWave–enabled devices and propose a scalable security mechanism for the detection of wireless spoofing attacks in NGIoT networks. This uniqueness is proven to exist due to the non–ideal manufacturing of antenna arrays used in mmWave–enabled devices. In our approach, when legitimate mmWave–enabled IoT devices enrol into the network, their unique beam features are learned by a learning model developed at the network server. Then, during data transmission, network base stations (gNBs)/Access Points (APs) measure the beam features from the received RF signals and send them to the network server for the detection of anomalies. We develop our learning model based on Deep Autoencoders (DAEs) that are an effective tool for anomaly detection. Fortunately, the beam feature extraction can be performed using the beam searching mechanism that is already provided in mmWave standards (5G–NR and IEEE 802.11ad). Thus, feature extraction does not introduce any signal processing overheads to the system. Moreover, the proposed mechanism imposes zero computation/communication overhead to the resource—constrained IoT nodes. In our experiments, we reached 98.6% accuracy in the detection of illegitimate devices which confirms the effectiveness of the proposed approach.

Разработка математической модели интерферометрической системы определения доплеровского сдвига частоты.

This work presents the result of the received signal measuring system for processing Doppler frequency theoretical research. In the researching device means of controlling laser frequency whose amplitude is proportional to the Doppler frequency shift of the received RF signal is realized. The coherent laser beam is divided in two forming interference pattern. In this case, one of the beams passes through the delay line, which leads to a phase shift in the optical wave. The rate of this phase shift is proportional to the laser frequency, changes in which cause corresponding changes in the interference pattern. Changes in the interference pattern in center analysis makes it possible to determine the changes of the laser frequency, which depends on Doppler frequency shift of the received RF signal. In this work opposition of the requirements for the Doppler frequency shift determination interferometric system parameters (the coefficient of proportionality to conversion Doppler frequency shift of the received RF signal in laser frequency and time delay) is discovered: large dynamic measurement range and high Doppler frequency shift measurement resolution. The processing the received RF signal method is proposed. This method take into consideration these requirements. The proposed measurement algorithm implements the multiscale principle. It is pointed that the proposed processing the measurements results method can be implemented both the parallel processing in channels with different values of conversion coefficients, and sequential – with their iterative change.

Modeling and Designed of a Monopole Antenna that Operate at 3.3 [GHz] for Future 5G sub 6 [GHz

Antenna unit is an important part of ADAS L2, L2+ and Automated Driving L3 systems. It needs to function as needed in dGPS, HD Map Correction Services, OEM Radios and Navigation Systems. The presented monopole antenna model for 5G below 6 [GHz] operating at 3.3 [GHz] is developed. This work demonstrates the modeling, design, and determining of monopole antenna with intended targeted applications within the automotive system emerging autonomous vehicles space and as well as 5G Wireless Cellular Technology domain. FEKO simulation is undertaken rather than mathematical modeling to create the structure and conduct the analysis of the proposed monopole antenna. In order to support the fifth generation (5G) of wireless communication networks, SOS messages, vehicle tracking, remote vehicle start, Advanced Driver Assistance Systems (ADAS) L2, L2+/ Autonomous Driving (AD) L3 systems self-driving vehicles powered by 5G with rapidly growing sets of ADAS and AD features and functions within the autonomous space, USA cellular carriers mobile phone communication standard 4G MISO and 5G MIMO, LTE1, LTE2, connected functions, features/services, IoT, DSRC, V2X, and C-V2X applications and 5G enable vehicles destined for the NAFTA (USA, Canada and Mexico) market, a new single monopole antenna that operate at 3.3 [GHz] for future 5G (MIMO) below 6 [GHz] modeling, design and simulation with intended automotive applicability and applications is proposed. The presented novel new 5G below 6 [GHz] monopole antenna: 1. Is not being investigated on the literatures review and published papers studied. 2. No paper exists on these frequency bands. 3. The desired monopole antenna is a new antenna with fewer components, reduction in size, low profile, competitive cost, better response to received RF signals for frequencies for future 5G below 6 [GHz] with each of the following: a. Range of operating frequencies, 0.6 [GHz] to 5.9256 [GHz]. b. Center frequency = 3.2628 [GHz] ~ 3.3 [GHz] for the above band. c. Lambda (λ) = (3.0 x10^8 [m/sec^2]) / (3.3x10^9 [Hz]) = 0.090 [m] = 90 [mm], lambda (λ) /4 = (0.090 [m])/4 = 0.0225 [m] = 22.5 mm ~ 23 [mm], the overall monopole antenna height. To be more direct, simulation studies are carried out and are done utilizing FEKO software package from Altair to model the proposed monopole antenna for 5G below 6 [GHz] frequency band. The focus is on the frequency band for 5G sub 6 [GHz] cellular system. The paper will introduce the following key points: 1. Modelled and anayzed single element 5G sub 6 [GHz] monopole antenna. 2. Student version of CAD FEKO program was used to design our desired monopole antenna with a wire feed excitation coupled with step-by-step instructions is undertaken to highlight the model geometry creation of our monopole antenna. POST FEKO program is used to plot and view our simulation results. 3. We report the development of 5G below 6 [GHz] for fifth generation (5G) system that meets automotive and vehicle homologation specification requirement of antenna height < 70 [mm]. So that the proposed monopole antenna can easly be integrated into multi tuned cellular antenna system. 4. The FEKO simulation is conducted in 2D and 3D element model, in terms of Far-Field Vertical Gain as a function of an Elevation Angle plots. 5. Future research work and study for the next steps will be recommended.

Microwave Omnidirectional Angle-of-Arrival Measurement based on an Optical Ten-Port Receiver

A photonics-based scheme to measure microwave omnidirectional angle-of-arrival (AOA) is proposed. In the proposed system, an optical carrier is split into two branches. In one branch, the optical carrier is frequency-shifted by an acousto-optic modulator (AOM) and led to a Mach-Zehnder modulator (MZM) which is modulated by an echo signal from an antenna. In the other branch, a polarization-division-multiplexed MZM (PDM-MZM) is used to imprint two different echo signals received by another two antennas, respectively. Then, an optical bandpass filter is connected after each modulator to select one of the 1st-order sidebands. The selected sidebands are sent to an optical ten-port receiver, which is consisted of a dual-polarization 90-degree optical hybrid and four balanced photodetectors (BPDs). After processing the low-frequency signals from the orthogonal outputs of the ten-port optical receiver, the azimuth and altitude AOA of the received RF signal could be simultaneously obtained. In a proof-of-concept experiment, the measurement error of the altitude AOA is less than 1.63 within the angular range of -48.08~56.43, and the measurement error of the azimuth AOA is smaller than 3.09 when the angular range is from -68.35 to 64.65.

Physical layer security of cooperative wireless networks with RF energy harvesting

The paper derives the secrecy outage probability (SOP) and the probability of strictly positive secrecy capacity (SPSC) for wireless networks with energy harvesting. The Base Station (BS) uses the received RF signal to harvest energy. The harvested energy is used to transmit data to the receiver R. The eavesdropper E receives the signal from BS and try to decode it. We also derive the SPSC and SOP when there are K relay nodes. The best relay is selected to amplify the BS signal to the receiver R.

Optical Self-Interference Cancellation With Frequency Down-Conversion Based on Cascade Modulator

A novel approach to simultaneous radiofrequency self-interference cancellation (SIC) and frequency down-conversion in a unified system is proposed and demonstrated experimentally based on cascade Mach-Zehnder modulators (MZM). The local oscillator signal is injected into the MZM1, whereas the received RF signal and the reference signal are fed into MZM2 and MZM3. After photoelectrical conversion by a balanced photodetector, the desired intermediate frequency signal with SIC is obtained. The cancellation depth for the single frequency SIC with frequency down-conversion is around 38 dB, and that for a wideband signal is around 19 dB. No electrical delay and attenuation are used in the proposed system, so it can potentially reach a wider frequency band and a higher cancellation depth.