Nonlinear Radio Frequency Research Articles

Nonlinear RF impairments modeling with OFDM symbol-based parallel Wiener–Hammerstein structure

In the paper, a novel orthogonal frequency division multiplexing (OFDM) symbol-based parallel Wiener–Hammerstein structure is proposed to deal with the problem of nonlinear radio frequency (RF) impairments modeling for a cyclic prefix OFDM (CP-OFDM) waveform in telecommunication systems. The aforementioned structure is an equivalent linear-in-parameters representation of the parallel Wiener–Hammerstein structure in the considered problem. The structure is formally derived enabling the usage of identification algorithms compared with the artificial neural network (ANN) approach. The solution is compliant with current telecommunication standards.

Efficient Constant Envelope Precoding for Massive MU-MIMO Downlink via Majorization-Minimization Method.

The practical implementation of massive multi-user multi-input-multi-output (MU-MIMO) downlink communication systems power amplifiers that are energy efficient; otherwise, the power consumption of the base station (BS) will be prohibitive. Constant envelope (CE) precoding is gaining increasing interest for its capability to utilize low-cost, high-efficiency nonlinear radio frequency amplifiers. Our work focuses on the topic of CE precoding in massive MU-MIMO systems and presents an efficient CE precoding algorithm. This algorithm uses an alternating minimization (AltMin) framework to optimize the CE precoded signal and precoding factor, aiming to minimize the difference between the received signal and the transmit symbol. For the optimization of the CE precoded signal, we provide a powerful approach that integrates the majorization-minimization (MM) method and the fast iterative shrinkage-thresholding (FISTA) method. This algorithm combines the characteristics of the massive MU-MIMO channel with the second-order Taylor expansion to construct the surrogate function in the MM method, in which minimizing this surrogate function is the worst-case of the system. Specifically, we expand the suggested CE precoding algorithm to involve the discrete constant envelope (DCE) precoding case. In addition, we thoroughly examine the exact property, convergence, and computational complexity of the proposed algorithm. Simulation results demonstrate that the proposed CE precoding algorithm can achievean uncoded biterror rate (BER) performance gain of roughly 1dB compared to the existing CE precoding algorithm and has an acceptable computational complexity. This performance advantage also exists when it comes to DCE precoding.

Analysis of a Graphene FET-Based Frequency Doubler for Combined Sensing and Modulation through Compact Model Simulation

The ambipolar conduction property of graphene field-effect transistors (GFETs) and the inherent square-like dependence of the drain current on the gate voltage, enable the development of single-device architectures for analog nonlinear radiofrequency (RF) circuits. The use of GFETs in novel RF component topologies allows leveraging graphene’s attractive thermal and mechanical properties to improve the miniaturization and weight reduction of electronic components. These features are specifically appealing for integrated sensing, modulation, and transmission systems. However, given the innovative nature of emerging graphene-based technology, a complete performance analysis of any novel electronic component is essential for customizing the operating conditions accordingly. This paper presents a comprehensive circuital analysis of a GFET-based frequency doubler, exploiting a compact model for GFET circuit simulation to assess the device’s performance parameters, including power conversion gain bandwidth and saturation. The performed analysis proposes to support the design of GFET-based harmonic transponders, offering integrated sensing and signal manipulation capabilities.

Payload symbol-based nonlinear RF fingerprint for wireless QPSK-OFDM devices

Radio Frequency (RF) fingerprinting is one physical-layer authentication method for wireless communication, which uses the unique hardware characteristic of the transmitter to identify its true identity. To improve the performance of RF Fingerprint (RFF) based on preamble with fixed duration, a nonlinear RF fingerprinting method based on payload symbols is proposed for the wireless OFDM communication with the bit mapping scheme of QPSK. The wireless communication system is modeled as a Hammerstein system containing the nonlinear transmitter and multipath fading channel. A parameter separation technique based on orthogonal polynomial is presented for the estimation of the parameters of the Hammerstein system. The Hammerstein system parameter separation technique is firstly used to estimate the linear parameter with the training signal, which is used to compensate the adverse effect of the linear channel for the demodulation of the successive payload symbols. The demodulated payload symbols are further used to estimate the nonlinear coefficients of the transmitter with the Hammerstein system parameter separation technique again, which is used as the novel RFF for the authentication of the QPSK-OFDM device. Numerical simulations have verified the proposed method, which can also be extended to the OFDM signals with other bit mapping schemes.

Dominant andreev reflection through nonlinear radio-frequency transport

It is found that Andreev reflection provides a deterministic teleportation process at an ideal normal-superconductor interface, making it behave like an information mirror. However, it is challenging to control the Andreev reflection in a spatially-separated junction due to the mode mixing at the interface. We theoretically propose the laser-induced Andreev reflection between two-component Fermi superfluid and normal states without mode mixing via spatially-uniform Rabi couplings. By analyzing the tunneling current up to the fourth order, we find that the Andreev current exhibits unconventional non-Ohmic transport at zero temperature. The Andreev current gives the only contribution in the synthetic junction system at zero detunings regardless of the ratio of the chemical potential bias to the superfluid gap, which is in sharp contrast to that in conventional junctions. Our result may give a potential impact on theoretical and experimental study of quantum many-body phenomena, and also pave a way for understanding the black hole information paradox through the Andreev reflection as a quantum-information mirror.

Magnetic potential based formulation for linear and non-linear 3D RF sheath simulation

This paper reports a new numerical scheme to simulate the radio-frequency (RF) induced RF sheath, which is suitable for a large 3D simulation. In the RF sheath boundary model, the tangential component of the electric field () is given by the gradient of a scalar electric field potential. We introduce two additional scalar potentials for the tangential components of the magnetic field, which effectively impose the normal electric displacement (D n ) on the plasma sheath boundary condition via in-homogeneous Neumann boundary condition and constrain the tangential electric field on the surface as curl-free (). In our approach, the non-linear sheath impedance is formulated as a natural extension of the large thickness (or asymptotic) sheath limit (), allowing for handling both asymptotic and non-linear regimes seamlessly. The new scheme is implemented using the Petra-M finite element method analysis framework and is verified with simulations in the literature. The significance of non-linearity is discussed in various plasma conditions. An application of this scheme to asymptotic RF sheath simulation on the WEST ICRF antenna side limiters is also discussed.

Design of RF Frontend Unit to Avoid Intermodulation Using Arduino Uno

Designing a Radio Frequency (RF) front end is vastly realized for determining the level of integration that is required in the signal chain inside the receivers to be idealistic. The receivers is susceptible to harmful intermodulation due to nonlinear RF front ends. In this paper, intermodulation distortion is avoided by a selective prototype hardware design of RF fort end which is connected with the Arduino Uno for controlling the power levels. The measurements are tested out as a result of injecting a signals within x-band frequencies and chosen different power levels are assumed. These measurements is revealed an accepted results for the intermodulation avoidance.

Modeling inductive radio frequency coupling in powerful negative hydrogen ion sources: validating a self-consistent fluid model

Radio frequency (RF) negative hydrogen ion sources utilized in fusion and for accelerators use inductively coupled plasmas, which are operated at a low driving frequency, high power densities and gas pressures in the order of 1 MHz, 10 W cm−3 and 1 Pa, respectively. In this work a numerical fluid model is developed for a self-consistent description of the RF power coupling in these discharges. After validating the RF power coupling mechanism, such a model is a valuable tool for the optimization of RF power coupling and hence can help to increase the efficiency and reliability of RF ion sources. The model validation is achieved using measurements from the ITER RF prototype ion source. Steady state numerical solutions are obtained for the first time, where all modeled trends fit well. Remaining systematic quantitative differences could be caused by 3D effects such as highly non-uniform magnetic fields that cannot be captured in the current model formulation, which is 2D cylindrically symmetric. The coupling between the RF fields and the electrons is realized in the electron momentum transport equation, where approximations consistent with the operating regime of RF ion sources are applied. Here large magnetic RF fields lead to a plasma compression by the nonlinear RF Lorentz force. Using a local approximation for the electron viscosity, it is found that increased diffusion of the RF current density mitigates the compression. Navier–Stokes equations for the neutral atoms and molecules are used to capture neutral depletion. In this way it is shown that at high powers neutral depletion has a large impact on the power coupling via the viscosity of the electrons. The application of the self-consistent model for optimization of the RF power coupling will be described in a forthcoming paper.

Nonlinear Dynamic RF System Characterization: Envelope Intermodulation Distortion Profiles—A Noise Power Ratio-Based Approach

As radio frequency (RF) applications occupy larger bandwidths, nonlinear dynamics become nonnegligible. This work presents a theoretical framework capable of quantifying the impacts of nonlinear dynamic effects on RF systems through the observation of intermodulation distortion (IMD) profiles produced under multitone excitation. This framework defines static reference profiles and quantifies inband nonlinear dynamic effects as the error between the measured and reference profiles. This analysis demonstrates that classic linearity metrics, such as noise power ratio (NPR), adjacent-channel power ratio, and cochannel power ratio, do not have sufficient frequency resolution to reliably evaluate the impacts of nonlinear dynamics manifested in the IMD profiles produced by broadband RF systems. These observations result in a list of general characterization guidelines to overcome the limitations of classical linearity metrics in the assessment of nonlinear dynamics and the proposal and experimental validation of a novel method, swept-tone NPR, for the characterization of IMD profiles affected by nonlinear dynamic effects. Beyond this, the classic nonlinear dynamic mechanism, responsible for IMD asymmetry, is analyzed under multitone excitation at the system level for the first time, and the limitations of mechanism-based IMD analysis in the presence of nonlinear dynamic effects are evidenced with theoretical examples.

Nonlinear Dynamics of Topological Ferromagnetic Textures for Frequency Multiplication

We propose that the nonlinear radio-frequency dynamics and nanoscale size of topological magnetic structures associated with their well-defined internal modes advocate their use as in materio scalable frequency multipliers for spintronic systems. Frequency multipliers allow for frequency conversion between input and output frequencies, and thereby significantly increase the range of controllably accessible frequencies. In particular, we explore the excitation of eigenmodes of topological magnetic textures by fractions of the corresponding eigenfrequencies. We show via micromagnetic simulations that low-frequency perturbations to the system can efficiently excite bound modes with a higher amplitude. For example, we excite the eigenmodes of isolated ferromagnetic skyrmions by applying half, a third, and a quarter of the corresponding eigenfrequency. We predict that frequency multiplication via magnetic structures is a general phenomenon that is independent of the particular properties of the magnetic texture and works for magnetic vortices, droplets, and other topological textures.

Self-consistent fluid model for simulating power coupling in hydrogen ICPs at 1 MHz including the nonlinear RF Lorentz force

Radio frequency (RF) power coupling in inductively coupled plasmas is investigated numerically using a self-consistent fluid model. Hydrogen discharges are simulated at pressures from 0.3–10 Pa and at RF powers of around 1 kW. At the low excitation frequency of 1 MHz a high magnetic RF field of around 30 G is generated by the RF coil, meaning that discharges at low pressures are in the nonlinear skin effect regime. Therefore, a description of the RF power coupling by simple collisional Joule heating is not appropriate. Moreover, models that account for collisionless heating by means of a stochastic collision frequency or as diffusion of the RF current density (as is state of the art for discharges operated in the anomalous skin effect regime at higher frequencies of e.g. 13.56 MHz) are incapable of describing the RF power coupling in the nonlinear skin effect regime properly. This is due to their total neglect or simplified treatment of the RF Lorentz force. Instead, this work demonstrates that the RF power coupling mechanism for discharges operating at low RF in the nonlinear skin effect regime can be described by an electron momentum balance retaining the nonlinear RF Lorentz force as well as electron inertia and advection. The crucial role of the RF Lorentz force in generating the RF plasma current density and thus in shaping the plasma parameter profiles is validated successfully with experimentally obtained electrical and spatially resolved plasma parameters for pressures as low as 0.5 Pa. Below this pressure the results obtained from the model and the ones from the experiment diverge. Most likely this is caused by a sudden change in the electron distribution function at the lowest pressures.

On outage analysis of nonlinear radio frequency energy harvesting based cooperative communication in cognitive radio network

AbstractThe aim of this article is to investigate the outage performance of nonlinear radio frequency (RF) energy harvesting (EH) enabled decode‐and‐forward relay assisted cognitive radio network. Here, secondary transmitter (ST) can access the licensed spectrum of primary users (PUs) to send its message toward the secondary receiver and at the same time, it can support the primary communication by performing like a relay node. ST can harvest the energy from the received RF signal of primary transmitter to execute its necessary activities. The closed‐form expressions of PU and secondary user outage are derived to measure the end‐to‐end reliability of the system. The accuracy of derived expressions are also validated through the observation of simulation results. In addition to that, the performance of nonlinear EH model is also compared with respect to linear EH model.

Classification of benign and malignant breast masses using entropy from nonlinear ultrasound radiofrequency signal

In this paper the classification of benign and malignant breast masses is investigated by using the entropy of nonlinear ultrasound radio frequency (RF) signal. The parameters (entropy and weighted entropy) derived from the nonlinear ultrasound RF signal and the conventional ultrasound parameters (image grayscale, aspect ratio, irregularity, breast mass size, and depth) are extracted from 306 image samples (158 benign and 148 malignant); t-test and linear-discriminant classifier (LDC) are used to test the distinction between benign and malignant breast masses by each parameter; furthermore the effective parameters are combined to classify benign and malignant breast masses. The results show that except the image grayscale, the other parameters are significantly different between benign and malignant breast masses. Multi-parameter combined with support vector machine (SVM) is used to classify breast masses as benign and malignant. The accuracy is 81.4%, the sensitivity is 78.4%, and the specificity is 84.2%. The present work shows that the combination of the nonlinear entropy of ultrasound RF signal and traditional ultrasound parameters can more effectively characterize the benign and malignant breast masses. The entropy of nonlinear ultrasound RF signal can become a new parameter for characterizing the benign and malignant breast masses.

On Maximizing Max–Min Source Rate in Wireless-Powered Internet of Things

Future Internet-of-Things (IoT) networks will consist of radio-frequency (RF) energy harvesting devices that are charged by solar-powered power beacons (PBs). To this end, this article aims to maximize the minimum data rate of devices acting as sources operating in a multihop IoT network. The main problem is to decide the amount of energy delivered by solar-powered PBs, routing of data from each source, and link scheduling, which determines the capacity of links. To this end, we make two contributions. First, we present a linear program (LP) to optimize the max–min rate of sources. Our LP considers nonlinear RF conversion at devices, energy storage loss at devices due to the imperfect battery, and time-varying channel quality, which affect the amount of energy harvested by devices. The second contribution is a novel distributed protocol called distributed max–min rate allocation (D-MRA), whereby devices only need local information, such as their battery and data buffer state to make decisions. Our results show that the max–min rate of D-MRA is 58.25% that of LP, which requires global information, in all tested cases.

Time-Division Energy Beamforming for Multiuser Wireless Power Transfer With Non-Linear Energy Harvesting

Energy beamforming has emerged as a promising technique for enhancing the energy transfer efficiency of radio-frequency (RF) enabled wireless power transfer (WPT). However, the performance of conventional energy beamforming may seriously degrade due to the non-linear RF to direct current (DC) conversion at energy receivers (ERs). To tackle this issue, this letter proposes a new time-division energy beamforming scheme, in which different energy beamforming matrices (of high ranks in general) are time shared to exploit the “convex-concave” shape of the RF-DC power relation at ERs. In particular, we maximize the minimum harvested DC energy among all ERs, by jointly optimizing the energy beamforming matrices and the corresponding time allocation subject to a given charging time duration (e.g., a second). To solve the formulated non-convex min-DC-energy maximization problem, we propose an efficient solution by using the techniques of alternating optimization and successive convex approximation (SCA). Numerical results show that the proposed time-division energy beamforming design indeed outperforms the conventional multi-beam and time-division-multiple-access (TDMA)-based energy transmissions.

Passive Intermodulation in Simultaneous Transmit–Receive Systems: Modeling and Digital Cancellation Methods

This article presents novel solutions for suppressing passive intermodulation (PIM) distortion in frequency-division duplexing (FDD)-based radio transceivers, stemming from nonlinear radio frequency (RF) components and simultaneous transmission and reception, with special emphasis on modern carrier aggregation networks. With certain transmission band combinations in, e.g., long-term evolution (LTE) or the emerging 5G new radio (NR) mobile radio systems, the nonlinear distortion produced by the passive components of the transceiver RF front end can result in intermodulation (IM) distortion that falls within one of the configured reception bands. While the traditional solution to mitigate this problem is to reduce the transmit power, we take an alternative approach and seek to cancel such PIM in the transceiver digital front end by using the original transmit data as a reference. To generate as accurate cancellation signal as possible, we derive different advanced signal models for the observable IM distortion at own receiver band that incorporates also the power amplifier (PA) nonlinearities, together with the passive component nonlinearities and the frequency-selective responses of the duplex filters. The performance and the processing complexity of the devised digital cancellation and parameter estimation solutions are evaluated with real-life RF measurements, where an actual LTE-Advanced user equipment (UE)-type transceiver system is utilized. The obtained results show that the proposed cancellers are implementation feasible and can suppress the self-interference by over 20 dB, canceling the distortion nearly perfectly up to UE transmit powers of +24 dBm. The results also indicate that, in many cases, it is necessary to model the nonlinear distortion effects produced by the PAs, even if the individual component carriers are combined after the amplification stage.

A Zero-Power Ubiquitous Wireless Liquid-Level Sensor Based on Microfluidic-Integrated Microstrip Antenna

Harmonic transponder sensors, receiving radio-frequency (RF) signal and converting it to a modulated second harmonic, have been demonstrated to be effective for signal interrogation in environments with strong clutters. Here, we propose a compact dual-resonance microstrip antenna consisting of an elliptical patch loaded with shorting pins. Such an antenna utilizes the TM e 110 resonant mode to intercept the perpendicularly-polarized fundamental tone (2.86 GHz) and uses the TM o 110 resonant mode to retransmits the parallelly-polarized second harmonic (5.72 GHz). Moreover, we have developed a harmonic-based wireless liquid sensor comprising the proposed antenna and a micromachined liquid channel. Our measurement results show that even in the noisy environment, the second harmonic strength can precisely indicate the dielectric property of liquid filled in the microfluidic tank (e.g., acetone-water mixtures with various concentrations). However, a similar setup without frequency and polarization modulations (i.e., linear and passive backscatter tag) fails to provide a sensitive and quantitative measurement of liquid property. The proposed low-profile dual-resonance antenna with sensing capability will pave the way for the development of harmonic sensors and nonlinear radio-frequency identification (RFID) tags.

Deep Reservoir Computing Meets 5G MIMO-OFDM Systems in Symbol Detection

Conventional reservoir computing (RC) is a shallow recurrent neural network (RNN) with fixed high dimensional hidden dynamics and one trainable output layer. It has the nice feature of requiring limited training which is critical for certain applications where training data is extremely limited and costly to obtain. In this paper, we consider two ways to extend the shallow architecture to deep RC to improve the performance without sacrificing the underlying benefit: (1) Extend the output layer to a three layer structure which promotes a joint time-frequency processing to neuron states; (2) Sequentially stack RCs to form a deep neural network. Using the new structure of the deep RC we redesign the physical layer receiver for multiple-input multiple-output with orthogonal frequency division multiplexing (MIMO-OFDM) signals since MIMO-OFDM is a key enabling technology in the 5th generation (5G) cellular network. The combination of RNN dynamics and the time-frequency structure of MIMO-OFDM signals allows deep RC to handle miscellaneous interference in nonlinear MIMO-OFDM channels to achieve improved performance compared to existing techniques. Meanwhile, rather than deep feedforward neural networks which rely on a massive amount of training, our introduced deep RC framework can provide a decent generalization performance using the same amount of pilots as conventional model-based methods in 5G systems. Numerical experiments show that the deep RC based receiver can offer a faster learning convergence and effectively mitigate unknown non-linear radio frequency (RF) distortion yielding twenty percent gain in terms of bit error rate (BER) over the shallow RC structure.

Photonic Assisted Radio-Frequency Interference Mitigation

Rapidly evolving technologies for photonic interference mitigation are surveyed and discussed. The techniques are categorized into photonic radio-frequency (RF) filters, photonic RF cancellers, and photonic RF front ends. Analysis is presented on an approach that combines linear and non-linear photonic RF front ends. An argument is presented for cooperative photonic, analog-electronic, and digital-electronic techniques.

Conditional Capacity and Transmit Signal Design for SWIPT Systems With Multiple Nonlinear Energy Harvesting Receivers

In this paper, we study information-theoretic limits for simultaneous wireless information and power transfer (SWIPT) systems employing practical nonlinear radio frequency (RF) energy harvesting (EH) receivers (Rxs). In particular, we consider a SWIPT system with one transmitter that broadcasts a common signal to an information decoding (ID) Rx and multiple EH Rxs. Owing to the nonlinearity of the EH Rxs’ circuitry, the efficiency of wireless power transfer depends on the waveform of the transmitted signal. We aim to answer the following fundamental question: What is the optimal input distribution of the transmit signal waveform that maximizes the information transfer rate at the ID Rx conditioned on individual minimum required direct-current (DC) powers to be harvested at the EH Rxs? Specifically, we study the conditional capacity problem of a SWIPT system impaired by additive white Gaussian noise subject to average-power (AP) and peak-power (PP) constraints at the transmitter and nonlinear EH constraints at the EH Rxs. To this end, we develop a novel nonlinear EH model that captures the saturation of the harvested DC power by taking into account not only the forward current of the rectifying diode but also the reverse breakdown current. Then, we derive a novel semi-closed-form expression for the harvested DC power, which simplifies to closed form for low input RF powers. The derived analytical expressions are shown to closely match circuit simulation results. We solve the conditional capacity problem for real- and complex-valued signalling and prove that the optimal input distribution that maximizes the rate-energy (R-E) region is unique and discrete with a finite number of mass points. Furthermore, we show that, for the considered nonlinear EH model and a given AP constraint, the boundary of the R-E region saturates for high PP constraints due to the saturation of the harvested DC power for high input RF powers. In addition, we devise a suboptimal input distribution whose R-E tradeoff performance is close to optimal. All theoretical findings are verified by numerical evaluations.