Nonlinear Power Amplifier Research Articles

B-Spline Neural Network Assisted Space-Time Equalization for Single-Carrier Multiuser Nonlinear Frequency-Selective MIMO Uplink

This paper designs a nonlinear space-time equalizer based on B-spline neural network (BSNN) for the singlecarrier high-throughput multiuser frequency-selective multipleinput multiple-output (MIMO) nonlinear uplink. Specifically, based on a BSNN parametrization of the nonlinear high power amplifiers (NHPAs) at mobile terminals’ transmitters, a novel nonlinear identification scheme is developed to estimate the nonlinear dispersive MIMO uplink channel, which includes the BSNN models for the NHPAs at transmitters as well as the frequency-selective MIMO channel impulse response (CIR) matrix. Furthermore, the BSNN inverse models of the NHPAs are also estimated in closed-form. This allows the base station to implement nonlinear multiuser detection effectively using the space-time equalization (STE) based on the estimated frequencyselective MIMO CIR matrix and followed by compensating for the nonlinear distortion of the transmitters’ NHPAs based on the estimated BSNN inverse models. Simulation results are utilized to demonstrate the superior bit error rate performance of our nonlinear STE approach for single-carrier highthroughput multiuser nonlinear frequency-selective MIMO uplink.

A New Approach to Improve the Performance of OFDM Signal for 6G Communication

The orthogonal frequency division multiplexing is a very efficient modulation technique that can achieve very high throughput by transmitting many carriers simultaneously and it is spectrally efficient because of the proximity of the subcarriers. OFDM is used in 5G communication for higher data transmission. 6th generation communication also demands OFDM, since it is more spectrally efficient and suitable for high data transmission. The drawback of the OFDM includes peak to average power ratio and sensitivity to carrier offsets and drifts. The usage of a non-linear power amplifier causes the signal spreading and leads to inter-modulation and signal constellation distortion. These two distortions have an impact on the signalto-noise ratio and hence reduce the efficiency. The methods used to reduce PAPR are clipping and filtering, selective mapping, partial transmit sequence, tone reservation, and injection and non-linear commanding. The drawbacks of the above methods are computational complexity, spectrum inefficiency, increase in bit error rate and PAPR rate. In this work, three effective methods are discussed and compared to improve the performance parameters. These are adaptive peak window method based on harmonize clipping, harmonics kernel adaptive filter and Slepian-based flat-top window techniques are presented to reduce the BER, PAPR, and CCDF to improve the signal-to-noise of the system. This window technique averages out the noise spread out in the spectrum and thus reduces the signal loss by minimizing peak to average power ratio. The results are analyzed and compared with the existing conventional methods. Finally, the reductions in PAPR, BER and CCDF obtained are discussed in the results and comparison section. The proposed work has a higher signal-to-noise ratio than the conventional methods.

A Survey on Robust Modulation Requirements for the Next Generation Personal Satellite Communications

The unrelenting technological advancement in the generation of wireless networks in recent years has awakened the motion concerning the inclusion of satellites in personal communications. Leveraging their ability to provide wide coverage, uniform services, wide bandwidth, and so forth, Satellite systems will be expected to co-exist with the current state-of-the-art infrastructure of terrestrial networks. Herein, we present a comparative study on the representative digital modulation techniques for use in personal satellite communications. We discuss the advantages and limitations of different modulation techniques, such as phase shift keying, continuous phase modulation, amplitude phase shift keying, and quadrature amplitude modulation. We also perform evaluations based on spectral efficiency, power efficiency, modulation error ratio, error vector magnitude, and peak-to-average power ratio in the presence of high power amplifier nonlinearities and Doppler effects. Comparisons in the form of tables, illustrations, and curves are also presented. In correspondence to the comparisons made basing on the aforementioned metrics, we conclude that continuous phase modulation is the best candidate modulation scheme for personal satellite communications since it outperforms other schemes by compromising the trade-off between power efficiency, bandwidth efficiency, and immunity to errors. We further present open issues that would reinforce personal satellite communications in terms of reliability, throughput and latency, other than power and spectral efficiency, if combined with appropriate modulation schemes.

A Novel Autoregressive Spectral Estimation-Based Neural Network Crest Factor Reduction Structure in Power Amplifiers of 5G Systems in Sandstorm Environment

In this paper, an autoregressive spectral estimation using a multilayered neural network is proposed to reduce the nonlinearities of 5G MIMO power amplifiers and increase the signal-transmitting qualities. The proposed method adopts the two-sided doubly exponential lattice algorithm to achieve the most suitable estimation for in-band compensation. Also, based on the iterative learning control method, a novel crest factor reduction digital predistortion is combined with the multilayered neural network. Based on the results, the proposed algorithm has increased the linearity and stability of the PA performance. The proposed method can improve the robustness of 5G MIMO wireless communication systems.

Impact of HPA nonlinearity on the performance of power domain OFDM-NOMA system

Non-orthogonal multiple access (NOMA) is expected to be used in beyond fifth-generation (B5G) and sixth-generation (6G) mobile networks to support ultra-massive connectivity. Since the two preceding mobile networks generations used orthogonal frequency division multiplexing (OFDM), NOMA is expected to be combined with OFDM. Unfortunately, the OFDM signal suffers from a high peak to average power ratio (PAPR) that limits its performance as it passes through the nonlinear high power amplifier (HPA). In literature, few works have studied the effect of nonlinear distortion on OFDM-NOMA. Furthermore, the HPA models used in previous works to describe the impact of nonlinear distortion on OFDM-NOMA in downlink (DL) were impractical or inaccurate. In contrast, this work uses the well-known soft limiter (SL) model with input back-off (IBO) as a practical controlling parameter. Also, instead of investigating the effect of nonlinear distortion on OFDM-NOMA in DL only, this work investigated this effect in both DL and uplink (UL). In particular, during this work, the performance of the OFDM-NOMA system in the presence of nonlinear distortion in both UL and DL is investigated in terms of users’ achievable data rate, sum rate capacity, system fairness, and the bit error rate (BER) of each user. Results showed that, in DL, the NU is the most affected by the nonlinear distortion, while, in UL, the nonlinear distortion caused by the NU’s HPA is more severe than the nonlinear distortion caused by other users.

A modified broadband weighted magnitude‐selective behavioral model for digital predistortion of radio frequency power amplifiers

With the increasing demand for large signal bandwidth in communication systems, the complexity of the behavioral model of power amplifier (PA) will also increase. In this paper, a modified weighted magnitude-selective model based on magnitude-selective affine (MSA) function based model and weighted memory polynomial model is proposed to ensure low complexity and good modeling performance under broadband signal excitation. This model is constructed by using the power-dependent weighted function instead of the sum of multiple MSA functions in MSA. It can not only be used to solve the nonlinearity of PA excited by large bandwidth signal but also reducing the model coefficients without affecting the modeling performance makes the digital predistortion of large bandwidth signals more simple and effective. In this paper, a 100 MHz broadband signal is used for simulation and experiment on a wideband PA. The results show that for the same performance the WMA model required approximately 80% less coefficients.

SER optimization in transparent OFDM relay systems in the presence of dual nonlinearity

Transparent relay is a frequently used solution to enhance signal coverage with low implementation cost. However, the nonlinear distortion caused by cascaded amplification in the relay systems degenerates the system performance, increases the analysis complexity, and brings challenges to the system-level optimization. This paper analytically studies the system-level optimization of symbol error rate (SER) performance in nonlinear OFDM relay systems, where both power amplifiers (PAs) in transmitter and transponder show clear nonlinearity. Firstly, the system SER is expressed as a function of receiver signal-to-noise ratio (SNR), and the latter is further simplified to a polynomial-based function of PA parameters and system operating points. Secondly, the asymptotic behavior and Hessian Matrix (HM) of the receiver SNR are analyzed, and it is found that the SNR has an upper bound when dual nonlinearity of the transmitter PA and transponder PA are considered. Thirdly, this paper derives the analytical expressions of the optimal PA operating points corresponding to the optimal SER performance for the first time. Finally, the expression of the SNR upper bound is presented, and the derived functions are found to have the merit of low complexity, which suits the application in transparent relay systems with limited computational resources.

Inverse Covariance Matrix Estimation for Low-Complexity Closed-Loop DPD Systems: Methods and Performance

In this article, we study closed-loop digital predistortion (DPD) systems and associated learning algorithms. Specifically, we propose various low-complexity approaches to estimate and manipulate the inverse of the input data covariance matrix (CM) and combine them with the so-called self-orthogonalized (SO) learning rule. The inherent simplicity of the SO algorithm, combined with the proposed solutions, allows for remarkably reduced complexity in the DPD system while maintaining similar linearization performance compared to other state-of-the-art methods. This is demonstrated with thorough over-the-air (OTA) mmW measurement results at 28 GHz, incorporating a state-of-the-art 64-element active antenna array, and very wide channel bandwidths up to 800 MHz. In addition, complexity analyses are carried out, which together with the measured linearization performance demonstrates favorable performance–complexity tradeoffs in linearizing mmW active array transmitters through the proposed solutions. The techniques can find application in systems where the power amplifier (PA) nonlinearities are time-varying and thus frequent or even constant updating of the DPD is required, good examples being mmW adaptive antenna arrays as well as terminal transmitters in 5G and beyond networks.

공통 소스 트랜지스터의 Self-Body-Biasing을 통해 선형성이 향상된 2.45 GHz CMOS 전력증폭기의 설계

This study introduces the design of an RF CMOS power amplifier based on a cascode powercell. self-body-biasing (SBB) of common source (CS) transistors (TRs) was proposed to improve the nonlinearity of power amplifiers. Accordingly, an analysis of the linearization principle of SBB was performed through simulation. The SBB technique is configured by inserting a 4 kΩ resistor between the body and the drain of the CS TRs. Accordingly, using the SBB to the CS TRs could achieve the effect of reducing the third-order intermodulation distortions (IMD3) by changing the third-order transconductance (gm3). Moreover, an effect of reducing AM-PM distortions could be achieved by securing a voltage condition in which the CG TRs could operate in a saturation region, which reduces the variation of parasitic capacitances at the output terminal.

Power amplifier behavioral modeling based on LaguerrePolar‐Volterraseries with independent truncations

This article proposes an approach that modifies the Polar-Volterra series expanded by a set of Laguerre Orthonormal Basis Functions and the Polar-Volterra series using independent truncation techniques to significantly reduce the amount of parameters, where the resulting models reproduce the distortions of the nonlinearities of a radio frequency power amplifier (RF PA). An RF PA GaN HEMT class AB, stimulated by a wave centered at 900 MHz modulated by two 3GPP WCDMA envelope signals, each having a bandwidth of 3.84 MHz and shifted by 5 MHz, was used. A comparison of several models showed that the two proposed models, both containing a larger number of independent truncation factors, can provide a reduction over 50% in the number of generated coefficients, reaching a maximum of 84%. In another comparison with the other models, the modified Polar-Volterra series expanded by a set of Laguerre functions significantly improved the modeling accuracy, quantified by improvements of normalized mean square error of up to 6.51 dB.

Statistical Modeling and Analysis of Power Amplifier Nonlinearities in Communication Systems

Hardware impairments in general and amplifier nonlinearity in particular severely limit the performance of communication links. This paper analytically provides statistical results on how a nonlinear amplifier affects the quality of signals in communication systems. In particular, we propose a statistical model that describes the nonlinear distortion as a function of the input signal’s average and instantaneous power and captures the pulse-shaping and matched filters’ effects. We show through simulations and complementary measurements that the proposed model can provide an authentic connection between the communication system parameters, power amplifier nonlinearity characteristics, and the communication system performance. It serves not only as a reliable model for nonlinear distortion analysis but also as a design tool that allows optimization of signal and filter characteristics with respect to nonlinear distortion.

Assessing Power Amplifier Impairments and Digital Predistortion on Radar Waveforms for Spectral Coexistence

This article deals with the effects of power amplifiers (PAs) on radar waveforms designed to ensure spectral compatibility with other radio frequency wireless systems cohabitating in the same frequency band. To this end, a specific hardware-in-the-loop testbed composed of a personal computer, an arbitrary waveform generator, a nonlinear PA, and a signal analyzer is designed. It allows to gather measurements of the amplified signal and to grasp unwanted modifications of its spectral features due to the PA nonlinear distortion. Besides, it permits a quantitative assessment of the discrepancies between the nominal and the actual interference power injected by the radar in the shared frequency bandwidths. To alleviate the spectral distortions induced by the PA and improve spectral coexistence, the use of a digital predistortion (DPD) stage upstream the PA is investigated. Modeling techniques together with parameter inference are discussed and applied to the measured waveforms. The obtained experimental results highlight that pairing a suitable waveform design strategy with DPD processing represents a viable means to mitigate the PA distortions and to realize spectral coexistence.

Memory polynomial based support vector regression dynamic behavioral model for Doherty power amplifiers

AbstractIn this article, a novel behavior modeling methodology for radio frequency (RF) power amplifiers (PAs) is introduced. The model is targeted towards strongly nonlinear Doherty power amplifiers (DPAs), combining the memory polynomial (MP) topology with the existing support vector regression (SVR) algorithm. The resulting novel model, is termed the memory polynomial support vector regression (MP‐SVR) model. Experimental validation proceeds by applying the proposed modeling method to both two standard gallium nitride (GaN) DPA with different nonlinearity, as well as a multi‐transistor GaN DPA. Compared with traditional Volterra based models, the standard SVR model, the augmented SVR (ASVR) model and the new augmented SVR (NASVR) model, the proposed MP‐SVR model gives superior prediction accuracy in both cases. This shows the efficacy of the proposed modeling method.

Design of Multihop Communication Systems Under Hardware Manufacturing Defects and Self Interference

Most studies on multi-hop communication systems are actually based on the assumption that hardware parts are built with high quality transmit/receive radio frequency chains, which are expensive and power-hungry. In practice, low cost hardware components are employed, which are prone to hardware manufacturing defects (e.g., phase noise, nonlinear power amplifier, inphase/quadrature imbalance, nonlinear low noise amplifier and analog to digital converter impairments). This paper focuses on the design of the transmitter, relay stations (RSs) and receiver for multi-hop communication systems under hardware defects. This paper analyzes the hardware defects and their impacts on the performance of multi-hop communication system. In addition, the impact of self-interference at the RSs is considered. The effect of hardware defects is modeled using distortion noises. A closed-form expression for the signal to noise and distortion ratios (SNDRs) is mathematically derived, then the performance metrics (i.e., SNDR, outage probability (OP) and ergodic capacity) are calculated, accounting for hardware defects. In addition, exact form expression of the average bit error probability is derived. To facilitate comparison, performance metrics of the proposed multi-hop relaying system and ideal system are illustrated. We also propose a linear minimum mean square error (LMMSE) and self-interference cancellation technique to mitigate the hardware defects. The results reveal that hardware defects can degrade the system performance. In addition, SNDR ceiling is inversely proportional to the summation of the square of hardware defect lev el. Also, the proposed mitigation technique can enhance the system performance.

Iterative Equalization of STSK-Aided Single-Carrier Systems: Design and Analysis With Non-Ideal Power Amplifiers

A plethora of new applications will be enabled by next generation wireless networks. These demand sophisticated medium access control and physical layer protocols in order to fulfill the requirements in terms of spectral efficiency, bit error rate (BER), energy efficiency, reliability, and security, among others. This paper develops an advanced space-time multiple-input, multiple-output (MIMO) solution that builds on the concept of space-time shift keying (STSK) for single-carrier frequency domain equalization (SC-FDE). STSK-aided SC-FDE, or SSF, ensures space-time and frequency diversity in dispersive channels, but can only support suboptimal linear receiver schemes. We therefore introduce a turbo equalizer for SSF in frequency-selective multipath channels. It enables inter-symbol-interference cancellation by means of iterative space-time processing. We coin it the iterative space-time block equalizer (SSF-ISTBE). We provide the mathematical formulation for the proposed SSF-ISTBE framework in non-linear channel conditions. We demonstrate that the SSF-ISTBE achieves a substantial 4 dB gain in terms of BER over the linear minimum mean square error equalizer while significantly reducing the computational complexity of the optimal maximum likelihood SSF. When considering practical transceivers, in particular non-linear power amplifiers, the gain of the SSF-ISTBE becomes more prominent over state-of-the-art approaches, demonstrating its robustness against non-linear distortion.

Low Complexity Joint Impairment Mitigation of I/Q Modulator and PA Using Neural Networks

neural networks (NNs) for multiple hardware impairments mitigation of a realistic direct conversion transmitter are impractical due to high computational complexity. We propose two methods to reduce the complexity without significant performance penalty. First, propose a novel NN with shortcut connections, referred to as shortcut real-valued time-delay neural network (SVDEN), where trainable neuron-wise shortcut connections are added between the input and output layers. Second, we implement a NN pruning algorithm that gradually removes connections corresponding to minimal weight magnitudes in each layer. Simulation and experimental results show that SVDEN with pruning achieves better performance for compensating frequency-dependent quadrature imbalance and power amplifier nonlinearity than other NN-based and Volterra-based models, while requiring less or similar complexity.

A Low-Complexity Joint PAPR Reduction and Predistortion Based on Generalized Memory Polynomial Model

Digital predistortion (DPD) technique is an effective means to alleviate the nonlinearity of power amplifiers (PAs) and improve transmitter efficiency. However, for orthogonal frequency division multiplexing (OFDM) systems with a high peak-to-average power ratio (PAPR), the PAPR reduction needs to be deployed in combination with DPD, to maximize transmitter efficiency. The extra complexity caused by the introduction of PAPR reduction on the main road has become a non-negligible defect. To address this issue, this letter proposes a joint PAPR reduction and DPD model based on the generalized memory polynomial (GMP). To train the joint GMP model, this letter improves the ping-pong joint optimization (P2JO) approach under the offline case, to obtain accurate training data. The comparative experimental results based on 100-MHz Doherty PA show that the proposed joint model significantly reduces the model complexity on the main road, while ensuring adjacent channel power ratio (ACPR) and bit error rate (BER).

Energy-Efficient OFDM Radio Resource Allocation Optimization With Computational Awareness: A Survey

In this paper, we review radio resource optimization methods for energy-efficient wireless communication in links and networks using the Orthogonal Frequency Division Multiplexing (OFDM) and Orthogonal Frequency Division Multiple Access (OFDMA) techniques. We first consider the energy-efficiency metrics and optimization goals. We discuss the increasingly complex systems, starting from (i) a single OFDM link, (ii) an OFDMA single-hop network to (iii) multi-hop relay OFDMA interference networks. In each case, we elaborate on the transmission rate estimation, power consumption modelling, existing optimization constraints and the optimization solutions. Specifically, in the power-consumption modelling, we include the signal-processing (and related computing) power.We discuss the practicality of the considered solutions. We also touch upon the problem of nonlinear power amplifier characteristics (causing distortions typical for OFDM signals) to be taken into account for energy-efficient resource allocation. We discuss trade-offs and provide recommendations for future energy-efficient OFDM networks design. We also discuss the future works and challenges in the context of energy efficiency resource allocation for OFDM/OFDMA and their derivative techniques.We conclude that the presented design practices should include computational awareness in the networks to trade-off between information communication, information processing and the required network management energy-efficiency.

Digital Predistortion of Nonlinear Power Amplifier Based on Improved Spline Adaptive Filtering Method

To improve the modeling accuracy and digital predistortion compensation effect, this paper proposed a kind of polynomial based spline adaptive filter (SAF) power amplifier (PA) behavioral modeling method. The proposed model can solve the shortcomings of the traditional memory polynomial model (MP), such as higher nonlinear order, highly coefficient calculation difficulty, poor hardware stability, low modeling accuracy and poor digital predistortion compensation. Meanwhile, the proposed SAF based model can avoid the pseudo-inversion operation of the matrix when calculating the coefficients through the indirect learning structure, which can improve the compensation effect of digital predistortion. In order to compare the performance of the different models, the modeling processes of original filtering model, MP model and dynamic variation reduction (Dynamic Deviation Reduction, DDR) model based on SAF method (OSAF, MPSAF, DDRSAF) are presented respectively. The proposed models are verified by a class F PA, which are stimulated by a set of measured input and output data of an LTE signal with 20 MHz bandwidth. The measured results shows that compared with the conventional MP model, the proposed DDRSAF model presents the best model performance and improves the modeling accuracy by 6.6dB while maintaining the similar computational complexity, and the ACPR compensation effect increases by 19.58dB and 20.47dB respectively, which have the important significance for practical engineering application.

Deep Learning-Based Joint Optimization of Modulation and Power for Nonlinearity-Constrained System

For wireless communication systems with a long distance or severe interference, the insufficient transmit power limits the system performance. In this case, the maximum transmit power depends on the nonlinearity and the saturation region of the power amplifier (PA), which is referred to as a nonlinearity-constrained problem in this paper. To increase the transmit power as high as possible in a nonlinearity-constrained system, this paper proposes an autoencoder-based system to jointly optimize the modulation scheme and transmit power. The optimal solution can achieve a tradeoff between increasing the transmit power and reducing the nonlinear distortion. Meanwhile, the optimized signal constellation and the neural network-based receiver can effectively improve the capacity against nonlinear distortion. The simulation results indicate that the proposed method outperforms conventional methods in terms of symbol error rate (SER) and transmit power, and the SER of the proposed method is close to the SER lower bound of the nonlinear PA.