In-band Distortion Research Articles

In-Band Distortion Compensation for Peak Cancellation-Based PAPR Reduction in Massive MIMO-OFDM With Uniform Planar Array

In-Band Distortion Compensation for Peak Cancellation-Based PAPR Reduction in Massive MIMO-OFDM With Uniform Planar Array

Post-Processing of Iterative Estimation and Cancellation Scheme for Clipping Noise in OFDM Systems

Clipping is an efficient and simple method that can reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. However, clipping causes in-band distortion referred to as clipping noise. To resolve this problem, a novel iterative estimation and cancellation (IEC) scheme for clipping noise is one of the most popular schemes because it can significantly improve the performance of clipped OFDM systems. However, IEC exploits detected symbols at the receiver to estimate the clipping noise in principle and the detected symbols are not the sufficient statistic in terms of estimation theory. In this paper, we propose the post-processing technique of IEC, which fully exploits given sufficient statistic at the receiver and thus further enhances the performance of a clipped OFDM system as verified by simulations.

Out-of-Band Digital Predistortion for Power Amplifiers With Strong Nonlinearity

Conventional full-band digital predistortion (DPD) suppresses the inband (IB) distortion to improve the error vector magnitude (EVM) performance and simultaneously suppresses the out-of-band (OOB) distortion to reduce the adjacent-channel interference. However, its performance is very limited when the nonlinearity is strong, especially in terms of suppressing the OOB distortion. This paper proposes an OOB DPD scheme for strong nonlinearity with a special focus on suppressing the OOB distortion to reduce the adjacent-channel interference. The proposed OOB DPD is featured by specifying an arbitrary OOB-distortion band for linearization and controlling the improvement level of EVM performance. Experiments demonstrate that the proposed OOB DPD can achieve superior performance in suppressing the OOB distortion when the nonlinearity is strong. We also present analyses to show that in strong nonlinearity cases with high compression, focusing on suppressing the OOB distortion at a specific band is an effective way to improve the suppression level of the target distortion. The proposed OOB DPD can further improve the transmission power under the assurance of low adjacent-channel interference. It can be applied in communications with urgent needs in high transmission power, high efficiency, and low adjacent-channel interference, such as military communications that usually adopt low-order modulations with low EVM requirements.

Mitigating Clipping Distortion in Multicarrier Transmissions Using Tensor-Train Deep Neural Networks

Multicarrier transmissions, such as orthogonal frequency/chirp division multiplexing (OF/CDM), offer high spectral efficiency and low complexity equalization in multipath fading channels at the cost of high peak-to-average power ratio (PAPR). High peak powers can occur randomly and may drive the power amplifier (PA) into saturation, resulting in non-linear distortion. In this work, we propose a novel tensor-train (TT) deep neural network (DNN) architecture combined with soft clipping to reduce the PAPR to a deterministic level and minimize in-band distortion, while also satisfying spectral mask constraints. The proposed solution requires modifications only at the transmitter and there is no loss of spectral efficiency. Employing the TT decomposition allows for significant reduction in parameters. Results show that the proposed solution allows for significant reduction in PAPR with minimal performance loss. Furthermore, an upper bound for the PAPR is also derived which allows for the prediction of the required input power back off (IBO) without extensive simulations and trial-and-error.

Bandlimited DPD Adapted APD for 5G Communication

Spectrally efficient techniques which help in achieving a high data rate in the communication system also generate signals with a high peak-to-average power ratio (PAPR), which drives the power amplifier (PA) in early saturation. This brief proposes a bandlimited digital predistortion (DPD) adapted analog predistortion (APD) method to linearize the PA. It uses the APD technique first to remove the out-of-band distortion, and then bandlimited DPD is used to remove the in-band distortion. Unlike the conventional DPD, the bandlimited DPD does not require a very high bandwidth feedback signal which is three-to-seven times the input signal bandwidth. The bandwidth of the feedback signal in the bandlimited DPD is the same as that of the input signal. This makes the proposed method more suitable for high bandwidth signals used in advanced communication standards like 5G. The experiments performed with 64-QAM OFDM signals of bandwidth 20 MHz and 100 MHz achieve a maximum normalized mean square error (NMSE) improvement of 21 dB and 18 dB over PA, respectively. The APD circuit used in the method is designed at a central frequency of 3.5 GHz, but the experiments are carried out in an extended frequency range of 2.5 to 4.5 GHz, and the results show that the proposed method delivers significant NMSE improvement in this frequency range.

OFDM and MIMO wireless communication performance measurement using enhanced selective mapping based partial transmit sequences

The great spectral efficiency to mitigate multipath fading of OFDM (orthogonal frequency division multiplexing) made more accepted for broadband communication systems with some drawbacks such as high PAPR (Peak-to-Average Power Ratio), ISI (Inter-Symbol Interference) and ICI (Interiv Carrier Interference). High PAPR forces the operations of the HPA amplifier to work beyond its linear region causing in-band distortion as well as out-band noise and are overcome by using an amplifier with a large dynamic range. In this method, OFDM symbols are partitioned into multiple disjoint sub-blocks which are independently rotated in phase by optimum phase weighting factors. The resultant OFDM signal has less PAPR when compared to that of original OFDM signal in wireless communication. To minimize computational complexity, a modified PTS technique is proposed to enhance PAPR reduction and power amplifier efficiency in OFDM and MIMO (multiple inputs, multiple outputs)-OFDM methods through Selective Mapping based PTS (SMPTS) method combined with PAPR reduction methods.

PAPR Reduction Techniques and Their BIT Error Rate Measurement at OFDM in LTE System

Orthogonal frequency division multiplexing (OFDM) has become an indispensable part of waveform generation in wideband digital communication since its first appearance in digital audio broadcasting (DAB)and it is indeed in use. These descriptions are simplified version of the detailed descriptions provided by 3gpp. It is a superior technology for the high-speed data rate of wire-line and wireless communication systems. The OFDM has many advantages over other techniques such as its high capacity and immunity against multipath fading channels. However ,one of the main drawbacks of the OFDM system is the high-peak-to-average power ratio (PAPR) that leads the system to produce in-band distortion and out-of-band radiation because of the non-linearity and reduces its efficiency is the distortion of the signal caused at the High Power Amplifier (HPA) of a transmitter . Therefore, it is highly desirable to reduce the PAPR of an OFDM signal. For this, numerous techniques have been proposed to overcome the PAPR problem such as i) selective mapping(SLM) ii) partial transmit sequence (PTS), iii) clipping, iv) clipping and filtering. In this paper, the PTS technique was analytically reviewed as one of the important methods to reduce the high PAPR problem. Simulations are used to analyze the efficiency of the techniques used which signifies OFDM to be providing much better PAPR reduction and a better Bit Error Rate (BER) . From simulation results clipping method shows good PAPR reduction with significant amount of BER degradation. Clipping and filtering method shows slight increase in PAPR with small degradation in BER performance than Clipping method and both methods are computationally less complex. PTS provides good PAPR reduction with high computational complexity.

PAPR Reduction and Bit Error Rate Evaluation in OFDM System using Hybrid Techniques

Orthogonal frequency division multiplexing (OFDM) has become an important component of waveform generation in wideband transmission. it's a superior technology for the high-speed rate of wired and wireless communication systems. Currently, multiple-input multiple-output orthogonal frequency division multiplexing (MIMO OFDM) systems are crucial wireless communication systems like 4G and 5G networks & tactical communication. The OFDM has many advantages over other techniques like its high capacity and immunity against multipath fading channels. However, one amongst the foremost drawbacks of the OFDM system is that the high-peak-to-average power ratio (PAPR) that leads the system to provide in-band distortion and out-of-band radiation and reduces its efficiency. This problem increases with a rise within the number of transmit antennas. Therefore, it's highly desirable to cut back the PAPR of an OFDM signal. For this, numerous techniques are proposed to beat the PAPR problem like i) Selective mapping (SLM) ii) Partial transmit sequence (PTS), iii) Clipping, iv) Clipping and filtering. All of those are reduced the PAPR by generating alternative subcarrier vector that are statistically independent OFDM symbols for a given data frame and transmitting the symbol with rock bottom peak power. During this paper we also proposed, some hybrid techniques. The hybrid techniques are the technique of clipping is employed in conjunction with SLM and PTS to cut back computational complexity. And also the combination of SLMPTS to scale back PAPR. Simulations are acquainted with analyze the efficiency of the techniques used which signifies OFDM to be providing much better PAPR reduction and a way better Bit Error Rate (BER). it's shown in simulation results that the proposed scheme performs well reducing PAPR. But the proposed scheme is more complex than the prevailing techniques.

Implementation of FBMCbased Massive MIMOusing Space Time Block Coding

In wireless communication multipath propagation of signal will cause major drawbacks like Intersymbol interference (ISI), Delay spread, Doppler Spread and Intercarrier interference. These drawbacks are efficiently handled by using OFDM technology with Cyclic Prefix, but at the cost of High PAPR increasing the non-linear behaviour of Power Amplifier thereby increases BER and inband distortion, high out of band emissions and loss of spectral efficiency.To reduce the PAPR several PAPR reduction techniques have been proposed over the last few decades but at high complexity. Due to above drawbacks, OFDM technology is not able to provide the requirements of next generation wireless communication and thereby making it un-favourable for 5G communications. To overcome above drawbacks of OFDM, I used a, Filter Bank multicarrier (FBMC), 5G candidate waveform and proposed a method for reducing PAPR, Out-of-band emissions and latency with improving spectral efficiency. I developed a novel precoding method based on a pruned Discrete Fourier Transform (pDFT) in combination with Poly Phase Network (PPN) architecture. The proposed technique has the same peak-to average power ratio as OFDM but does not require a cyclic-prefix and has much lower out-of-band emissions. Furthermore, my method restores complex orthogonality and the ramp-up and ramp-down period of FBMC is dramatically decreased, allowing low latency transmissions. PPN is processed after pDFT, which transforms the received data into ISI-free data.

Maximum-Likelihood-Based Performance Enhancement of Clipped and Filtered OFDM Systems With Clipping Noise Cancellation

Clipping and filtering (CAF) technique is known as a simple and effective approach that reduces the peak-to-average power ratio (PAPR) of orthogonal frequency-division multiplexing (OFDM) signals at the cost of increasing in-band distortion. Clipping noise cancelation (CNC) can compensate for the performance degradation due to the in-band distortion caused by CAF, especially when the number of subcarriers is large, but its achievable symbol error rate (SER) performance is in general worse than that of the unclipped OFDM systems. In this letter, we propose an additional compensation scheme based on the maximum likelihood (ML) metric. We reveal that the proposed approach can even outperform the unclipped OFDM systems, only with moderate increase of complexity from the conventional CNC. Furthermore, we demonstrate that significant gain resulting from the diversity effect can be achieved in the case of frequency-selective Rayleigh fading channels.

Adaptive subcarrier nulling for error vector magnitude and peak to average power ratio reduction in block coded OFDM-VLC

A subcarrier nulling technique based on Reed–Solomon (RS) encoding and nonlinear distortion measurement in orthogonal frequency-division multiplexing (OFDM)-based visible-light communication (VLC) is proposed. The effect of nonlinear clipping imposed by the low dynamic range in an OFMD-VLC leads to a non-uniform distortion on the data-bearing OFDM subcarriers. This distortion combined with the low bandwidth modulation of the light-emitting diode could limit the throughput of the VLC system. The proposed technique employs the clipping distortion to adaptively select and null the group of subcarriers that are responsible for the peak values in the OFDM symbol. Using the frequency domain RS block code, the OFDM transmitter is provided with the flexibility to find and remove the accumulated in-band distortion anywhere within the OFDM frame without the need for prior subcarrier reservation. With the help of log-likelihood ratio detection, nulled subcarriers are estimated at the receiver, and the RS codewords with erasure are recovered and decoded without using side information. This technique mitigates the error vector magnitude and reduces the peak to average power ratio in an OFDM-VLC under severe clipping conditions with reduced complexity. The proposed technique bit error rate performance is studied and compared with traditional techniques in a VLC system with clipping constraint.

Performance Analysis and Comparison of Clipped and Filtered OFDM Systems With Iterative Distortion Recovery Techniques

A well-known drawback of orthogonal frequency-division multiplexing (OFDM) is its signal with high peak-to-average power ratio (PAPR). Among a number of PAPR reduction techniques, clipping and filtering (CAF) is the simplest approach, which effectively reduces the PAPR of band-limited OFDM signals at the cost of increasing in-band distortion. In order to mitigate the performance degradation caused by the in-band distortion, several iterative distortion recovery techniques have been proposed in the literature, and they are largely classified into time-domain (TD) and frequency-domain (FD) compensation approaches: The former and latter are represented by the decision-aided reconstruction (DAR) and clipping noise cancellation (CNC), respectively. To date, however, their theoretical performance limits have not been studied. In this work, we revisit the performance limits of CAF and derive a closed-form signal-to-distortion power ratio (SDR) expression. Furthermore, we introduce a time-domain distortion model for characterizing the OFDM signal with CAF, based on which we make performance comparison between the two compensation approaches. Theoretical analysis and simulations in terms of their achievable symbol error rate (SER) reveal that, unlike the FD counterpart, the TD compensation may suffer from unrecoverable distortion when filtering after clipping is applied at the transmitter.

CLIPPING TECHNIQUES FOR PAPR REDUCTION IN FBMC/OQAM SYSTEM OVER DOUBLY-SELECTIVE CHANNELS

One of the major disadvantages of Filter Bank Multicarrier (FBMC) is high Peak-to-Average Power Ratio (PAPR) of transmitted signal. As a result, nonlinear power amplifier (PA) properties, considerable out-of-band and the in-band distortion types take place in the case where the signals of high peak exceed the PA saturation level. In the present study, a new method of the PAPR reduction is presented and applied to reduce PAPR in FBMC/OQAM system. Different clipping methods have been proposed and studied that are Amplitude Clipping (AC), Palm Clipping (PC), Deep Clipping (DC), and smooth Clipping (SC) for the reduction of PAPR. To evaluate and analyze the performance of PAPR reduction methods, PAPR and Bit Error Rate (BER) measures are used and programmed using MATLAB program. The simulation results show that the clipping methods are strong substitute methods which may be assumed as a method of PAPR reduction for the FBMC-based communication systems and AC appears to be the best method.

A Layer-Reduced Neural Network Based Digital Backpropagation Algorithm for Fiber Nonlinearity Mitigation

A layer-reduced neural network based digital backpropagation algorithm called smoothing learned digital backpropagation (smoothing-LDBP), is proposed in this paper. The smoothing-LDBP smooths the power terms in nonlinear activation functions to limit the bandwidth. The limited bandwidth of the power terms generates fewer in-band distortions, thus reduces the required layer for a given equalization performance. Simulation results show that the required layers of smoothing-LDBP are reduced by approximately 62% at 6.7% HD-FEC compared with learned digital backpropagation. Owing to the layer reduction, the latency and the complexity are reduced by 69% and 51%, respectively. The layer-reduced property of smoothing-LDBP is also validated by a proof-of-concept experiment.

A Signal Processing Framework for Agile RF Beamforming: From RF-Chain-Free to Hybrid Beamformers

In conventional hybrid beamforming approaches, the number of radio-frequency (RF) chains is the bottleneck on the achievable spatial multiplexing gain. Recent studies have overcome this limitation by increasing the update-rate of the RF beamformer. This paper presents a framework to design and evaluate such approaches, which we refer to as agile RF beamforming, from theoretical and practical points of view. In this context, we consider the impact of the number of RF-chains, phase shifters' speed, and resolution to design agile RF beamformers. Our analysis and simulations indicate that even an RF-chain-free transmitter, which its beamformer has no RF-chains, can provide a promising performance compared with fully-digital systems and significantly outperform the conventional hybrid beamformers. Then, we show that the phase shifter's limited switching speed can result in signal aliasing, in-band distortion, and out-of-band emissions. We introduce performance metrics and approaches to measure such effects and compare the performance of the proposed agile beamformers using the Gram-Schmidt orthogonalization process. Although this paper aims to present a generic framework for deploying agile RF beamformers, it also presents extensive performance evaluations in communication systems in terms of adjacent channel leakage ratio, sum-rate, power efficiency, error vector magnitude, and bit-error rates.

Requirements Justification to Digital Signal Synthesizers for Various Types of Radar Systems

The paper justifies the requirements for the level of distortion of radar stations with pulse and quasi-continuous radiation, built on the basis of digital signal synthesizers of four types: digital synthesizers of voltage counts and digital synthesizers of phase counts with uniform sampling, digital synthesizers of voltage counts and digital synthesizers of phase counts with uneven sampling. When building a radar master device, the question arises about choosing the type of digital signal synthesizer. The main initial criteria are the maximum operating range of the digital synthesizer and the level of in-band distortion. When choosing the type of digital signal synthesizer, you have to take into account a large number of factors, the main of which are the complexity of the execution of the digital readout shaper, the possibility of implementing a digital readout shaper with the required speed and number of digits [1, 2]. When making requirements for the total level of distortion, the criterion of acceptable reduction of the probability of correct detection in comparison with its potential value for a fixed probability of false alarm is used. Based on this criterion, in pulse radars, the maximum relative RMS value of the distortion of the intercorrelation function of a signal with angular modulation generated by a digital synthesizer should not exceed Dδx ≤ –(51...67) dB. In a radar with quasi-continuous radiation, the maximum relative mean-square value of the distortion of the autocorrelation function of the signal with angular modulation should not exceed Dδ ≤ –(80...120) dB. The number of bits of phase quantization, voltage and time delay compensation in digital signal synthesizers depends not only on the maximum relative RMS value of the distortion of the intercorrelation function, but also on the number of samples of the signal with angular modulation. Therefore, initially you need to select the reference frequency of the digital signal synthesizer, setting the type of modulation and the effective spectrum width of the signal with angular modulation based on the tactical and technical characteristics radar

EVM-Constrained and Mask-Compliant MIMO-OFDM Spectral Precoding

Spectral precoding is a promising technique to suppress out-of-band emissions and comply with leakage constraints over adjacent frequency channels and with mask requirements on the unwanted emissions. However, spectral precoding may distort the original data vector, which is formally expressed as the error vector magnitude (EVM) between the precoded and original data vectors. Notably, EVM has a deleterious impact on the performance of multiple-input multiple-output orthogonal frequency division multiplexing-based systems. In this paper we propose a novel spectral precoding approach which constrains the EVM while complying with the mask requirements. We first formulate and solve the EVM-unconstrained mask-compliant spectral precoding problem, which serves as a springboard to the design of two EVM-constrained spectral precoding schemes. The first scheme takes into account a wideband EVM-constraint which limits the average in-band distortion. The second scheme takes into account frequency-selective EVM-constraints, and consequently, limits the signal distortion at the subcarrier level. Numerical examples illustrate that both proposed schemes outperform previously developed schemes in terms of important performance indicators such as block error rate and system-wide throughput while complying with spectral mask and EVM constraints.

Indirect learning Hammerstein HPA predistorter for wideband GNSS signals

Compared with the traditional GPS L1 C/A signal, the existing and emerging new-generation wideband GNSS signals suffer more severe distortions due to the nonlinear characteristics of a high-power amplifier (HPA) in the satellite transmitter. HPA nonlinearity can lead to in-band signal distortion and out-of-band spectral regrowth, which degrade the ranging performance of a GNSS receiver. Researchers have reported power loss, correlation peak asymmetries, lock point bias as well as carrier tracking error caused by the HPA nonlinearity. However, few pre-distortion approaches that compensate for the HPA nonlinear effects have been presented in the GNSS field. We first take BDS-3 B2 asymmetric constant envelope binary offset carrier signal as an example to present the HPA nonlinear effects on wideband GNSS signals. Then, the design principle of a predistorter is investigated, and a Hammerstein predistorter is proposed to eliminate the nonlinear HPA with memory. Finally, we compare the constellation diagram, power spectrum, correlation function, code tracking bias with and without the Hammerstein predistorter. The comparison results demonstrate that a digital predistorter is a potential solution to compensate the HPA nonlinear distortions for wideband GNSS signals. This pre-distortion approach is of great significance that can effectively guarantee the nominal signal quality in space not only during the maintenance of the current GNSSs but also for the future emerging local or global navigation systems.

Compensation of Transmitter I/Q Imbalance in Millimeter-Wave MIMO Systems Using a Single Transmitter Observation Receiver

This article proposes a new method to concurrently identify and compensate for the $I/Q$ imbalance in millimeter-wave (mm-wave) multiple-input multiple-output (MIMO) direct-conversion transmitters (Txs) using a single transmitter observation receiver (TOR) fed with the combined outputs of the individual Tx chains. In addition, a signal training approach is proposed that minimizes in-band distortion while maintaining acceptable performance in the out-of-band region. The proposed $I/Q$ imbalance mitigation method is validated by both the simulation and measurement results, using quadrature modulators arranged in one, two, and four Tx configurations for a compensation bandwidth of 4 GHz. The simulation results demonstrate the ability of the proposed method to obtain the same performance for one, two, and four Txs after compensation using an ideal power combiner. Simulations also reveal the sensitivity of the output signal quality to the isolation of the combiner. The experimental measurement results show a normalized mean-square error improvement from 14.5% to 2.22% and 3.46% for the one and four Tx configurations, respectively, using a power combiner with limited isolation. Finally, the method’s ability to improve compensation accuracy is demonstrated as part of the digital predistortion (DPD) linearization of an mm-wave power amplifier (PA).

Performance Analysis of OFDM With Peak Cancellation Under EVM and ACLR Restrictions

This paper presents performance analysis of an adaptive peak cancellation method to reduce the high peak-toaverage power ratio (PAPR) for OFDM systems, while keeping the out-of-band (OoB) power leakage as well as an in-band distortion power below the pre-determined level. In this work, the increase of adjacent leakage power ratio (ACLR) and error vector magnitude (EVM) are estimated recursively using the detected peak amplitude. We present analytical framework for OFDM-based systems with theoretical bit error rate (BER) representations and detection of optimum peak threshold based on predefined EVM and ACLR requirements. Moreover, the optimum peak detection threshold is selected based on the oretical design to maintain the predefined distortion level. Thus, their degradations are automatically restricted below the pre-defined levels which correspond to target OoB radiation. We also discuss the practical design of peak-cancellation (PC) signal with target OoB radiation and in-band distortion through optimizing the windowing size of the PC signal. Numerical results show the improvements with respect to both achievable bit error rate (BER) and PAPR with the PC method in eigen-beam space division multiplexing (E-SDM) systems under restriction of OoB power radiation. It can also be seen that the theoretical BER shows good agreements with simulation results.