Imbalance Compensation Research Articles

Efficient adaptive filtering algorithm for IQ imbalance compensation Tx/Rx systems

This study addresses the problem of in-phase and quadratic-phase (IQ) imbalance in digital transmitter and receiver communication systems. Recently, several adaptive and non-adaptive solutions to this problem have been proposed. In this study, an adaptive solution to this problem is given. The authors propose a new robust two-channel adaptive algorithm to compensate the IQ imbalance problem of quadratic receivers. The new algorithm is based on the combination between the backward blind source separation (BBSS) structure and the fast Newton transversal filter (FNTF) technique to form a two-channel algorithm that cancels the noisy IQ signal adaptively. The combination of the Newton recursion of the FNTF algorithm with the BBSS principle shows the efficiency of the new algorithm to enhance the output signal to interference ratio and allows distortion correction at the output. Simulation results show the efficiency of the new algorithm to compensate the IQ imbalance problem in comparison with the conventional two-channel normalised least mean square algorithm.

IQ Imbalance Compensation and Digital Predistortion for Millimeter-Wave Transmitters Using Reduced Sampling Rate Observations

This paper expounds on the mitigation of the hardware nonidealities exhibited by millimeter-wave (mm-wave) transmitters (TXs) generating ultra-wideband signals. In particular, it tackles the IQ imbalance and nonlinear distortions attributed to the IQ modulator and power amplifier (PA) stages. For that, an offline frequency-domain-based IQ imbalance detection and compensation method using an interleaved multitone test signal with an interleaved I and Q frequency grid is first proposed. Then, the multitone signal settings were modified to enable the reduction of the required sampling rate of the analog-to-digital converter in the TX observation receiver (TOR) needed for IQ imbalance detection. Subsequently, a rearranged pruned Volterra series digital predistortion (DPD) scheme was exploited to separately set the nonlinearity order and linear and nonlinear memory depths for reducing the number of DPD coefficients needed for mm-wave PA linearization. The application of the proposed IQ imbalance detection and compensation method to a commercial IQ mm-wave modulator is stimulated by an interleaved multitone test signal spanning a modulation bandwidth of 4 GHz allowed for the reduction in the normalized mean squared errors (NMSEs) between the input and output signals from −14.0 to −37.7 dB at a complex baseband sampling rate of 8 GS/s and −37.1 and −36.5 dB with the sub-Nyquist complex baseband sampling rates of 1 and 500 MS/s, respectively. With the full and reduced complex baseband sampling rates of the TOR, the subsequent application of the rearranged DPD scheme was used to linearize a PA under test with an output 1 dB compression point of 23 dBm operating at 30 GHz. The PA stimulated by carrier aggregated orthogonal frequency division multiplexing signals with the bandwidths of 320 and 800 MHz is demonstrated the NMSEs of −36.5 and −32.4 dB and the adjacent channel power ratios of 50 and 45 dBc, using 77 and 66 DPD coefficients, respectively.

Novel transmitter IQ imbalance compensation algorithm using training symbols in PDM CO-OFDM system

We systematically deduce the optical fiber channel transmission mathematical model with in-phase/quadrature (IQ) imbalance and channel distortion for polarization division multiplexed (PDM) coherent optical orthogonal frequency division multiplexing (CO-OFDM) system. With the analysis of model, we propose two novel algorithms using training symbols, which can well realize channel distortion and IQ imbalance estimation. This study shows the proposed algorithms performed significantly better than the commonly used approaches. We examine the two proposed methods with simulation via analyzing the bit error rate in the case of different optical signal to noise ratio (OSNR), transmission distance and IQ mismatch at 80Gb/s and 100Gb/s.

Standard-independent I/Q imbalance estimation and compensation scheme inOFDM

Direct-conversion transceivers are gaining increasing attention due to their low power consumption. However, they suffer from a serious in- and quadrature-phase (I/Q) imbalance problem. The I/Q imbalance can severely limit the achievable operating signal-to-noise ratio (SNR) at the receiver and, consequently, the supported constellation sizes and data rates. In this paper, we first investigate the effects of I/Q imbalance on orthogonal frequency division multiplexing (OFDM) receivers, and then propose a new I/Q imbalance compensation scheme. In the proposed method, a new statistic, which is robust against channel distortion, is used to estimate the I/Q imbalance parameters, and then the I/Q imbalance is corrected in the frequency domain. Simulations are performed to verify the effectiveness of the proposed method for I/Q imbalance compensation. The results show that the proposed I/Q imbalance compensation method can achieve bit error rate (BER) performance close to that in the ideal case without I/Q imbalance in additive white Gaussian noise (AWGN) or multipath environments. Furthermore, because no pilot information is required, this method can be applied in various standard communication systems.

Mass Imbalance Compensation Control for Stabilized Platform Based on UKF Identification

Due to the mass imbalance about the center of rotation, the stability of stabilized platform system degrades with carrier’s disturbances. Various feed-forward control methods are provided by reaserchers to solve this problem, however these methods are not well applied because the eccentricity of stabilized platform could not be measured directly. The dynamics model of a typical 2-axis stabilized platform is given. The eccentricity vector is identified through Unscented Kalman Filter(UKF) algorithm. Imbalance torque is precisely observed so that the real-time nonlinear compensation for mass imbalance is achieved through a feed-forward loop. The simulation result indicates that the Root Mean Squared Error (RMSE) of parameters estimation is 0.024 after convergence. the LOS stabilization with carrier’s 2.5Hz vibration is 0.04 rad/s, which improves 78% compared to conventional feed-back control.

Application of Second-Order Sliding-Mode Concepts to Active Magnetic Bearings

Rotor mass imbalance is a common problem to rotating machines due to the unavoidable imperfections in manufacturing. These imbalance forces can be viewed as harmonic disturbances which lead to a periodic rotor runout during rotation. Furthermore, the runout length increases with the rotational speed squared. Moreover, for variable rotational speed applications, these harmonic disturbances are also time-varying. Active magnetic bearings (AMB) provide a means of actively attenuating these disturbances. Although various imbalance compensation schemes have been proposed in the literature to handle this problem, they are often more suitable for constant rotational speed applications where disturbances can be handled at a predetermined rotational speed. This study proposes the application of second-order sliding-mode control (2-SMC) to regulate AMB systems throughout a wide operating speed range. The proposed controllers are composed of two components. The first component is a linear controller for the sake of stabilizing the inherently unstable system, while the second component is a 2-SMC to handle the model uncertainties of the system as well as the exogenous harmonic disturbances. Simulation and experimental results are provided to demonstrate the effectiveness and superiority of the proposed techniques compared to the conventional linear controller.

Stability Analysis Method for Three-Phase Multi-Functional Grid-Connected Inverters With Unbalanced Local Loads Considering the Active Imbalance Compensation

This paper proposes a small-signal stability analysis method for the three-phase multi-functional grid-connected inverter (MFGCI) system with an unbalanced local load based on impedance modeling. To attenuate the imbalance introduced by the local load, a modified power quality-compensation algorithm for the MFGCI based on the conservative power theory is proposed and incorporated into the stability analysis. The impedance model of the three-phase system is developed by adopting the complex space vector method to simplify the stability analysis process in this paper. In addition, based on the proposed impedance model and stability analysis, it is proven that the unbalanced local load can affect the stability of the system when the grid-impedance is not negligible. Furthermore, the adoption of the active imbalance compensation can reshape the impedance characteristics of the unbalanced system and improve the stability. The accuracy of the proposed impedance model, and the stability analysis results are verified by the simulation and experimental results.

Blind Compensation of I/Q Impairments in Wireless Transceivers.

The majority of techniques that deal with the mitigation of in-phase and quadrature-phase (I/Q) imbalance at the transmitter (pre-compensation) require long training sequences, reducing the throughput of the system. These techniques also require a feedback path, which adds more complexity and cost to the transmitter architecture. Blind estimation techniques are attractive for avoiding the use of long training sequences. In this paper, we propose a blind frequency-independent I/Q imbalance compensation method based on the maximum likelihood (ML) estimation of the imbalance parameters of a transceiver. A closed-form joint probability density function (PDF) for the imbalanced I and Q signals is derived and validated. ML estimation is then used to estimate the imbalance parameters using the derived joint PDF of the output I and Q signals. Various figures of merit have been used to evaluate the efficacy of the proposed approach using extensive computer simulations and measurements. Additionally, the bit error rate curves show the effectiveness of the proposed method in the presence of the wireless channel and Additive White Gaussian Noise. Real-world experimental results show an image rejection of greater than 30 dB as compared to the uncompensated system. This method has also been found to be robust in the presence of practical system impairments, such as time and phase delay mismatches.

Voltage Balance Control Strategy of Microgrid Inverter under Unbalanced Loads

微网孤岛运行时系统通过众多网内微网逆变器提供电压支撑，由于网内大量单相负载的存在使得负载难以保持三相平衡，而单相负载投切的随机性又使得负载表征为动态的不平衡。为控制电压的平衡，微网逆变器一般采用双DQ控制方式。这一控制方式可以实现对微网逆变器端电压不平衡控制，但在负载频繁随机投切情况下，电压不平衡控制需要一定动态调节时间。此外，需多个控制器且控制参数整定相对困难。为此，本文提出一种前馈控制策略，通过检测微网逆变器电流实时动态计算电压不平衡补偿量，实现对微网逆变器输出电压不平衡控制。通过前馈控制方式，即使负载存在频繁投切仍可快速跟踪负载变化，实现微网逆变器不平衡电压的补偿。基于该控制策略搭建了仿真模型，仿真结果表明即使在负载突变情况下微网逆变器仍可快速保持电压平衡。 The system voltage of microgrid operating in island mode is supported by numerous microgrid inverter switches in the network. Due to the existence of a large number of single-phase loads in the network, it is difficult to keep three-phase loads balance. Furthermore, the system loads represent dynamic unbalance because of the random switching in or out of single-phase loads. In order to control the voltage to be balance, the microgrid inverter usually adopts double DQ control mode. Although this control mode can realize the voltage unbalance control of the microgrid inverter terminal voltage, the voltage imbalance control needs a certain dynamic regulation period when frequent load switching occurs. In addition, several controllers are needed and its control parameters tuning is complex. To this end, this paper presents a feedforward control strategy to achieve imbalance control of microgrid inverter output voltage, by detecting the microgrid inverter real-time current and then calculate the compensation of voltage imbalance. Through the feedforward control method, the load change can be traced quickly and the unbalanced voltage of the microgrid inverter can be well compensated even if the system loads are switched frequently. Based on the control strategy, the system simulation model is built and resulting simulation results show that the microgrid inverter can maintain the voltage balance even under sudden load change.

Distributed Secondary Level Control for Energy Storage Management in DC Microgrids

DC microgrids have been known to be a promising solution for improving renewable energy integration with electrical grid and enhancing the system’s overall energy efficiency. A key component of this microgrid is the energy storage system, which besides smoothing the intermittent behavior of renewable sources, also allows intentional islanding and the execution of optimization routines to improve the microgrid performance. Assuming that storage systems in commercial and residential buildings will mostly be composed of multiple storage units, an energy storage management system, which provides charge/discharge monitoring and state-of-charge (SOC) equalization, is needed to prevent overcharging the units or their uneven use, which can lead to faster deterioration of battery banks. This paper proposes an energy storage management system based on distributed secondary level control, which promotes charge/discharge control and provides SOC equalization simultaneously. The SOC imbalance compensation alters the energy storage unit virtual droop resistance according to the difference between the unit SOC and the microgrid average SOC, thus the compensation intensity is dependent on the imbalance level being suitable to be employed in dc bus signaling controlled microgrids.

An Imbalance Compensation Framework for Background Subtraction

Class imbalance refers to the instance where the number of training samples for the majority classes is far more than that of the minority classes (relative imbalance), and the quality of training samples for the minority classes is inferior to that of the majority classes (absolute imbalance), which are further complicated by other imbalance factors, e.g., data overlapping. Video background subtraction aims to classify each pixel into two classes: foreground and background. This paper first reveals that background subtraction is a class imbalance problem, where the foreground and background are the minority and majority classes, respectively. By exploring spatial and temporal correlation inherent in video data, we present an imbalance compensation framework for background subtraction, which consists of two sequential modules, imbalance-compensated bilayer modeling, and imbalance-compensated Bayesian classification. In the first module, spatio-temporal oversampling (SOS) and selective downsampling (SDS) are proposed to compensate the imbalance at data level. SOS attempts to synthesize representative samples appended to the minority sample set, while SDS selectively deletes a number of majority samples in data overlapping areas. The rebalanced samples are then used to learn a bilayer model. In the second module, novel cost functions are proposed to compensate the effect of class imbalance at algorithm level. The cost functions are based on imbalance measurement, and used to construct the prior term in the Bayesian classification scheme. Experiments are conducted on public databases to demonstrate the effectiveness of the proposed method.

Blind receiver IQ imbalance compensation in DD Nyquist-SCM system

Receiver in-phase/quadrature (IQ) imbalance caused by imperfect analog receiver front end can rapidly degrade system performance in Nyquist-subcarrier-modulation (Nyquist-SCM) direct detection scheme. These imbalances, including IQ skew, IQ gain and phase imbalance, become increasingly important when higher symbol rate, higher modulation order, and lower roll-off pulse shape are used. Here, an adaptive four real-valued widely linear equalizer in an inner two-by-two butterfly structure is used to compensate receiver IQ imbalance and channel linear distortion, which has the same computational complexity with the conventional complex-valued FIR filter. In addition, the effectiveness of adaptive equalizer is validated experimentally with offline processing through a 20-Gbps 16-QAM Nyquist-SCM signal over 40-km standard single mode fiber transmission.

Iterative IQ Imbalance Compensation Receiver for Single Carrier Transmission

It is well known that low-cost RF front-end implementation such as direct conversion transmitter suffers from serious in-phase/quadrature phase (IQ) imbalance. Most existing works in single carrier transmission employ linear compensation methods, such as Least Square and minimum mean square error, to combat the interference caused by IQ imbalance. Actually, for single carrier transmission, it is possible for the receivers to adopt advanced nonlinear compensation methods to improve the system performance under IQ imbalance. In this paper, we design a new iterative decision feedback receiver to compensate the IQ imbalance caused by unideal radio front end for single carrier frequency domain equalization (SC-FDE). Numerical results shows that, compared with the conventional linear method, our proposed iterative IQ imbalance compensation can significantly improve the performance of SC-FDE system under IQ imbalance.

Blind Transmitter IQ Imbalance Compensation in M-QAM Optical Coherent Systems

We investigate transmitter IQ imbalance compensation based on the blind adaptive source separation (BASS) method in a dual-polarization M-QAM optical coherent system. The robustness of the BASS method against the residual carrier frequency offset (CFO) is numerically investigated and compared to that of the Gram-Schmidt or-thogonalization procedure (GSOP). We further validate experimentally the proposed method with 10 Gbaud optical 4-QaM and 16-QAM signals at 30° and 10° phase imbalance, respectively, with simulated impairments. More specifically, in the presence of 5 χ 10−6 residual CFO (normalized to the sample rate), the optical signal-to-noise ratio penalty reduction of the BASS method compared to the GSOP method is 1 dB for 4-QAM at a bit error ratio (BER) of 2 χ 10−3 and 2 dB for 16-QAM at a BER of 10−3. In contrast to the GSOP, which requires an independent block, the BASS method can be integrated into an equalizer, simplifying the operation and allowing parallel implementation.

IQ Imbalance Compensation for Generalized Frequency Division Multiplexing Systems

Generalized frequency division multiplexing (GFDM) with a flexible structure is one of the promising candidates for the fifth generation wireless communication system. This letter presents a compensation scheme of in-phase and quadrature (IQ) imbalance caused by radio frequency front-end for GFDM. The motivation behind this letter is to relax the requirement on time-invariant channel in the process of estimating IQ imbalance parameters. A low computational complexity approach is proposed to directly estimate IQ imbalance parameters without any prior knowledge of channel. Meanwhile, the structure of training sequences that avoid channel estimation is derived. Simulation results confirm that the proposed method can reduce the effects of IQ imbalance and provide reliable performance even over severe IQ imbalance environment.

Control Strategy for the Compensation of Imbalance and Harmonic in Energy Internet

Control Strategy for the Compensation of Imbalance and Harmonic in Energy Internet

Full-duplex amplify-and-forward relays with optimized transmission power under imperfect transceiver electronics

In-band full-duplex (FD) relays are useful for extending coverage areas and increasing overall throughput in wireless networks. The main technical difficulty hindering their implementation and use is their inherent self-interference (SI), generated due to simultaneous in-band reception and forwarding. Efficient SI mitigation is a practical necessity, and the imperfections in transceiver electronics, from which power amplifier (PA) non-linearity is one of the most serious phenomena, have to be taken into account in order to not limit the performance of such techniques. The magnitude of the distortion introduced by the PA depends on the relay input back-off (IBO) whose optimization for alleviating the effect of PA non-linearity is the main research objective in this paper. In particular, although plain signal-to-noise ratio (SNR) at the destination obviously increases when the IBO decreases, increased transmit power also strengthens the non-linear distortion leading to decreasing overall signal-to-interference-plus-noise ratio (SINR). We develop expressions for bounding the optimal IBO setting that maximizes the SINR at the destination, considering all relevant hardware impairments and SI cancellation with I/Q imbalance compensation. We provide closed-form solutions for the soft-limiter PA model and numerical results for more general PA models. Finally, the derived IBO bounds are compared with the numerical maximization of the SINR and the minimization of the bit-error rate (BER) to demonstrate that the theoretical bound settings provide good approximations to the optimal one.

Investigation of quadrature imbalance compensation algorithm for coherent 6PolSK-QPSK

6PolSK-QPSK is a promising modulation format in optical fiber communication. Because of the damage suffered during the transmission and reception, a series of algorithms are needed to be adopted to recover the original data. We proposed a novel quadrature imbalance compensation algorithm based on the data statistical properties. Simulation results show that the quadrature imbalance can be well compensated with the proposed algorithm.

Predictive modeling of respiratory tumor motion for real-time prediction of baseline shifts

Baseline shifts in respiratory patterns can result in significant spatiotemporal changes in patient anatomy (compared to that captured during simulation), in turn, causing geometric and dosimetric errors in the administration of thoracic and abdominal radiotherapy. We propose predictive modeling of the tumor motion trajectories for predicting a baseline shift ahead of its occurrence. The key idea is to use the features of the tumor motion trajectory over a 1 min window, and predict the occurrence of a baseline shift in the 5 s that immediately follow (lookahead window). In this study, we explored a preliminary trend-based analysis with multi-class annotations as well as a more focused binary classification analysis. In both analyses, a number of different inter-fraction and intra-fraction training strategies were studied, both offline as well as online, along with data sufficiency and skew compensation for class imbalances. The performance of different training strategies were compared across multiple machine learning classification algorithms, including nearest neighbor, Naïve Bayes, linear discriminant and ensemble Adaboost. The prediction performance is evaluated using metrics such as accuracy, precision, recall and the area under the curve (AUC) for repeater operating characteristics curve. The key results of the trend-based analysis indicate that (i) intra-fraction training strategies achieve highest prediction accuracies (90.5–91.4%); (ii) the predictive modeling yields lowest accuracies (50–60%) when the training data does not include any information from the test patient; (iii) the prediction latencies are as low as a few hundred milliseconds, and thus conducive for real-time prediction. The binary classification performance is promising, indicated by high AUCs (0.96–0.98). It also confirms the utility of prior data from previous patients, and also the necessity of training the classifier on some initial data from the new patient for reasonable prediction performance. The ability to predict a baseline shift with a sufficient look-ahead window will enable clinical systems or even human users to hold the treatment beam in such situations, thereby reducing the probability of serious geometric and dosimetric errors.

Digital Frequency Discriminator (DFD) Improvement by LO Leakage and I/Q Imbalance Compensation

Digital Frequency Discriminator (DFD) Improvement by LO Leakage and I/Q Imbalance Compensation