Mismatch Estimation Research Articles

On the General Mathematical Framework, Calibration/Compensation Method, and Applications of Non-Ideal Software Defined Harmonics Rejection Transceivers

Recently harmonic interference rejection has been recognized as a crucial bottleneck of truly wide-band software defined radio transceivers. Phase and gain mismatches among mixing paths, typical for nanoscale technology nodes, severely impact the achievable rejection ratio in classical harmonic rejection transceivers. This paper proposes an alternative digital intensive architecture, which enables increased harmonic interference rejection for wide-band SDR transceivers impacted by severe gain and phase mismatches. A generic mathematical framework of the target architecture is introduced to support a systematic design space exploration for multi-path harmonic interference rejection transceivers. With the framework, an iterative on-die estimation and compensation of mismatch for both the transmitter and receiver are presented. Case study with four mixing paths shows that ideal rejection can be achieved when targeting a single dominating harmonic interferer, and joint suppression of the 3rd and 5th order harmonic interferers of at least 70 dB can be obtained under realistic radio input scenarios.

Economic Multi-stage Output Feedback NMPC using the Unscented Kalman Filter

Nonlinear Model predictive control (NMPC) is a popular control strategy for highly nonlinear chemical processes. The ability to handle safety and environmental constraints along with the use of an economic objective makes NMPC highly appealing to industries. The performance of NMPC depends strongly on the accuracy of the model. In reality, there always are plant-model mismatch and state estimation errors. Hence the NMPC controller must be robust to uncertainties in the model as well as against estimation errors. Among the several approaches presented in the literature, the scenario-tree based multi-stage NMPC approach is a non-conservative and efficient formulation. In this approach, the evolutions of the plant for different realizations of the uncertainties are considered as different scenarios and the optimization problem is formulated as a multi-stage stochastic programming problem with recourse. In this work, we consider multi-stage output feedback NMPC using the Unscented Kalman Filter (UKF) where the nonlinearities are represented using deterministically chosen sigma points for state estimation. In the control problem, we explicitly consider the UKF estimation equations to predict the future evolution of the system. The proposed approach is illustrated by simulation results of fed-batch chemical reactor with an economic cost function.

Investigating interaural frequency-place mismatches via bimodal vowel integration.

For patients having residual hearing in one ear and a cochlear implant (CI) in the opposite ear, interaural place-pitch mismatches might be partly responsible for the large variability in individual benefit. Behavioral pitch-matching between the two ears has been suggested as a way to individualize the fitting of the frequency-to-electrode map but is rather tedious and unreliable. Here, an alternative method using two-formant vowels was developed and tested. The interaural spectral shift was inferred by comparing vowel spaces, measured by presenting the first formant (F1) to the nonimplanted ear and the second (F2) on either side. The method was first evaluated with eight normal-hearing listeners and vocoder simulations, before being tested with 11 CI users. Average vowel distributions across subjects showed a similar pattern when presenting F2 on either side, suggesting acclimatization to the frequency map. However, individual vowel spaces with F2 presented to the implant did not allow a reliable estimation of the interaural mismatch. These results suggest that interaural frequency-place mismatches can be derived from such vowel spaces. However, the method remains limited by difficulties in bimodal fusion of the two formants.

Estimation and Correction of Gain Mismatch and Timing Error in Time-Interleaved ADCs Based on DFT

Abstract Time-interleaved analog-to-digital converter (ADC) architecture is crucial to increase the maximum sample rate. However, offset mismatch, gain mismatch, and timing error between time-interleaved channels degrade the performance of time-interleaved ADCs. This paper focuses on the gain mismatch and timing error. Techniques based on Discrete Fourier Transform (DFT) for estimating and correcting gain mismatch and timing error in an M-channel ADC are depicted. Numerical simulations are used to verify the proposed estimation and correction algorithm.

Penumbra pattern assessment in acute stroke patients: comparison of quantitative and non-quantitative methods in whole brain CT perfusion.

Background And PurposeWhile penumbra assessment has become an important part of the clinical decision making for acute stroke patients, there is a lack of studies measuring the reliability and reproducibility of defined assessment techniques in the clinical setting. Our aim was to determine reliability and reproducibility of different types of three-dimensional penumbra assessment methods in stroke patients who underwent whole brain CT perfusion imaging (WB-CTP).Materials And MethodsWe included 29 patients with a confirmed MCA infarction who underwent initial WB-CTP with a scan coverage of 100 mm in the z-axis. Two blinded and experienced readers assessed the flow-volume-mismatch twice and in two quantitative ways: Performing a volumetric mismatch analysis using OsiriX imaging software (MMVOL) and visual estimation of mismatch (MMEST). Complementarily, the semiquantitative Alberta Stroke Programme Early CT Score for CT perfusion was used to define mismatch (MMASPECTS). A favorable penumbral pattern was defined by a mismatch of ≥30% in combination with a cerebral blood flow deficit of ≤90 ml and an MMASPECTS score of ≥1, respectively. Inter- and intrareader agreement was determined by Kappa-values and ICCs.ResultsOverall, MMVOL showed considerably higher inter-/intrareader agreement (ICCs: 0.751/0.843) compared to MMEST (0.292/0.749). In the subgroup of large (≥50 mL) perfusion deficits, inter- and intrareader agreement of MMVOL was excellent (ICCs: 0.961/0.942), while MMEST interreader agreement was poor (0.415) and intrareader agreement was good (0.919). With respect to penumbra classification, MMVOL showed the highest agreement (interreader agreement: 25 agreements/4 non-agreements/κ: 0.595; intrareader agreement 27/2/0.833), followed by MMEST (22/7/0.471; 23/6/0.577), and MMASPECTS (18/11/0.133; 21/8/0.340).ConclusionThe evaluated approach of volumetric mismatch assessment is superior to pure visual and ASPECTS penumbra pattern assessment in WB-CTP and helps to precisely judge the extent of 3-dimensional mismatch in acute stroke patients.

An IQ mismatch calibration and compensation technique for wideband wireless transceivers

An IQ mismatch calibration and compensation technique based on the digital baseband for wideband wireless communication transmitters is proposed. The digital baseband transmits the signal used for IQ mismatch calibration. The signal passes through the RF transmitter path, the calibration loop (which is composed of a square power detector and a band-pass filter in the RF transceiver) and the variable gain amplifier of the receiver. The digital baseband samples the signal for IQ mismatch estimation and compensates for it. Compared with the self-calibration technique in the RF chip, the proposed technique saves area and power consumption for the wireless local area network solution. This technique has been successfully used for the 802.11n system and satisfies the requirement of the standard by achieving over 50 dB image suppression.

Distributed Consensus-Based Economic Dispatch With Transmission Losses

A distributed algorithm is presented to solve the economic power dispatch with transmission line losses and generator constraints. The proposed approach is based on two consensus algorithms running in parallel. The first algorithm is a first-order consensus protocol modified by a correction term which uses a local estimation of the system power mismatch to ensure the generation-demand equality. The second algorithm performs the estimation of the power mismatch in the system using a consensus strategy called consensus on the most up-to-date information. The proposed approach can handle networks of different size and topology using the information about the number of nodes which is also evaluated in a distributed fashion. Simulations performed on standard test cases demonstrate the effectiveness of the proposed approach for both small and large systems.

Difficulty of MRI based identification of lesion age by acute infra-tentorial ischemic stroke.

BackgroundSystemic thrombolysis in acute ischemic stroke is restricted to the 4.5 h time window. Many patients are excluded from this treatment because symptom onset is unknown. Magnetic resonance imaging (MRI) studies have shown that stroke patients presenting with acute supra-tentorial diffusion-weighted imaging (DWI) lesions that do not have matching lesions on fluid attenuated inversion recovery (FLAIR) are likely to be within a 4.5 hour time window. This study examines the DWI-FLAIR mismatch in infra-tentorial stroke.MethodsThis was a retrospectively conducted substudy of the “1000+” study; a prospective, single-center observational study (http://clinicaltrials.gov; NCT00715533). Fifty-six patients with infra-tentorial stroke confirmed by MRI and known symptom onset who underwent the scan within 24 h after symptom onset were analysed. Two neurologists blinded to clinical information separately rated the DWI lesion visibility on FLAIR. Lesion volume, relative signal intensities of DWI and relative apparent diffusion coefficient values were determined.ResultsRegarding baseline characteristics our study population had a median age of 66 years, a median time from symptom onset to MRI of 616.5 minutes, a median NIHSS of 3 and a median DWI lesion volume of 0.26 ml. A negative FLAIR allocated patients to a time window under 4.5 h correctly with a sensitivity of 55% and a specificity of 61%, a positive predictive value of 44% and a negative predictive value of 71%. FLAIR positivity decreased with age (p = 0.018), and showed no significant correlation to lesion volume (p = 0.145).ConclusionsIn our study the DWI-FLAIR-Mismatch does not help to reliably identify patients within 4.5 h of symptom onset in acute ischemic infra-tentorial stroke. Thus therapeutical decisions based on the DWI-FLAIR mismatch estimation of time from onset cannot be recommended in patients with infra-tentorial stroke.

A Fast and Precise Blind I/Q Mismatch Compensation for Image Rejection in Direct-Conversion Receiver

In this paper, we propose a new digital blind in-phase/quadrature-phase (I/Q) mismatch compensation technique for image rejection in a direct-conversion receiver (DCR). The proposed image-rejection circuit adopts DC offset cancellation and a sign-sign least mean squares (LMS) algorithm with a unique step size adaptation both for a fast and precise I/Q mismatch estimation. In addition, several performance-optimizing design considerations related to accuracy, speed, and hardware simplicity are discussed. The implementation of the proposed circuit in an FPGA results in an image-rejection ratio (IRR) of 65 dB, which is the best performance with modulated signals, along with an adaptation time of 0.9 seconds, which is a tenfold increase in the compensation speed as compared to previously reported circuits. The proposed technique will be a promising solution in the area of image rejection to increase both the speed and accuracy of future DCRs.

A Fast and Precise Blind I/Q Mismatch Compensation for Image Rejection in Direct-Conversion Receiver

In this paper, we propose a new digital blind in-phase/quadrature-phase (I/Q) mismatch compensation technique for image rejection in a direct-conversion receiver (DCR). The proposed image-rejection circuit adopts DC offset cancellation and a sign-sign least mean squares (LMS) algorithm with a unique step size adaptation both for a fast and precise I/Q mismatch estimation. In addition, several performance-optimizing design considerations related to accuracy, speed, and hardware simplicity are discussed. The implementation of the proposed circuit in an FPGA results in an image-rejection ratio (IRR) of 65 dB, which is the best performance with modulated signals, along with an adaptation time of 0.9 seconds, which is a tenfold increase in the compensation speed as compared to previously reported circuits. The proposed technique will be a promising solution in the area of image rejection to increase both the speed and accuracy of future DCRs.

A Novel Iterative Structure for Online Calibration of $M$-channel Time-Interleaved ADCs

This paper proposes a computationally efficient calibration structure for online estimation and compensation of offset, gain and frequency response mismatches in M-channel time-interleaved (TI) analog-to-digital converters (ADCs). The basic idea of the proposed approach is to reserve some sampling instants for estimating and tracking the mismatch parameters of sub-ADCs with reference to a known input. Since the estimation problem is analogous to a standard system identification problem, we propose two simple variable digital filter (VDF) based adaptive filter structures which are derived from the least mean squares (LMS) and normalized LMS algorithms. On the other hand, the reservation of some sampling instants in the normal operation of TI ADC implies that part of samples have to be sacrificed. Based on a general time-varying linear system model for the mismatch and the spectral property of a slightly oversampled input signal, we also propose a novel iterative framework to solve the resulting underdetermined problem. It not only embraces a number of iterative algorithms for the tradeoff between convergence rate and arithmetic complexity but also admits efficient update structure based again on VDFs. Therefore, thanks to the well-known efficient implementation of VDFs, the adaptability of both estimation and compensation algorithms allows us to combine them seamlessly to form an online calibration structure, which is able to track and compensate for the channel mismatches with low complexity and high reconstruction accuracy. Finally, we demonstrate the usefulness of the proposed approach by means of computer simulations.

Relations Between Zero-IF Receiver I/Q and TI-ADC Channel Mismatches

This paper shows that the in-phase and quadrature (I/Q) channel mismatch problem for complex signals in zero-IF receivers (ZIFRs) is related to the real-signal channel-mismatch problem in two-channel time-interleaved analog-to-digital converters (TI-ADCs). The problems are related in that, given one of the problems, it can be converted to the other problem via relatively simple signal processing operations. This offers more options for the estimation of and compensation for I/Q and TI-ADC channel mismatches. In particular, if there is a need to perform both I/Q and TI-ADC channel mismatch correction, one can make use of the same basic estimation and/or compensation principles for both applications which may save computational resources. The use of TI-ADC mismatch estimation and/or compensation also offers real-signal processing techniques to the complex-signal mismatch estimation and compensation problem in ZIFRs.

Robust Adaptive Beamforming Using a Low-Complexity Shrinkage-Based Mismatch Estimation Algorithm

In this work, we propose a low-complexity robust adaptive beamforming (RAB) technique which estimates the steering vector using a Low-Complexity Shrinkage-Based Mismatch Estimation (LOCSME) algorithm. The proposed LOCSME algorithm estimates the covariance matrix of the input data and the interference-plus-noise covariance (INC) matrix by using the Oracle Approximating Shrinkage (OAS) method. LOCSME only requires prior knowledge of the angular sector in which the actual steering vector is located and the antenna array geometry. LOCSME does not require a costly optimization algorithm and does not need to know extra information from the interferers, which avoids direction finding for all interferers. Simulations show that LOCSME outperforms previously reported RAB algorithms and has a performance very close to the optimum.

Non-intrusive Cognitive Radio Using Adaptive Nulls-Steering

In this paper, we propose an adaptive non-intrusive cognitive radio network based on smart antenna technologies. The cognitive transmitter (CT), which is equipped with antenna array, first estimates and tracks the composite steering vectors of each primary (licensed) user. In what follows, CT forms transmit beamforming to place nulls to primary receivers based on the estimated spatial signatures. Moreover, we extensively analyze performance degradation caused by spatial signatures mismatch (estimation error) and verify that the proposed robust nulls-steering beamformer can comprehensively alleviate the mismatch effect. Simulation results demonstrate convergence of the proposed gradient-based recursive least squares algorithm. Furthermore, we have shown that outage probability can be kept extremely low under appropriate array size, which ensures the practicability of the proposed scheme.

Novel Pilot Scheme for Transmitter IQ Mismatch Compensation in CO-OFDM System

Transmitter in-phase and quadrature (Tx IQ) mismatch is one of the major obstacles preventing coherent optical orthogonal frequency division multiplexing systems from achieving high data rates. Several Tx IQ mismatch compensation methods at the receiver side have been proposed based on the mismatch estimation by the use of pilot signals. In this letter, we propose a novel pilot system for the Tx IQ mismatch estimation to improve the channel-estimation performance. The pilot scheme exploits the conjugate redundancy of the subcarrier mirror images due to the Tx IQ mismatch and allows the estimation of the Tx IQ mismatch factor and channel parameter independently. The advantages of the proposed algorithm are proved via mean square error analysis, and the bit error rate improvement is shown in simulations.

Adaptive Control of Systems with Actuator Failures Using an Adaptive Reference Model

This paper considers model reference adaptive control of uncertain plants under actuator failures when the plant model matching conditions are violated due to abnormal changes in the plant or incorrect knowledge of the plant’s mathematical structure. The approach consists of direct adaptation of state feedback gains for state tracking to compensate for model errors and actuator failures and simultaneous estimation of the plant model mismatch. Because of mismatch resulting from large changes in the plant, the original reference model may no longer be appropriate, and it may be desirable to track the state of a modified reference model that still provides satisfactory performance. The reference model is redesigned if the estimated plant model mismatch exceeds a bound that is determined via robust stability and/or performance criteria. The proposed controller is a hybrid direct–indirect adaptive controller that offers asymptotic state tracking in the presence of plant model mismatch, parameter deviations, and actuator failures.

CRLB-Achieving I/Q Mismatch Estimator for Low-IF Receiver Using Repetitive Training Sequence in the Presence of CFO

This paper presents a method for estimating the in-phase/quadrature-phase (I/Q) mismatch in low-intermediate frequency receivers for orthogonal frequency division multiplexing (OFDM) signals in the presence of carrier-frequency offset. The proposed estimator operates on the repetitive training sequence of the OFDM packet preamble. To derive a practical maximum-likelihood estimator, an invertible mapping operation is applied on the observation vectors, so that a closed-form expression of the likelihood function can be obtained. The proposed estimator is shown to achieve the Cramer Rao lower bound at high image signal power levels. The error variance of the estimator is analyzed, which closely matches simulation results. The uncoded bit-error-rate is shown via simulation to be approximately that of an ideal receiver without I/Q mismatch.

Direct adaptive control using an adaptive reference model

Direct model reference adaptive control is considered when the plant-model matching conditions are violated due to large changes in the plant or incorrect knowledge of the plant's mathematical structure. Because of the mismatch, the plant can no longer track the original reference model, but may be able to track a modified reference model that still provides satisfactory performance. The proposed approach uses a time-varying ‘adaptive’ reference model that reflects the achievable performance of the changed plant. The approach consists of direct adaptation of state feedback gains for state tracking and simultaneous estimation of the plant-model mismatch. The reference model adapts to the changed plant, and is redesigned if the estimated plant-model mismatch exceeds a bound determined via robust stability and/or performance criteria. The resulting controller offers asymptotic state tracking in the presence of plant-model mismatch as well as matched parameter deviations.

Joint Mismatch and Channel Compensation for High-Speed OFDM Receivers with Time-Interleaved ADCs

Analog-to-digital converters (ADCs) with high sampling rates and output resolution are required for the design of mostly digital transceivers in emerging multi-Gigabit communication systems. A promising approach is to use a time-interleaved (TI) architecture with slower sub-ADCs in parallel, but mismatch among the sub-ADCs, if left uncompensated, can cause error floors in receiver performance. Conventional mismatch compensation schemes typically have complexity (in terms of number of multiplications) that increases with the desired resolution at the output of the TI-ADC. In this paper, we investigate an alternative approach, in which mismatch and channel dispersion are compensated jointly, with the performance metric being overall link reliability rather than ADC performance. For an OFDM system, we characterize the structure of mismatch-induced interference, and demonstrate the efficacy of a frequency-domain interference suppression scheme whose complexity is independent of constellation size (which determines the desired resolution). Numerical results from computer simulation and from experiments on a hardware prototype show that the performance with the proposed joint mismatch and channel compensation technique is close to that without mismatch. While the proposed technique works with offline estimates of mismatch parameters, we provide an iterative, online method for joint estimation of mismatch and channel parameters which leverages the training overhead already available in communication signals.

Internal model sliding mode control approach for glucose regulation in type 1 diabetes

Patients with type 1 diabetes require insulin therapy to maintain blood glucose levels within safe ranges since their pancreas is unable to complete its function. The development of a closed-loop artificial pancreas capable of maintaining normoglycemia during daily life will dramatically improve the quality of life for insulin-dependent diabetic patients. In this work, a closed-loop control strategy for blood glucose level regulation in type 1 diabetic patients is presented. A robust controller is designed using a combination of internal model and sliding mode control techniques. Also, the controller is provided with a feedforward loop to improve meal compensation. A simulation environment designed for testing the artificial pancreas control algorithms has been used to evaluate the controller. The simulation results show a good controller performance in fasting conditions and meal disturbance rejection, and robustness against model–patient mismatch and meal estimation errors.