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Zsolt Kollar

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Zsolt Kollár was born in 1983. He obtained his Diploma in Electrical Engineering in 2008 from the Budapest University of Technology and Economics (BME). He received his Ph.D. degree in Electrical Engineering from BME in 2013. He is currently an associate professor at the Department of Measurement and Information Systems. Since 2016, he is the head of the MATLAB Laboratory. He is responsible for the maintenance and development of the Fdident (Frequency Domain Identification Toolbox) MATLAB Toolbox. He has participated in numerous research and industrial projects. Besides research, he has been teaching courses on signal processing, measurement technology, and MATLAB programming. His research interests include digital signal processing, system identification, quantization effects, and wireless communication.

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Papers by Zsolt Kollar

Software and Hardware Solutions for Channel Estimation based on Cyclic Golay Sequences

Radioengineering, Sep 15, 2016

This paper presents channel estimation methods based on cyclic complementary Golay sequences. Fir... more This paper presents channel estimation methods based on cyclic complementary Golay sequences. First, the conventional Golay correlator is investigated, then a frequency domain approach using Discrete Fourier Transform (DFT) is provided. A complex valued fast Golay correlator is introduced which can be used for the estimation of complex valued channel impulse response. Furthermore, this paper presents the Recursive DFT (R-DFT), a signal processing architecture which may be beneficial compared to the wellknown Fast Fourier Transform (FFT). The R-DFT is able to efficiently calculate a point-by-point block spectra of the input signal, which makes it suitable for hardware implementation. Throughout the paper, the R-DFT is applied and it is compared to the conventional estimation methods. Finally, the efficiency of the proposed schemes is compared through simulations based on the 60 GHz WiGig and the COST 207 standard, applying various channel models.

MIMO Communication Measurements in Small Cell Scenarios at 28 GHz

IEEE Transactions on Antennas and Propagation, Jul 1, 2021

Massive multiple-input-multiple-output (MIMO) systems operating in the centimeter-wave (cmWave) a... more Massive multiple-input-multiple-output (MIMO) systems operating in the centimeter-wave (cmWave) and millimeter-wave (mmWave) region offer huge spectral efficiencies, which enables to satisfy the urgent need for higher data rates in mobile communication networks. However, the proper design of those massive MIMO systems first requires a deep understanding of the underlying wireless propagation channel. Therefore, we present a fully digital MIMO measurement system operating around 28 GHz. The system enables to take fast subsequent snapshots of the complex MIMO channel matrix. Based on this method, we statistically analyze the time-dependent channel behavior, the achievable signal quality and spectral efficiency, as well as the channel eigenvalue profile. Furthermore, the presented calibration approach for the receiver enables an estimation of the dominant absolute angle of arrival (AoA) and allows us to draw conclusions about the line-of-sight (LOS) dominance of the scenario. In total, 159 communication measurements over 20 s are conducted in three different small cell site scenarios to investigate the wireless propagation behavior. The measurements reveal the existence of several spatial propagation paths between the mobile transmitter and the base station. Furthermore, an insight into their likelihood in different propagation scenarios is also given.

Sliding Window Evaluation of the Wiener-Hopf Equation

Radioengineering, Jun 12, 2020

This paper presents an efficient method for solving the Wiener-Hopf equation in a sliding window ... more This paper presents an efficient method for solving the Wiener-Hopf equation in a sliding window by calculating the correlation matrices recursively. Furthermore, a novel algorithm is introduced for evaluating the inverse of the auto-correlation matrix-the Recursion with Splitting the Correlation matrix into 4 Blocks for Inversion (RSC4BI)-which can significantly reduce the computational requirements. The presented procedure is optimized for special cases to achieve an efficient implementation which allows faster real-time signal processing or to reduce the response time-e.g. the latency-by distributing the computations over the time. The proposed method is also validated through numerical simulations and hardware implementation.

Low complexity PPN-FBMC Receivers with improved sliding window equalizers

Physical Communication, Oct 1, 2022

Development and validation of a surface profiling system for end of line monitoring of microstructured elastomer seals based on chromatic confocal microscopy

Precision Engineering-journal of The International Societies for Precision Engineering and Nanotechnology, Sep 1, 2022

Quantization noise analysis in FBMC receivers and its effect on the BER performance

Digital Signal Processing

Optimization of the Crest Factor for Complex-Valued Multisine Signals

Radioengineering

Multisine signals are commonly used in the measurement of dynamic systems and wireless channels. ... more Multisine signals are commonly used in the measurement of dynamic systems and wireless channels. For optimal measurements with a high dynamic range, a low Crest Factor (CF) excitation signal is required. In this paper, a modified approach to optimize the crest factor for complex-valued multisine signals is presented. The approach uses a nonlinear optimization method where the real and imaginary parts can also be optimized for low CF. Furthermore, extensions of the real-valued multisine CF optimization methods are presented for complex-valued cases. The proposed methods are validated and compared using simulations. Based on the results it is shown that the novel approach can lead to more optimal signal design and lower CF compared to other techniques for complex-valued multisine signals.

Computationally efficient predictive control based on ANN state-space models

arXiv (Cornell University), Mar 30, 2023

Artificial neural networks (ANN) have been shown to be flexible and effective function estimators... more Artificial neural networks (ANN) have been shown to be flexible and effective function estimators for identification of nonlinear state-space models. However, if the resulting models are used directly for nonlinear model predictive control (NMPC), the resulting nonlinear optimization problem is often overly complex due the size of the network, requires the use of high-order observers to track the states of the ANN model, and the overall control scheme exploits little of the structural properties or available autograd tools for these models. In this paper, we propose an efficient approach to auto-convert ANN state-space models to linear parameter-varying (LPV) form and solve predictive control problems by successive solutions of linear model predictive problems, corresponding to quadratic programs (QPs). Furthermore, we show how existing ANN identification methods, such as the SUBNET method that uses a state encoder, can provide efficient implementation of MPCs. The performance of the proposed approach is demonstrated via a simulation study on an unbalanced disc system.

Improved crest factor minimization of multisine excitation signals using nonlinear optimization

Automatica

Analysis of quantization noise in FBMC transmitters

Digital Signal Processing

Approximate Time-Optimal Model Predictive Control of a SCARA Robot: A Case Study

Proceedings of the 29th Minisymposium, 2022

This paper investigates, based on a case study of a SCARA robot, how time-optimal point-to-point ... more This paper investigates, based on a case study of a SCARA robot, how time-optimal point-to-point motion can be approximately realized using a model predictive control formulation that has low computational complexity. Time-optimality is realized by an indirect formulation and different objective functions are compared. Using the ℓ1-norm instead of a quadratic penalty mimics time-optimality, however, to reduce computational complexity and evade some of its disadvantages, the Huber-norm is introduced as a velocity penalty while the position is penalized quadratically. The contribution of the sampling rate and the length of the prediction horizon is also examined, as the sampling rate poses a limit on the available computation time, while the prediction horizon influences computational complexity. Simulations were carried out in a MATLAB environment using the CasADi toolbox.

Optimization of Hopping DFT for FS-FBMC Receivers

Signal Processing, 2021

Analysis of Fixed-Point Quantization Noise in Multicarrier Transmitter Schemes

2022 32nd International Conference Radioelektronika (RADIOELEKTRONIKA)

Multicarrier Modulation Schemes for 5G Wireless Access

ECTI Transactions on Computer and Information Technology (ECTI-CIT)

The 5G wireless access technology will supersede its predecessor, 4G, in the current decade, at f... more The 5G wireless access technology will supersede its predecessor, 4G, in the current decade, at first coexisting with it and later as a standalone technology. This work examines and compares the performance of the following orthogonal multicarrier schemes: Cyclic Prefix Orthogonal Frequency Division Multiplexing (CP-OFDM), Windowed Orthogonal Frequency Division Multiplexing (W-OFDM), Filtered Orthogonal Frequency Division Multiplexing (F-OFDM), Universal Filtered Multi-Carrier (UFMC), and Filter Bank Multi-Carrier (FBMC). The system architecture of each scheme is investigated while considering the performance in fading channel models. The simulation was performed using a standard set of parameters, and the performance was appraised based on Power Spectral Density (PSD), Peak to Average Power Ratio (PAPR), Complementary Cumulative Distribution Function (CCDF) of PAPR, Bit Error Rate (BER), and Signal to Noise Ratio (SNR). In addition, a comprehensive analysis is presented concerning ...

Analysis of Quantization Noise in FFT Algorithms for Real-Valued Input Signals

2022 32nd International Conference Radioelektronika (RADIOELEKTRONIKA)

Overview and Complexity Evaluation of FBMC Transmitter Architectures

Infocommunications journal

Computational complexity is one of the key factors considered for evaluating transmitter performa... more Computational complexity is one of the key factors considered for evaluating transmitter performance of future 5G applications. In this contribution we have chosen Filter Bank MultiCarrier (FBMC) as it is the most possible candidate to replace/coexist with the Orthogonal Frequency Division Multiplexing (OFDM) modulation. In the literature two main design approaches can be found for FBMC: Frequency Spreading (FS) and PolyPhase Network (PPN). From these two structures numerous schemes were derived. These schemes are studied and the complexity (real multiplications and additions) for each scheme is compared. Based on the complexity calculations, the simulation results show that PPN has a better complexity performance compared with FS. Also, the alternative PPN schemes have significant improvement in complexity compared to the standard PPN.

FBMC Transmitters with Reduced Complexity

Radioengineering, 2018

Filter Bank MultiCarrier (FBMC) modulation is currently considered as one of the key enablers for... more Filter Bank MultiCarrier (FBMC) modulation is currently considered as one of the key enablers for future 5G technologies. In the literature, two approaches are applied for the modulation of FBMC signals: Frequency Spreading (FS) and PolyPhase (PP) implementation. The complexity requirements of FBMC transmitters is considered to be one of the key research fields. In this paper various FBMC implementations are compared in terms of complexity and quantization error. An alternative design approach is suggested: the two full size Inverse Fast Fourier Transforms (IFFTs) in the standard PP can be replaced by two half size IFFTs taking advantage of real valued data processing. It is shown that the complexity of the design will be almost reduced by half. Furthermore, the proposed alternative method has the lowest quantization error among the investigated transmitter architectures, which is a key issue in hardware with low precision arithmetics.

Cognitive radios

R–DFT-based Parameter Estimation for WiGig

Periodica Polytechnica Electrical Engineering and Computer Science, 2017

In this paper we present parameter estimation methods for IEEE 802.11ad transmission to estimate ... more In this paper we present parameter estimation methods for IEEE 802.11ad transmission to estimate the frequency offset value and channel impulse response. Furthermore a less known low complexity signal processing architecture – the Recursive Discrete Fourier Transform (R-DFT) – is applied which may improve the estimation results. The paper also discusses the R-DFT and its advantages compared to the conventional Fast Fourier Transform.

Software implementation of the Recursive Discrete Fourier Transform

2017 27th International Conference Radioelektronika (RADIOELEKTRONIKA)

The Discrete Fourier Transform is one of the fundamental operations in digital signal processing.... more The Discrete Fourier Transform is one of the fundamental operations in digital signal processing. This paper presents a software based implementation of the less known Recursive Discrete Fourier Transform on the PC x86 architecture and Microchip PIC30 microcontroller. The results are compared with an efficient/optimized Fast Fourier Transform implementation. Both algorithms require complex operations with real valued adders and multipliers, thus a complex result has to be calculated separately for the real and imaginary parts. During the implementation a floating-point number representation is applied. The comparison is performed based on the required resources and computational time.

Software and Hardware Solutions for Channel Estimation based on Cyclic Golay Sequences

Radioengineering, Sep 15, 2016

This paper presents channel estimation methods based on cyclic complementary Golay sequences. Fir... more This paper presents channel estimation methods based on cyclic complementary Golay sequences. First, the conventional Golay correlator is investigated, then a frequency domain approach using Discrete Fourier Transform (DFT) is provided. A complex valued fast Golay correlator is introduced which can be used for the estimation of complex valued channel impulse response. Furthermore, this paper presents the Recursive DFT (R-DFT), a signal processing architecture which may be beneficial compared to the wellknown Fast Fourier Transform (FFT). The R-DFT is able to efficiently calculate a point-by-point block spectra of the input signal, which makes it suitable for hardware implementation. Throughout the paper, the R-DFT is applied and it is compared to the conventional estimation methods. Finally, the efficiency of the proposed schemes is compared through simulations based on the 60 GHz WiGig and the COST 207 standard, applying various channel models.

MIMO Communication Measurements in Small Cell Scenarios at 28 GHz

IEEE Transactions on Antennas and Propagation, Jul 1, 2021

Massive multiple-input-multiple-output (MIMO) systems operating in the centimeter-wave (cmWave) a... more Massive multiple-input-multiple-output (MIMO) systems operating in the centimeter-wave (cmWave) and millimeter-wave (mmWave) region offer huge spectral efficiencies, which enables to satisfy the urgent need for higher data rates in mobile communication networks. However, the proper design of those massive MIMO systems first requires a deep understanding of the underlying wireless propagation channel. Therefore, we present a fully digital MIMO measurement system operating around 28 GHz. The system enables to take fast subsequent snapshots of the complex MIMO channel matrix. Based on this method, we statistically analyze the time-dependent channel behavior, the achievable signal quality and spectral efficiency, as well as the channel eigenvalue profile. Furthermore, the presented calibration approach for the receiver enables an estimation of the dominant absolute angle of arrival (AoA) and allows us to draw conclusions about the line-of-sight (LOS) dominance of the scenario. In total, 159 communication measurements over 20 s are conducted in three different small cell site scenarios to investigate the wireless propagation behavior. The measurements reveal the existence of several spatial propagation paths between the mobile transmitter and the base station. Furthermore, an insight into their likelihood in different propagation scenarios is also given.

Sliding Window Evaluation of the Wiener-Hopf Equation

Radioengineering, Jun 12, 2020

This paper presents an efficient method for solving the Wiener-Hopf equation in a sliding window ... more This paper presents an efficient method for solving the Wiener-Hopf equation in a sliding window by calculating the correlation matrices recursively. Furthermore, a novel algorithm is introduced for evaluating the inverse of the auto-correlation matrix-the Recursion with Splitting the Correlation matrix into 4 Blocks for Inversion (RSC4BI)-which can significantly reduce the computational requirements. The presented procedure is optimized for special cases to achieve an efficient implementation which allows faster real-time signal processing or to reduce the response time-e.g. the latency-by distributing the computations over the time. The proposed method is also validated through numerical simulations and hardware implementation.

Low complexity PPN-FBMC Receivers with improved sliding window equalizers

Physical Communication, Oct 1, 2022

Development and validation of a surface profiling system for end of line monitoring of microstructured elastomer seals based on chromatic confocal microscopy

Precision Engineering-journal of The International Societies for Precision Engineering and Nanotechnology, Sep 1, 2022

Quantization noise analysis in FBMC receivers and its effect on the BER performance

Digital Signal Processing

Optimization of the Crest Factor for Complex-Valued Multisine Signals

Radioengineering

Multisine signals are commonly used in the measurement of dynamic systems and wireless channels. ... more Multisine signals are commonly used in the measurement of dynamic systems and wireless channels. For optimal measurements with a high dynamic range, a low Crest Factor (CF) excitation signal is required. In this paper, a modified approach to optimize the crest factor for complex-valued multisine signals is presented. The approach uses a nonlinear optimization method where the real and imaginary parts can also be optimized for low CF. Furthermore, extensions of the real-valued multisine CF optimization methods are presented for complex-valued cases. The proposed methods are validated and compared using simulations. Based on the results it is shown that the novel approach can lead to more optimal signal design and lower CF compared to other techniques for complex-valued multisine signals.

Computationally efficient predictive control based on ANN state-space models

arXiv (Cornell University), Mar 30, 2023

Artificial neural networks (ANN) have been shown to be flexible and effective function estimators... more Artificial neural networks (ANN) have been shown to be flexible and effective function estimators for identification of nonlinear state-space models. However, if the resulting models are used directly for nonlinear model predictive control (NMPC), the resulting nonlinear optimization problem is often overly complex due the size of the network, requires the use of high-order observers to track the states of the ANN model, and the overall control scheme exploits little of the structural properties or available autograd tools for these models. In this paper, we propose an efficient approach to auto-convert ANN state-space models to linear parameter-varying (LPV) form and solve predictive control problems by successive solutions of linear model predictive problems, corresponding to quadratic programs (QPs). Furthermore, we show how existing ANN identification methods, such as the SUBNET method that uses a state encoder, can provide efficient implementation of MPCs. The performance of the proposed approach is demonstrated via a simulation study on an unbalanced disc system.

Improved crest factor minimization of multisine excitation signals using nonlinear optimization

Automatica

Analysis of quantization noise in FBMC transmitters

Digital Signal Processing

Approximate Time-Optimal Model Predictive Control of a SCARA Robot: A Case Study

Proceedings of the 29th Minisymposium, 2022

This paper investigates, based on a case study of a SCARA robot, how time-optimal point-to-point ... more This paper investigates, based on a case study of a SCARA robot, how time-optimal point-to-point motion can be approximately realized using a model predictive control formulation that has low computational complexity. Time-optimality is realized by an indirect formulation and different objective functions are compared. Using the ℓ1-norm instead of a quadratic penalty mimics time-optimality, however, to reduce computational complexity and evade some of its disadvantages, the Huber-norm is introduced as a velocity penalty while the position is penalized quadratically. The contribution of the sampling rate and the length of the prediction horizon is also examined, as the sampling rate poses a limit on the available computation time, while the prediction horizon influences computational complexity. Simulations were carried out in a MATLAB environment using the CasADi toolbox.

Optimization of Hopping DFT for FS-FBMC Receivers

Signal Processing, 2021

Analysis of Fixed-Point Quantization Noise in Multicarrier Transmitter Schemes

2022 32nd International Conference Radioelektronika (RADIOELEKTRONIKA)

Multicarrier Modulation Schemes for 5G Wireless Access

ECTI Transactions on Computer and Information Technology (ECTI-CIT)

The 5G wireless access technology will supersede its predecessor, 4G, in the current decade, at f... more The 5G wireless access technology will supersede its predecessor, 4G, in the current decade, at first coexisting with it and later as a standalone technology. This work examines and compares the performance of the following orthogonal multicarrier schemes: Cyclic Prefix Orthogonal Frequency Division Multiplexing (CP-OFDM), Windowed Orthogonal Frequency Division Multiplexing (W-OFDM), Filtered Orthogonal Frequency Division Multiplexing (F-OFDM), Universal Filtered Multi-Carrier (UFMC), and Filter Bank Multi-Carrier (FBMC). The system architecture of each scheme is investigated while considering the performance in fading channel models. The simulation was performed using a standard set of parameters, and the performance was appraised based on Power Spectral Density (PSD), Peak to Average Power Ratio (PAPR), Complementary Cumulative Distribution Function (CCDF) of PAPR, Bit Error Rate (BER), and Signal to Noise Ratio (SNR). In addition, a comprehensive analysis is presented concerning ...

Analysis of Quantization Noise in FFT Algorithms for Real-Valued Input Signals

2022 32nd International Conference Radioelektronika (RADIOELEKTRONIKA)

Overview and Complexity Evaluation of FBMC Transmitter Architectures

Infocommunications journal

Computational complexity is one of the key factors considered for evaluating transmitter performa... more Computational complexity is one of the key factors considered for evaluating transmitter performance of future 5G applications. In this contribution we have chosen Filter Bank MultiCarrier (FBMC) as it is the most possible candidate to replace/coexist with the Orthogonal Frequency Division Multiplexing (OFDM) modulation. In the literature two main design approaches can be found for FBMC: Frequency Spreading (FS) and PolyPhase Network (PPN). From these two structures numerous schemes were derived. These schemes are studied and the complexity (real multiplications and additions) for each scheme is compared. Based on the complexity calculations, the simulation results show that PPN has a better complexity performance compared with FS. Also, the alternative PPN schemes have significant improvement in complexity compared to the standard PPN.

FBMC Transmitters with Reduced Complexity

Radioengineering, 2018

Filter Bank MultiCarrier (FBMC) modulation is currently considered as one of the key enablers for... more Filter Bank MultiCarrier (FBMC) modulation is currently considered as one of the key enablers for future 5G technologies. In the literature, two approaches are applied for the modulation of FBMC signals: Frequency Spreading (FS) and PolyPhase (PP) implementation. The complexity requirements of FBMC transmitters is considered to be one of the key research fields. In this paper various FBMC implementations are compared in terms of complexity and quantization error. An alternative design approach is suggested: the two full size Inverse Fast Fourier Transforms (IFFTs) in the standard PP can be replaced by two half size IFFTs taking advantage of real valued data processing. It is shown that the complexity of the design will be almost reduced by half. Furthermore, the proposed alternative method has the lowest quantization error among the investigated transmitter architectures, which is a key issue in hardware with low precision arithmetics.

Cognitive radios

R–DFT-based Parameter Estimation for WiGig

Periodica Polytechnica Electrical Engineering and Computer Science, 2017

In this paper we present parameter estimation methods for IEEE 802.11ad transmission to estimate ... more In this paper we present parameter estimation methods for IEEE 802.11ad transmission to estimate the frequency offset value and channel impulse response. Furthermore a less known low complexity signal processing architecture – the Recursive Discrete Fourier Transform (R-DFT) – is applied which may improve the estimation results. The paper also discusses the R-DFT and its advantages compared to the conventional Fast Fourier Transform.

Software implementation of the Recursive Discrete Fourier Transform

2017 27th International Conference Radioelektronika (RADIOELEKTRONIKA)

The Discrete Fourier Transform is one of the fundamental operations in digital signal processing.... more The Discrete Fourier Transform is one of the fundamental operations in digital signal processing. This paper presents a software based implementation of the less known Recursive Discrete Fourier Transform on the PC x86 architecture and Microchip PIC30 microcontroller. The results are compared with an efficient/optimized Fast Fourier Transform implementation. Both algorithms require complex operations with real valued adders and multipliers, thus a complex result has to be calculated separately for the real and imaginary parts. During the implementation a floating-point number representation is applied. The comparison is performed based on the required resources and computational time.