Jakub Nikonowicz

2024

1. Jakub Nikonowicz, Aamir Mahmood, Muhammad Ikram Ashraf, Emil Björnson, Mikael Gidlund,
   Indoor Positioning in 5G-Advanced: Challenges and Solution toward Centimeter-Level Accuracy with Carrier Phase Enhancements,
   IEEE Wireless Communications, Vol. 31, No. 4, 2024, pp. 268-275,
   EndNoteCitation
   
   
2. Jakub Nikonowicz, Mieczysław Jessa, Łukasz Matuszewski,
   Computationally Efficient Wideband Spectrum Sensing through Cumulative Distribution Function and Machine Learning,
   Journal of Communications Software and Systems, Vol. 20, No. 1, 2024, pp. 38-46,
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2023

3. Jakub Nikonowicz, Mieczysław Jessa,
   Wideband Spectrum Sensing Utilizing Cumulative Distribution Function and Machine Learning,
   31st International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2023, 21-23.09.2023, Split, Croatia, Croatia, 2023, pp. 1-6,
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2021

4. Paweł Kubczak, Wiktor Woźniak, Jakub Nikonowicz, Łukasz Matuszewski, Mieczysław Jessa,
   An Online Platform for Testing and Evaluating Random Number Generators,
   29th International Conference on Software, Telecommunications and Computer Networks, IEEE, Split, Hvar, Croatia, 23-25 Sept. 2021,
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   Abstract
   

   This article introduces a new online platform for testing binary random number generators. The growing share of low-complex devices in IoT networks increases the demand for basic authorization and authentication tools, the critical block of which is a secure random number generator. Communication devices, therefore, require designers to carry out time-consuming tests and acquire specialist knowledge of statistical testing in evaluation of their results. To meet the current requirements, we have created a test platform to assess the quality of random strings produced by the generator. The presented solution, based on the proprietary evaluation metric, provides feedback on the properties of the uploaded random sequences. Clear interface provides ease of use and by machine learning in the platform’s backend, along with the increase of processed data, the improved quality of the interpretation delivered by the system is ensured. The operation of the platform has been confirmed experimentally, based on the analysis of hardware generators producing random strings with known properties.

5. Łukasz Matuszewski, Jakub Nikonowicz, Paweł Kubczak, Wiktor Woźniak,
   Physical Unclonable Function Based on the Internal State Transitions of a Fibonacci Ring Oscillator,
   Sensors, Vol. 21, No. 11, 2021, pp. 3920/1-3920/13,
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   Abstract
   

   This article introduces a new class of physical unclonable functions (PUFs) based on the Fibonacci ring oscillator (FIRO). The research conducted here proves that before reaching the desired randomness, the oscillator shows a certain degree of repeatability and uniqueness in the initial sequence of internal state transitions. The use of an FIRO in conjunction with the restart method makes it possible to obtain a set of short boot sequences, which are processed with an innovative feature extraction algorithm that enables reliable device identification. This approach ensures the reuse of the existing random number generator (RNG), rather than multiplying ring oscillators in a dedicated structure. Moreover, the algorithm for the recovery of the device key from the boot set can be successfully implemented in the authorizing center, thus significantly releasing the resources of authorized low-complexity devices. The proposed methodology provides an easily obtainable key with identifiability, which was proven experimentally on FPGAs from different manufacturers.

6. Jakub Nikonowicz, Łukasz Matuszewski, Paweł Kubczak,
   Sequence Alignment Algorithm for Statistical Similarity Assessment,
   IEEE Access, Vol. 9, 2021, pp. 102153-102160,
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   Abstract
   

   This paper presents a new approach to statistical similarity assessment based on sequence alignment. The algorithm performs mutual matching of two random sequences by successively searching for common elements and by applying sequence breaks to matchless elements in the function of exponential cost. As a result, sequences varying significantly generate a high-cost alignment, while for low-cost sequences the introduced interruptions allow inferring the nature of sequences dependence. The most important advantage of the algorithm is an easy interpretation of the obtained results based on two parameters: stretch ratio and stretch cost. The operation of the method has been simulation tested and verified with the use of real data obtained from hardware random number generators. The proposed solution ensures simple implementation enabling the integration of hardware solutions, and operation based on only two sequences of any length predisposes the method to online testing.

7. Jakub Nikonowicz, Mieczysław Jessa,
   Gaussianity Testing as an Effective Technique for Detecting Discontinuous Transmission in 5G Networks,
   IEEE Access, Vol. 9, 2021, pp. 22186-22194,
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   Abstract
   

   The paper investigates statistical distribution testing-based detection methods in an intermittent signal detection scenario. The relevance of the research is driven by 5G networks based on packet transmission, incorporating the concept of cognitive radio and adapting spectrum detection methods from Long Term Evolution (LTE) Licensed-Assisted Access (LAA). The conducted study refers to the recently proposed methods based on testing goodness-of-fit (GoF) of statistical distributions, which are compared with a conventional energy detector. The authors examine the applicability of well-known GoF methods in intermittent transmission, as they require reconsideration in 5G communication systems, and investigate the behavior of the innovative energy-based GoF. The experiments are carried out for different transmitter activity factors, i.e., channel occupancy and signal-to-noise ratio (SNR), demonstrating the superiority of the GoF-based methods in general and particularly the invented GoF test over other energy-based detectors for discontinuous signals detection.

2020

8. Jakub Nikonowicz, Aamir Mahmood, Mikael Gidlund,
   A Blind Signal Samples Detection Algorithm for Accurate Primary User Traffic Estimation,
   Sensors, Vol. 22, No. 15, 2020, pp. 4136/1-4136/11,
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   Abstract
   

   The energy detection process for enabling opportunistic spectrum access in dynamic primary user (PU) scenarios, where PU changes state from active to inactive at random time instances, requires the estimation of several parameters ranging from noise variance and signal-to-noise ratio (SNR) to instantaneous and average PU activity. A prerequisite to parameter estimation is an accurate extraction of the signal and noise samples in a received signal time frame. In this paper, we propose a low-complexity and accurate signal samples detection algorithm as compared to well-known methods, which is also blind to the PU activity distribution. The proposed algorithm is analyzed in a semi-experimental simulation setup for its accuracy and time complexity in recognizing signal and noise samples, and its use in channel occupancy estimation, under varying occupancy and SNR of the PU signal. The results confirm its suitability for acquiring the necessary information on the dynamic behavior of PU, which is otherwise assumed to be known in the literature.

9. Adrian Dziembowski, Dawid Mieloch, Olgierd Stankiewicz, Jakub Nikonowicz, Marek Domański,
   Noise modelling in TMIV,
   MPEG131/m54895, Rennes, France, October 2020,
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2019

10. Jakub Nikonowicz, Aamir Mahmood, Emiliano Sisinni, Mikael Gidlund,
    Noise Power Estimators in ISM Radio Environments: Performance Comparison and Enhancement Using a Novel Samples Separation Technique,
    IEEE Transactions on Instrumentation and Measurement, Vol. 68, No. 1, 2019, pp. 105-115,
    EndNoteCitationDOI
    
    Abstract
    

    Noise power estimation is central to efficient radio resource allocation in modern wireless communication systems. In the literature, there exist many noise power estimation methods that can be classified based on underlying theoretical principle; the most common are spectral averaging, eigenvalues of sample covariance matrix, information theory, and statistical signal analysis. However, how these estimation methods compare against each other in terms of accuracy, stability, and complexity is not well studied, and the focus instead remains on the enhancement of individual methods. In this paper, we adopt a common simulation methodology to perform a detailed performance evaluation of the prominent estimation techniques. The basis of our comparison is the signal-to-noise ratio estimation in the simulated industrial, scientific and medical band transmission, while the reference noise signal is acquired from an industrial production plant using a software-defined radio platform, USRP-2932. In addition, we analyze the impact of different techniques for noise-samples' separation on the estimation process. As a response to defects in the existing techniques, we propose a novel noise-samples' separation algorithm based on the adaptation of rank-order filtering. Our analysis shows that the proposed solution, apart from its low complexity, has a very good root-mean-squared error of 0.5 dB and smaller than 0.1-dB resolution, thus achieving a performance comparable with the methods exploiting information theory concepts.

11. Paweł Kubczak, Jakub Nikonowicz, Łukasz Matuszewski,
    Kalman Filter Design for Fast Synchronization of a High-Stability Rubidium Oscillator,
    2019 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), IEEE, Poznan, Poland, 18-20 Sept. 2019,
    EndNoteCitationDOI
    
    Abstract
    

    The article briefly describes the methodology of designing a Kalman filter that it is used in the phase lock loop (PLL). At the beginning the tools and the experimental environment are discussed, especially the structure of the synchronization loop. First, the characteristic of the 1PPS GNSS reference signal is obtained using superposition by gathering data when the oscillator is locked to GPS. This data is used to calculate a covariance matrix of the measurement noise for the Kalman filter. Next, a signal without noise from a very stable frequency source is applied as a reference signal, and the identification experiment of the oscillator is executed. Based on the identification data, one, two-, three- and four-dimensional space-state models of the rubidium clock are created and the process noise covariance matrix for the Kalman filter is calculated. At the end, the quality of Kalman filter tracking is examined. For this purpose, MSE between the real behavior of the phase and the estimation provided by the filter is calculated. Finally, the optimal dimensionality of the model is discussed. It is also shown how much the estimations of the phase prediction in Kalman filter can be trusted and how to adjust the process noise covariance matrix properly.

2018

12. Jakub Nikonowicz, Paweł Kubczak, Łukasz Matuszewski,
    Impact of the Decision Function on the Overall Performance of an Energy- and Entropy-Based Hybrid Detector,
    International Conference on Signals and Electronic Systems (ICSES 2018), IEEE, Krakow, Poland, 10-12 Sept. 2018, pp. 114-117,
    EndNoteCitationDOI
    
    Abstract
    

    The basic challenge in weak signal detection is not only to bring the signal to a useful form, but also to determine its presence in the surrounding background noise. One of the well-known and most commonly used methods is energy detection, extended in the following years to compound, hybrid solutions. In this article, the authors have shown that the improvement of detection can be achieved not only by extending already complex algorithms by additional processing branches, but simply by choosing a better decision criterion. For this purpose, the authors have defined a simulation model, which uses machine learning to redefine previously adopted decision thresholds and improve detection efficiency. The presented simulation results show significant improvement in detector performance in comparison with the classical approach.

13. Jakub Nikonowicz, Mieczysław Jessa,
    Stable Field Detection as a New Spectrum Sensing Technique-Performance Evaluation Under Real Radiofrequency Background Noise,
    International Conference on Signals and Electronic Systems (ICSES 2018), IEEE, Krakow, Poland, 10-12 Sept. 2018, pp. 201-205,
    EndNoteCitationDOI
    
    Abstract
    

    Detection of unknown and weak signals has become a study of particular importance as a consequence of the ongoing development in digital sensing technologies. Among well-known methods, the one most commonly used is energy detection. In this paper the efficiency of the conventional energy detection is compared with the efficiency of the recently proposed, so-called stable field detection. The comparison concerns pseudorandom, additive white Gaussian noise (AWGN) produced in the simulation experiment and real radiofrequency (RF) background noise measured in industrial, scientific and medical (ISM) band transmission. The background noise samples were acquired from a laboratory room using a software-defined radio platform NI USRP-2900. The reasonability of the proposed detection approach is confirmed by the results achieved in the modeled system.

2017

14. Jakub Nikonowicz, Mieczysław Jessa,
    Stable field detection as a novel method for blind sensing of weak radio signals,
    2nd International Conference on Astrophysics and Particle Physics, San Antonio, USA, 2017, pp. 104-104,
    EndNoteCitationDOI
    
    Abstract
    

    Since the discovery of space radio waves in the early 1930s, most astronomical objects have been perceived as radio wavessources. Radio-astronomy observations ultimately consist in measuring the energy received from a distant source, withparticular emphasis on the detection of unknown and weak signals. The most commonly used blind detection method relieson energy detection with noise power estimation. The variability of the radio environment, however, greatly complicates theentire detection process. In order to solve the problem of detection in varying noise conditions, we propose a novel method ofblind signal detection called Stable Field Detection (SFD), which does not require any knowledge of the noise variance. Theproposed method uses the bin value distribution of the received signal’s power spectrum density and the moving average. Itrefers to the mutual relations between the distributions of random variables to extract more information from the spectrumthan normal energy detection. As a result, SFD operates on thresholding Gaussian distribution, which makes it as easy to useas energy detection, but remains much more effective. The simulation results for radio pulses show that the performance ofthe method is significantly improved under the proposed scheme. With regard to weak signals, when compared to the energydetection, the lower limit of the permissible signal-to-noise ratio has been decreased by 4dB. At the same time, the proposedsolution maintains low O (nlogn) computational complexity. SFD is considered a new, effective and simple software defineddetector that addresses the challenges of modern astronomy.

15. Jakub Nikonowicz, Mieczysław Jessa,
    A novel method of blind signal detection using the distribution of the bin values of the power spectrum density and the moving average,
    Digital Signal Processing, Vol. 66, 2017, pp. 18-28,
    EndNoteCitationDOI
    
    Abstract
    

    Signal detection in additive white Gaussian noise (AWGN) is one of the long-term developments driving the evolution of many different fields of science and technology, with important applications in telecommunications, medicine and astronomy. In this paper, we propose a novel method of blind signal detection that does not require knowledge of the noise variance. This method uses the distribution of the bin values of the power spectrum density of the received signal and the moving average (MAV). The simulation results for radio pulses show that the spectrum sensing performance is significantly improved under the proposed scheme compared to that of known blind signal detection methods.

2016

16. Jakub Nikonowicz, Paweł Kubczak, Łukasz Matuszewski,
    Hybrid detection based on energy and entropy analysis as a novel approach for spectrum sensing,
    International Conference on Signals and Electronic Systems (ICSES 2016), IEEE, Krakow, Poland, 5-7 Sept. 2016, pp. 206-211,
    EndNoteCitationDOI
    
    Abstract
    

    Detection of weak signals has become the study of particular importance as a consequence of the ongoing technology development in many different fields such as more efficient radio communication or reaching further exploration in astrophysics. Its main task still remains spectrum sensing, which is detecting the weak signals hidden in the noise. Among the well-known methods most commonly used remains energy detection, extended in the following years to double thresholding or cooperative sensing by multiple receivers. The authors of the article propose the innovative hybrid detection, where cooperation is realized on the basis of two independent methods within a single receiver. In the studied case of detection, the energy associated with equally simple analysis of entropy allows to improve the detection results in a changing radio environment. Reasonability of the proposed approach is confirmed by the results achieved in experimental detection system.

17. Jakub Nikonowicz, Mieczysław Jessa,
    Blind detection methods in cognitive radio - an overview and comparison,
    2016 10th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP), IEEE, Prague, Czech Republic, 20-22 July 2016, pp. 206-211,
    EndNoteCitationDOI
    
    Abstract
    

    Cognitive radio (CR) is one of the most important challenges in contemporary communication. Because cognitive technologies are based on matching transmission parameters to the surrounding radio environment, several practical problems related to weak signal detection must be solved. These include, e.g., uncertainty of the noise variance value, the changes of this value in time and space, limited hardware resources or time of detection. All of these factors can seriously degrade system performance. The search for practically useful solutions of the encountered difficulties is therefore very important for the successful development and implementation of CR technology. This article provides an overview and comparison of chosen blind detection methods proposed for use in CR receivers. The comparison is based on simulation results, and the methods are compared in terms of detection efficiency, time complexity and robustness to changes in transmission parameters.