arXiv subjects

Jakub Nikonowicz

Publications and source records attributed to Jakub Nikonowicz.

6 recordsLinked to original sources

arXiv2026

Learning-Based Phase Estimation for Multi-Frequency Carrier Phase Ranging under Structured Multipath Conditions

Carrier-phase (CP) ranging is a key enabler of high-precision positioning in modern wireless systems. In multi-frequency OFDM-based sensing, phase observations across subcarriers provide information about the underlying propagation geometry. However, in realistic industrial and urban environments, these observations exhibit non-Gaussian and asymmetric characteristics due to deterministic multipath components, violating standard circular statistical assumptions. In this work, we analyze CP-based ranging as an estimation problem over circular phase observations. We show that conventional model-based estimators, such as circular averaging under von Mises assumptions, become biased under 3GPP-compliant propagation conditions. Using a QuaDRiGa-based simulation framework, we evaluate empirical phase distributions in Industrial Factory (InF) and Urban Microcell (UMi) scenarios and quantify their deviation from classical statistical models. To address these limitations, we propose a learning-based estimator that operates directly on empirical phase distributions without assuming a predefined statistical model. Experimental results show improved accuracy compared to classical estimators, particularly under multipath conditions.

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arXiv2025

A Robust 5G Terrestrial Positioning System with Sensor Fusion in GNSS-denied Scenarios

This paper presents a terrestrial localization system based on 5G infrastructure as a viable alternative to GNSS, particularly in scenarios where GNSS signals are obstructed or unavailable. It discusses network planning aimed at enabling positioning as a primary service, in contrast to the traditional focus on communication services in terrestrial networks. Building on a network infrastructure optimized for positioning, the paper proposes a system that leverages carrier phase (CP) ranging in combination with trilateration to localize the user within the network when at least three base stations (BSs) provide line-of-sight (LOS) conditions. Achieving accurate CP-based positioning requires addressing three key challenges: integer ambiguity resolution, LOS/NLOS link identification, and localization under obstructed LOS conditions. To this end, the system employs a multi-carrier CP approach, which eliminates the need for explicit integer ambiguity estimation. Additionally, a deep learning model is developed to identify NLOS links and exclude them from the trilateration process. In cases where LOS is obstructed and CP ranging becomes unreliable, the system incorporates an error-state extended Kalman filter to fuse complementary data from other sensors, such as inertial measurement units (IMUs) and cameras. This hybrid approach enables robust tracking of moving users across diverse channel conditions. The performance of the proposed terrestrial positioning system is evaluated using the real-world KITTI dataset, featuring a moving vehicle in an urban environment. Simulation results show that the system can achieve a positioning error of less than 5 meters in the KITTI urban scenario--comparable to that of public commercial GNSS services--highlighting its potential as a resilient and accurate solution for GNSS-denied environments.

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arXiv2024

Indoor Positioning in 5G-Advanced: Challenges and Solution towards Centimeter-level Accuracy with Carrier Phase Enhancements

After robust connectivity, precise positioning is evolving into an innovative component of 5G service offerings for industrial use-cases and verticals with challenging indoor radio environments. In this direction, the 3GPP Rel-16 standard has been a tipping point in specifying critical innovations, followed by enhancements in Rel-17 and Rel-18. In this article, we elaborate on the 5G positioning framework, measurements, and procedures before shifting the focus mainly to recently identified carrier-phase (CP) measurements in Rel-18 as a complementary measure for time- and angular-based positioning methods. We discuss the associated challenges and potential solutions for exploiting CP, including integer ambiguity, multipath sensitivity, and signaling aspects. Furthermore, we study how phase-continuous reference signaling can counter noisy phase measurements using realistic simulations to achieve centimeter-level accuracy in indoor factory (InF) scenarios.

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arXiv2021

Sequence Alignment Algorithm for Statistical Similarity Assessment

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.

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arXiv2020

A Blind Signal Separation Algorithm for Energy Detection of Dynamic PU Signals

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 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 letter, we propose a low-complexity and accurate signal separation 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.

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arXiv2017

Quantitative Benchmarks and New Directions for Noise Power Estimation Methods in ISM Radio Environment

Noise power estimation is a key issue in modern wireless communication systems. It allows resource allocation by detecting white spectral spaces effectively, and gives control over the communication process by adjusting transmission power. Thus far, the proposed estimation methods in the literature are based on spectral averaging, eigenvalues of sample covariance matrix, information theory, and statistical signal analysis. Each method is characterized by certain stability, accuracy and complexity. However, the existing literature does not provide an appropriate comparison. In this paper, we evaluate the performance of the existing estimation techniques intensively in terms of stability and accuracy, followed by detailed complexity analysis. The basis for comparison is signal-to-noise ratio (SNR) estimation in simulated industrial, scientific and medical (ISM) band transmission. The source of used background distortions is complex noise measurement, recorded by USRP-2932 in an industrial production area. Based on the examined solutions, we also analyze the influence of noise samples separation techniques on the estimation process. As a response to the defects in the used methods, we propose a novel noise samples separation algorithm based on the adaptation of rank order filtering (ROF). In addition to simple implementation, the proposed method has a very good 0.5 dB root-mean-squared error (RMSE) and smaller than 0.1 dB resolution, thus achieving a performance that is comparable with the methods exploiting information theory concepts.

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