| 1. |
- Nikonowicz, Jakub, et al.
(författare)
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A blind signal samples detection algorithm for accurate primary user traffic estimation
- 2020
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 20:15, s. 1-11
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Tidskriftsartikel (refereegranskat)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.
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| 2. |
- Nikonowicz, Jakub, et al.
(författare)
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Indoor Positioning in 5G-Advanced : Challenges and Solution toward Centimeter- Level Accuracy with Carrier Phase Enhancements
- 2024
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Ingår i: IEEE wireless communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 1536-1284 .- 1558-0687.
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Tidskriftsartikel (refereegranskat)abstract
- Like 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. Therefore, 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 discuss the 5G positioning framework, measurements, and procedures before shifting the focus 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 the ways in which 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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| 3. |
- Nikonowicz, Jakub, et al.
(författare)
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Noise Power Estimators in ISM Radio Environments: Performance Comparison and Enhancement Using a Novel Samples Separation Technique
- 2019
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Ingår i: IEEE Transactions on Instrumentation and Measurement. - 0018-9456 .- 1557-9662. ; 68:1, s. 105-115
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Tidskriftsartikel (refereegranskat)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.
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