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Aleš Švigelj

Publications and source records attributed to Aleš Švigelj.

3 recordsLinked to original sources

Non-Contiguous Wi-Fi Spectrum for ISAC: Impact on Multipath Delay Estimation

Leveraging channel state information from multiple Wi-Fi bands can improve delay resolution for ranging and sensing when a wide contiguous spectrum is unavailable. However, frequency gaps shape the delay response, introducing sidelobes and secondary peaks that can obscure closely spaced multipath components. This paper examines multipath delay estimation for Wi-Fi-compliant multiband configurations using channel state information (CSI). For a two-path model with unknown complex gains and delays, the Cramér-Rao lower bound (CRLB) for delay separation is derived and analyzed, confirming the benefit of larger frequency aperture, while revealing pronounced, separation-dependent oscillations driven by gap geometry and inter-path coupling. Given the local nature of Cramér-Rao lower bound, the delay response is analyzed next. In the single-path case, the combined subband responses determine how delay-domain sidelobe levels are distributed. The dominant peak spacing is set primarily by the separation between subband center frequencies. In the two-path case, increased aperture sharpens the mainlobe but also intensifies sidelobes and leakage, yielding competing peaks and, in some regimes, a dominant peak shifted from the true delay. Finally, a normalized leakage metric is introduced to predict problematic separations and to identify regimes where local Cramér-Rao lower bound analysis does not capture practical peak-leakage behavior in delay estimation.

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Radio technologies for environment-aware wireless communications

In this paper, we critically review the potential of today's terrestrial wireless communication systems including wireless cellular technologies (GSM, UMTS, LTE, NR), wireless local area networks (WLANs), and wireless sensor networks (WSNs), for estimating channel state information (CSI), the ratio between training and information symbols and the rate of channel variation, and the potential use of CSI in environment aware wireless communications. The research reveals, that early communication systems provide means for narrowband channel estimation and the CSI is only available as channel attenuation based on signal level measurements. By increasing the spectral bandwidth of communications, the CSI is estimated in some form of channel impulse response (CIR) in almost all currently used radio technologies, but this information is generally not available outside the communication systems. Also, the CSI is estimated only for the channel with active communications. The new radio technology (NR) offers the possibility of estimating the CIR for non-active channels as well, and thus the possibility of initiating environmentally aware wireless communications.

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Improving CSI-based Massive MIMO Indoor Positioning using Convolutional Neural Network

Multiple-input multiple-output (MIMO) is an enabling technology to meet the growing demand for faster and more reliable communications in wireless networks with a large number of terminals, but it can also be applied for position estimation of a terminal exploiting multipath propagation from multiple antennas. In this paper, we investigate new convolutional neural network (CNN) structures for exploiting MIMO-based channel state information (CSI) to improve indoor positioning. We evaluate and compare the performance of three variants of the proposed CNN structure to five NN structures proposed in the scientific literature using the same sets of training-evaluation data. The results demonstrate that the proposed residual convolutional NN structure improves the accuracy of position estimation and keeps the total number of weights lower than the published NN structures. The proposed CNN structure yields from 2cm to 10cm better position accuracy than known NN structures used as a reference.

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