Ensuring content security and copyright protection is a critical concern in wireless communication networks. Furthermore, the emergence of services demanding high-band width and very low delay such as online Games, extended reality (XR), Metaverses, etc., Non-Orthogonal Multiple Access (NOMA) is a technology with the potential to enhance the spectral efficiency of fifth-generation (5G) wireless network and beyond. Hence, this paper studies a NOMA-based downlink system that employs intelligent reconfigurable surfaces (IRS) and operates in a physical-layer security environment. Our study also incorporates the utilization of Fountain codes (FCs), all while contending with the presence of a malicious eavesdropper. Furthermore, a cooperative jamming technique is employed to degrade the quality of the eavesdropping channel. The main contribution of this paper is to derive precise closed-form expressions of outage probability (OP), energy efficiency (EE), intercept probability (IP), and average secrecy rate (ASR) for the proposed system. We also develop a Deep Neural Network (DNN) model to evaluate OP, IP, ASR and the average number of time slots (ATS). Subsequently, Monte Carlo simulations are presented as a means to validate the theoretical findings. The simulation results yield the following insights: i) Their primary purpose is to validate the analytical formulas. ii) This research significantly contributes to deepening our understanding of IRS-NOMA systems, providing a foundation for future investigations into practical implementations. iii) We investigate the optimal power allocation factors within the IRS-NOMA framework, offering valuable insights into designing IRS-NOMA systems to achieve reliable and secure communication. iv) The results illustrate the superior performance of IRS-NOMA in comparison to the conventional IRS-Orthogonal Multiple Access (OMA) method.

Nowadays, mobile robot exploration needs a rangefinder to obtain a large number of measurement points to achieve a detailed and precise description of a surrounding area and objects, which is called the point cloud. However, a single point cloud scan does not cover the whole area, so multiple point cloud scans must be acquired and compared together to find the right matching between them in a process called registration method. This method requires further processing and places high demands on memory consumption, especially for small embedded devices in mobile robots. This paper describes a novel method to reduce the burden of processing for multiple point cloud scans. We introduce our approach to preprocess an input point cloud in order to detect planar surfaces, simplify space description, fill gaps in point clouds, and get important space features. All of these processes are achieved by applying advanced image processing methods in combination with the quantization of physical space points. The results show the reliability of our approach to detect close parallel walls with suitable parameter settings. More importantly, planar surface detection shows a 99% decrease in necessary descriptive points almost in all cases. This proposed approach is verified on the real indoor point clouds.

This paper presents the automatic system for the processing of the signals from the frequency modulated interrupted continuous wave (FMICW) radar and describes methods for the primary signal processing. Further, we present methods for the detection of the targets in strong noise. These methods are tested both on the real and simulated signals. The real signals were measured using the developed at the IAP CAS experimental prototype of FMICW radar with operational frequency 35.4 GHz. The measurement campaign took place at the TU Delft, the Netherlands. The obtained results were used for development of the system for the automatic detection and analysis of the targets measured by the FMICW radar.

This paper studies the security and reliability of the power splitting (PS)-based relaying in the Internet of Things (IoT) networks with the help of a jammer. Based on the considered system model, we derive outage probability (OP) and intercept probability (IP) under two distinguished schemes, namely, the static PS relaying (SPSR) scheme and the dynamic PS relaying (DPSR) scheme. More precisely, the PS ratio of the former is a constant number, while the latter is optimally adjusted in order to minimize the OP and counts only on the channel gain of the second hop. Numerical results are provided to not only verify the accuracy of the proposed mathematical framework but also identify the trends of both OP and IP with respect to several important parameters. Our findings unveil that the OP and IP have contradictory behavior with respect to the transmit power and number of sources. Moreover, the performance of the DPSR scheme is superior to that of the SPSR scheme.

The reconfigurable intelligent surfaces (RIS) represent a transformative technology in wireless communication, offering a novel approach to managing and enhancing radio signal propagation. By dynamically adjusting their electromagnetic properties, RIS can significantly improve the performance and efficiency of 5G and beyond communication systems. In this paper, we study a cognitive RIS-aided non-orthogonal multiple access (NOMA) network that serves multiple users and improves spectrum efficiency. Our analysis assumes a secondary network operates under multi-primary user constraints and interference from the primary source. We derive approximation closed-form formulas for outage probability (OP), and system throughput. To obtain further insights, an asymptotic expression for OP is computed by taking into account two power configurations at the source. Additionally, numerical results show the effects of important factors on performance, confirming the accuracy of the theoretical derivation. According to the simulation results, performance by the system under consideration might be improved considerably by combining a RIS and NOMA, particularly when compared to an orthogonal multiple access scheme.

Preprocessed signals from GPS satellites can be used for ionospheric research. Important ionospheric characteristics are for example ionospheric propagation delays and scintillations. These characteristics are important for understanding the ionosphere and showing how the ionosphere reacts to external forces (e.g., the geomagnetic disturbance, solar eclipse etc.). Dual-frequency systems use an approach based on the difference between two pseudoranges. However, this approach has two possible disadvantages: i) the price of the dual frequency receiver is relatively high, and ii) both pseudoranges can affect the obtained results so the operators cannot separately analyze their relative contribution. The objective of the paper is to demonstrate an algorithm for processing data from a GPS receiver. The algorithm does not merge the pseudoranges obtained from different carrier waves. Accordingly, it was decided to use whitening filters to accomplish this task for every frequency separately. Compared with the dual-frequency approach, the obtained results of the newly developed algorithm demonstrate that this algorithm works accurately, and the propagation delays can be estimated independently of the used frequency.