AEGIS – Mobile Device for Generating Electromagnetic Curtain for Special Applications and Countering the Threats of RCIED

In the article the concept, design and realization of the technological demonstrator of a mobile device for generating an electromagnetic curtain (with a name AEGIS) were presented, both in the hardware and software areas. The device is designed to block the radio communication which allow detonating the Radio Controlled Improvised Explosive Devices (RCIEDs). The preliminary laboratory tests of the demonstrator for generating the jamming signal, that were presented in the paper, aimed at assessing the correctness of the device operation and verification of generated signal parameters. On the basis of the obtained results, the ability to jam the cellular systems as well as other radio devices operating in the frequency band from 400 MHz to 2700 MHz was assessed

IoT protocols, architectures, and applications

The proliferation of embedded systems, wireless technologies, and Internet protocols have made it possible for the Internet-of-things (IoT) to bridge the gap between the physical and the virtual world and thereby enabling monitoring and control of the physical environment by data processing systems. IoT refers to the inter-networking of everyday objects that are equipped with sensing, computing, and communication capabilities. These networks can collaborate to autonomously solve a variety of tasks. Due to the very diverse set of applications and application requirements, there is no single communication technology that is able to provide cost-effective and close to optimal performance in all scenarios. In this chapter, we report on research carried out on a selected number of IoT topics: low-power wide-area networks, in particular, LoRa and narrow-band IoT (NB-IoT); IP version 6 over IEEE 802.15.4 time-slotted channel hopping (6TiSCH); vehicular antenna design, integration, and processing; security aspects for vehicular networks; energy efficiency and harvesting for IoT systems; and software-defined networking/network functions virtualization for (SDN/NFV) IoT

An Off-Body Narrowband and Ultra-Wide Band Channel Model for Body Area Networks in a Ferryboat Environment

In the article an off-body narrowband and ultra-wide band channel model for body area networks in a ferryboat environment is described. Considering the limited number of publications there is a need to develop an off-body channel model, which will facilitate the design of radio links, both from the multimedia services provider and the security point of view, for body area networks in this atypical environment. A mobile heterogeneous measurement stand, using radio distance measurements, which consists of three types of devices: miniaturized mobile nodes, stationary reference nodes, and a data acquisition server, was developed. A detailed analysis of both radio channels’ parameters was carried out. An analysis of system loss for off-body communication, including mean system loss, large-scale fading (corresponding to body shadowing), and small-scale fading (associated with the multipath phenomenon), both for 868 MHz narrowband and for 6489 MHz ultra-wide band channels, was performed. A statistical analysis of the obtained system loss model parameters was also carried out; good fit to the empirical data is observed

Person Tracking in Ultra-Wide Band Hybrid Localization System Using Reduced Number of Reference Nodes

In this article a novel method of positional data integration in an indoor hybrid localization system combining inertial navigation with radio distance measurements is presented. A point of interest is the situation when the positional data and the radio distance measurements are obtained from less than thee reference nodes and it is impossible to unambiguously localize the moving person due to undetermined set of positional equations. The presented method allows to continuously provide localization service even in areas with disturbed propagation of the radio signals. Authors performed simulation and measurement studies of the proposed method to verify the precision of position estimation of a moving person in an indoor environment. It is worth noting that to determine the simulation parameters and realize the experimental studies the hybrid localization system demonstrator was developed, combining inertial navigation and radio distance measurements. In the proposed solution, results of distance measurements taken to less than three reference nodes are used to compensate the drift of the position estimated using the inertial sensor. In the obtained simulation and experimental results it was possible to reduce the localization error by nearly 50% regarding the case when only inertial navigation was used, additionally keeping the long term root mean square error at the level of ca. 0.50 m. That gives a degradation of localization precision below 0.1 m with respect to the fusion Kalman filtration when four reference nodes are present

Software-Defined NB-IoT Uplink Framework—The Design, Implementation and Use Cases

In the radiocommunication area, we may observe a rapid growth of new technology, such as 5G. Moreover, all the newly introduced radio interfaces, e.g., narrowband Internet of Things (NB-IoT), are strongly dependent on the software. Hence, the radiocommunication software development and optimization, as well as the 3GPP technical specification, should be introduced at the academic level of education. In this paper, a software-defined NB-IoT uplink framework in the field of design is presented, as well as its realization and potential use cases. The framework may be used as an academic tool for developing, investigating, and optimizing the digital transmitter paths. The proposed realization is focused on the key elements in the physical layer of the NB-IoT interface used in the sensor devices. Furthermore, the paper also highlights the need of the data processing optimization to minimize the power consumption and usage of the resources of the NB-IoT node during transmitting gathered telemetric data

Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks

In this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on the basis of the measurement data for dynamic scenarios in an indoor environment. The obtained results clearly prove the validity of the proposed DL approach in the UWB WBANs and high (over 98.6% for most cases) efficiency for LOS and NLOS conditions classification

Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning

Following the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides a significant gain (almost 40%) with 10.7% compared to the linear model with the lowest RMSE (Root Mean Squared Error) 17.01%. The solution can be adopted as a part of the data allocation algorithm implemented in the telemetry devices equipped with the 4G radio interface, or, after the adjustment, the NB-IoT (Narrowband Internet of Things), to maximize the reliability of the services in harsh indoor or urban environments. Presented results also prove the existence of the inverse proportional dependence between the number of hidden layers and the number of historical samples in terms of the obtained RMSE. The increase of the historical data memory allows using models with fewer hidden layers while maintaining a comparable RMSE value for each scenario, which reduces the total computational cost

A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks

In the article, a novel bitrate adaptation method for data streams allocation in heterogeneous Wireless Body Area Networks (WBANs) is presented. The efficiency of the proposed algorithm was compared with other known algorithms of data stream allocation using computer simulation. A dedicated simulator has been developed using results of measurements in the real environment. The usage of the proposed adaptive data streams allocation method by transmission rate adaptation based on radio channel parameters can increase the efficiency of resources’ usage in a heterogeneous WBANs, in relation to fixed bitrates transmissions and the use of well-known algorithms. This increase of efficiency has been shown regardless of the mobile node placement on the human body