A defensive strategy against beam training attack in 5G mmWave networks for manufacturing

Millimeter-wave (mmWave) carriers are an essential building block of fifth-generation (5G) systems. Satisfactory performance of the communications over the mmWave spectrum requires an alignment between the signal beam of the transmitter and receiver, achieved via beam training protocols. Nevertheless, beam training is vulnerable to jamming attacks, where the attacker intends to send jamming signals over different spatial directions to confuse legitimate nodes. This paper focuses on defending against this attack in smart factories where a moving Automated Guided Vehicle (AGV) communicates with a base station via a mmWave carrier. We introduce a defensive strategy to cope with jamming attacks, including two stages: jamming detection and jamming mitigation. Developed based on autoencoders, both algorithms can learn the characteristics/features of the received signals at the AGV. They can be employed consecutively before performing the downlink data transmission. In particular, once a jamming attack is identified, the jamming mitigation can be utilized to retrieve the corrupted received signal strength vector, allowing a better decision during the beam training operation. In addition, the proposed algorithm is straightforward and fully compliant with the existing beam training protocols in 5G New Radio. The numerical results show that not only the proposed defensive strategy can capture more than 80% of attack events, but it also improves the average signal-to-interference-plus-noise-ratio significantly, i.e., up to 15 dB

Experimental Analysis of 5G NR for Indoor Industrial Environments

Private 5G networks for industrial users are emerging as one of the leading advanced 5G use cases. This timely work presents a comprehensive experimental analysis of a private 5G network conducted in sparse and dense industrial environments at sub-6 GHz. Measured results of the over-the-air error vector magnitude (EVM) are provided, considering signal-to-noise ratio (SNR) for different 5G new radio modulation and coding schemes (MCSs), bandwidths (BWs) and numerologies (subcarrier spacings) using omnidirectional or directional antenna configurations at the transmitter (TX) and the receiver (RX). Channel sounding measurements are also conducted to characterise the channels in terms of root mean square (RMS) delay spread. The measurement results show that channels in the dense industrial environment have greater RMS delay spreads than in the sparse industrial environment due to strong reflected or scattered multipath components with significant delays. This results in higher EVMs and bit error rates (BERs), i.e., as the RMS delay spread increases, a higher SNR is required to meet the EVM limits. It is also observed that using directional antennas at the TX and RX in both environments reduces the RMS delay spread and hence the inter-symbol interference and the EVM. This allows higher MCS modes (e.g., 64 QAM and 256 QAM) to be used for reliable data transmission, significantly improving the bandwidth efficiency and reducing the latency. When evaluating system performance for different BWs and numerologies, using a lower BW and numerology provides a better system performance (lower EVMs and BERs), especially in dense industrial environments

Sub-6 GHz channel modelling and evaluation in indoor industrial environments

This paper presents sub-6 GHz channel measurements using a directional antenna at the transmitter and a directional or omnidirectional antenna at the receiver at 4.145 GHz in sparse and dense industrial environments for a line-of-sight scenario. Furthermore, the first measured over-the-air error vector magnitude (EVM) results depending on different 5G new radio modulation and coding schemes (MCSs of16 QAM, 64 QAM and 256 QAM) are provided. From the measurement campaigns, the path loss exponents (PLE) using a directional and an omnidirectional antenna at the receiver in the sparse and the dense environment are 1.24/1.39 and 1.35/1.5, respectively. PLE results are lower than the theoretical free space PLE of 2, indicating that indoor industrial environments have rich multipaths. The measured power delay profiles show the maximum root mean square (RMS) delay spreads of 11 ns with a directional antenna and 34 ns with an omnidirectional antenna at the receiver in a sparse industrial environment. However, in a dense industrial environment the maximum RMS delay spreads are significantly increased: maximum RMS delay spreads range from 226 to 282 ns for the omnidirectional and the directional antenna configuration. EVM measurements show that to increase coverage and enable higher MCS modes to be used for reliable data transmission, in both industrial environments using a directional antenna at the transmitter and the receiver is required. The large-scale path loss models, multipath time dispersion characteristics and EVM results provide insight into the deployments of 5G networks operating at sub-6 GHz frequency bands in different industrial environments

Of the importance of a leaf: the ethnobotany of sarma in Turkey and the Balkans

BACKGROUND: Sarma - cooked leaves rolled around a filling made from rice and/or minced meat, possibly vegetables and seasoning plants - represents one of the most widespread feasting dishes of the Middle Eastern and South-Eastern European cuisines. Although cabbage and grape vine sarma is well-known worldwide, the use of alternative plant leaves remains largely unexplored. The aim of this research was to document all of the botanical taxa whose leaves are used for preparing sarma in the folk cuisines of Turkey and the Balkans. Methods: Field studies were conducted during broader ethnobotanical surveys, as well as during ad-hoc investigations between the years 2011 and 2014 that included diverse rural communities in Croatia, Bosnia and Herzegovina, Serbia, Kosovo, Albania, Macedonia, Bulgaria, Romania, and Turkey. Primary ethnobotanical and folkloric literatures in each country were also considered. Results: Eighty-seven botanical taxa, mainly wild, belonging to 50 genera and 27 families, were found to represent the bio-cultural heritage of sarma in Turkey and the Balkans. The greatest plant biodiversity in sarma was found in Turkey and, to less extent, in Bulgaria and Romania. The most commonly used leaves for preparing sarma were those of cabbage (both fresh and lacto-fermented), grape vine, beet, dock, sorrel, horseradish, lime tree, bean, and spinach. In a few cases, the leaves of endemic species (Centaurea haradjianii, Rumex gracilescens, and R. olympicus in Turkey) were recorded. Other uncommon sarma preparations were based on lightly toxic taxa, such as potato leaves in NE Albania, leaves of Arum, Convolvulus, and Smilax species in Turkey, of Phytolacca americana in Macedonia, and of Tussilago farfara in diverse countries. Moreover, the use of leaves of the introduced species Reynoutria japonica in Romania, Colocasia esculenta in Turkey, and Phytolacca americana in Macedonia shows the dynamic nature of folk cuisines. Conclusion: The rich ethnobotanical diversity of sarma confirms the urgent need to record folk culinary plant knowledge. The results presented here can be implemented into initiatives aimed at re-evaluating folk cuisines and niche food markets based on local neglected ingredients, and possibly also to foster trajectories of the avant-garde cuisines inspired by ethnobotanical knowledge

Cardiac Prostheses‐related Hemolytic Anemia

Hemolysis is an unintended sequel of temporary or permanent intracardiac devices. However, limited data exist on the characteristics and treatment of hemolysis in patients with cardiac prostheses. This entity, albeit uncommon, often poses significant diagnostic and management challenges to the clinical cardiologist. In this article, we aim to provide a contemporary overview of the incidence, mechanisms, diagnosis, and management of cardiac prosthesis-related hemolysis