The radio frequency (RF) electromagnetic field (EMF) exposure of a 5G small cell radiobase station (RBS) using massive MIMO antenna is assessed. The compliance distance for auniform antenna excitation is determined for a 4x4- and an 8x8 planar array antenna at fourdifferent carrier frequencies, 10, 15, 28 and 60 GHz. Three different exposure standards areused to find the compliance distance, the ICNIRP-, the FCC- and a draft IEEE standard.Simulations using the method of moments (MoM) was used to analyze the antennas and calculatethe power density. The compliance distance converges to Fries far field formula in thefar field region, where said formula is valid. Each standard use different averaging areas andthe convergence is slower for a larger averaging area. This can be explained by the act ofaveraging working as a low pass filter. A lower frequency also leads to a slower convergence,as the far field is located further away.A statistical model is developed to assess the time-averaged realistic maximum power level,based on a 8x8 planar array antenna using a carrier frequency of 28 GHz. Parameters such asTDD, user position and utilization are considered and the model is valid in both the near fieldand the far field regions. The user positions are determined to obtain a realistic conservativeRF EMF exposure with a confidence level of 95%. The antenna can transmit the signal in adefined set of 47 different beam directions spanning -60 to 60 degrees in azimuth and -15 to15 degrees in elevation. The set of 47 beams are simulated using the method of moments tocalculate the electromagnetic fields in the vicinity of the RBS antenna. For the user distributionsinvestigated and at a distance of 20 cm, the power reduction factor is below 0.22. Asthe distance becomes larger the power reduction factor converges toward around 0.17 usinga weighted user distribution and toward 0.10 using a uniform user distribution. This impliesthat the compliance distance can be reduced significantly compared with the results using thetheoretical maximum power.A four panel model is created with the same input parameters as in the one panel case. Themodel is based on a small cell radio base station product produced by Ericsson. A statisticalmodel is created to assess the RF exposure which are made to converge towards the one panelcase far away from the antenna. The users are distributed uniformly and separately over the4 panels with priority given to the panels with highest exposure. The power reduction factoris one forth of the single panel case close to the antenna and converges toward the single panelresults. In general, a four panel product will also have a significant reduction in compliancedistance compared to the results obtained by using constant maximum power.

The new 5G technology, next generation of telecommunication and mobile network, is all around the world in course of inspection and inquiry for its astonishing novelty, from new services to functions and scalability. However, every technology brings alongside new possibilities and new threats scenarios, especially in this case where the impact on the present network is promised to be massive, with brand new features allowed by 5G, like Internet of Things, widespread virtualization and huge leap forward in rapidity and capability of the mobile transmission. An increase in the network surface, considered as more connections, more devices connected and more traffic load of data, will expand also the possible entry point and fault exploitable by a malevolent actor, raising common concern about the technology. The deployment of such a technology on European soil, especially in some states of the Union, caused uproar and critics primarily in the security field. Following a global trend, but also leading a best practice approach, the EU developed a series of mechanisms and agencies that are challenged to oversees the gradual shift from old 4G LTE to 5G. In this paper a Critical Information Infrastructure Protection (CIIP) framework is used to analyse the criticalities of the new technology. Definition of...

The latest advancements in mobile device technology are putting ever-higher demands for throughput of wireless networks. This is threatening to outpace the ability of service providers to deploy the necessary infrastructure. Fifth-Generation Mobile Network (5G) technology is experiencing rapid adoption as part of the effort to meet demand, and along with it researchers are continuously seeking new metrics and models for use in predicting the limits of current and future network infrastructure. To succeed, it is key that they have access to methods for simple, effective analysis of the wireless propagation channel in any given location. The typical laboratory test environment lacks the unpredictability and uniqueness of real-world conditions. Additionally, it utilizes equipment whose specifications are often far removed from devices that are actually intended to operate on the mobile network, such as smartphones themselves. This work focuses on the nature of contemporary path loss models and their ability to accurately predict signal levels, seeking to validate their use against observed path loss behavior in outdoor line-of-sight (LOS) scenarios, where the number of active devices can vary significantly over short periods of time. These conditions are typical of public spaces such as parks and city streets where a large number of users may all simultaneously be accessing high-throughput services. To test their validity, statistics are provided for sets of data collected on foot in public spaces using a novel software utility developed expressly for this purpose. The models we use for comparing against our measured results include both experiential models that are built on other data sets, along with stastically-based, large-scale path loss models. These are compared as a function of distance from the base station (BS), and any unique characteristics of the local network are considered. Finally, a combination of environmental imagery, coverage maps with signal strength overlays, and the aforementioned model comparison are used to estimate the signal source and predict performance in nearby areas.

Background and Objectives Smart healthcare systems use technologies such as wearable devices, Internet of Medical Things and mobile internet technologies to dynamically access health information, connect patients to health professionals and health institutions, and to actively manage and respond intelligently to the medical ecosystem's needs. However, smart healthcare systems are affected by many challenges in their implementation and maintenance. Key among these are ensuring the security and privacy of patient health information. To address this challenge, several mitigation measures have been proposed and some have been implemented. Techniques that have been used include data encryption and biometric access. In addition, blockchain is an emerging security technology that is expected to address the security issues due to its distributed and decentralized architecture which is similar to that of smart healthcare systems. This study reviewed articles that identified security requirements and risks, proposed potential solutions, and explained the effectiveness of these solutions in addressing security problems in smart healthcare systems. Methods This review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines and was framed using the Problem, Intervention, Comparator, and Outcome (PICO) approach to investigate and analyse the concepts of interest. However, the comparator is not applicable because this review focuses on the security measures available and in this case no comparable solutions were considered since the concept of smart healthcare systems is an emerging one and there are therefore, no existing security solutions that have been used before. The search strategy involved the identification of studies from several databases including the Cumulative Index of Nursing and Allied Health Literature (CINAL), Scopus, PubMed, Web of Science, Medline, Excerpta Medical database (EMBASE), Ebscohost and the Cochrane Library for articles that focused on the security for smart healthcare systems. The selection process involved removing duplicate studies, and excluding studies after reading the titles, abstracts, and full texts. Studies whose records could not be retrieved using a predefined selection criterion for inclusion and exclusion were excluded. The remaining articles were then screened for eligibility. A data extraction form was used to capture details of the screened studies after reading the full text. Of the searched databases, only three yielded results when the search strategy was applied, i.e., Scopus, Web of science and Medline, giving a total of 1742 articles. 436 duplicate studies were removed. Of the remaining articles, 801 were excluded after reading the title, after which 342 after were excluded after reading the abstract, leaving 163, of which 4 studies could not be retrieved. 159 articles were therefore screened for eligibility after reading the full text. Of these, 14 studies were included for detailed review using the formulated research questions and the PICO framework. Each of the 14 included articles presented a description of a smart healthcare system and identified the security requirements, risks and solutions to mitigate the risks. Each article also summarized the effectiveness of the proposed security solution. Results The key security requirements reported were data confidentiality, integrity and availability of data within the system, with authorisation and authentication used to support these key security requirements. The identified security risks include loss of data confidentiality due to eavesdropping in wireless communication mediums, authentication vulnerabilities in user devices and storage servers, data fabrication and message modification attacks during transmission as well as while the data is at rest in databases and other storage devices. The proposed mitigation measures included the use of biometric accessing devices; data encryption for protecting the confidentiality and integrity of data; blockchain technology to address confidentiality, integrity, and availability of data; network slicing techniques to provide isolation of patient health data in 5G mobile systems; and multi-factor authentication when accessing IoT devices, servers, and other components of the smart healthcare systems. The effectiveness of the proposed solutions was demonstrated through their ability to provide a high level of data security in smart healthcare systems. For example, proposed encryption algorithms demonstrated better energy efficiency, and improved operational speed; reduced computational overhead, better scalability, efficiency in data processing, and better ease of deployment. Conclusion This systematic review has shown that the use of blockchain technology, biometrics (fingerprints), data encryption techniques, multifactor authentication and network slicing in the case of 5G smart healthcare systems has the potential to alleviate possible security risks in smart healthcare systems. The benefits of these solutions include a high level of security and privacy for Electronic Health Records (EHRs) systems; improved speed of data transaction without the need for a decentralized third party, enabled by the use of blockchain. However, the proposed solutions do not address data protection in cases where an intruder has already accessed the system. This may be potential avenues for further research and inquiry.

Yes / This paper presents a circular polarization reconfigurable antenna for 5G applications, which is compact in size and has good axial ratio and frequency response. The proposed microstrip antenna is designed on a FR-4 substrate with a relative dielectric constant of 4.3 and has a maximum size of 30×30 mm2 with 50 Ω coaxial probe feeding. This design has two PIN diode switches controlling reconfiguration between right hand circular polarization (RHCP) and left hand circular polarization (LHCP). To achieve reconfigurability, a C-slot rectangular patch antenna with truncated corner techniques is employed by cutting off two corners on the radiating patch. The proposed antenna has been simulated using CST microwave studio software: it has 3.35-3.77 GHz and 3.4-3.72 GHz bands for both states of reconfiguration, and each is suitable for 5G applications with a good axial ratio of less than 1.8 dB and good gain of 4.8 dB for both modes of operation. / Innovation programme under grant agreement H2020-MSCA-ITN-2016 SECRET-722424, UK Engineering and Physical Sciences Research Council (EPSRC) under grant EP/E022936/1.

Yes / In this work, a compact 4-element multiple-input multiple-output (MIMO) antenna system is presented for sub-6 GHz applications. A modified M-shaped strip is used to form each antenna element in the MIMO system. To improve performance, a rectangular-shaped area is etched on the opposite side of each element in the ground plane. The antenna size is 100 × 60 mm2. Most interestingly, the port isolation is improved by rotating the etched areas and the corresponding radiating elements. This one-of-a-kind approach aided in the development of a highly isolated MIMO antenna with a small footprint. The theory of characteristic modes (TCM) is used to analyze the behavior of rotating the etched areas in the ground of the antenna. The antenna provides significant port isolation above 20 dB, stable radiation patterns, and an outstanding ECC of less than 0.01. The design is simple and compact, making it suitable for MIMO operation on handheld devices.

Yes / In indoor wireless communication networks, the optimal locations had been known to deploy the access points (AP's) which has a significant impact on improving various aspects of network operation, management, and coverage. In addition, develop the behavioral characteristics of the wireless network. The most used approach for localization purposes was based on Received Signal Strength (RSS) measurements, which is widely used in the wireless network. As well as, it can be easily accessed from different operating systems. In this paper, we proposed an optimal AP localization algorithm based on RSS measurement obtained from different received points. This localization algorithm works as a complementary to the 3D Ray tracing model based REMCOM wireless InSite software and considered two-step localization approach, data collection phase, and localization phase. Obtained result give relatively high accuracy to select the optimum location for AP compare with other selected locations. It is worth to mention that effect of different building materials on signal propagation has been considered with specifying the optimum location of deployment. Furthermore, channel characterizations that based on path losses have been considered as a confirmation for the optimum location being selected.

This thesis introduces a novel framework for enabling intelligent machines and robots with the fifth-generation (5G) cellular network technology. Autonomous robots, such as Unmanned Aerial Vehicles (UAVs), Autonomous Guided Vehicles (AGVs), and more, can notably benefit from multi-agent collaboration, human supervision, or operation guidance, as well as from external computational units such as cloud edge servers, in all of which a framework to utilize reliable communication infrastructure is needed. Autonomous robots are often employed to alleviate humans by operating demanding missions such as inspection and data collection in harsh environments or time-critical operations in industrial environments - to name a few. For delivering data to other robots to maximize the effectiveness of the considered mission, for executing complex algorithms by offloading them into the edge cloud, or for including a human operator/supervisor into the loop, the 5G network and its advanced Quality of Service (QoS) features can be employed to facilitate the establishment of such a framework. This work focuses on establishing a baseline for integrating various time-critical robotics platforms and applications with a 5G network. These applications include offloading computationally intensive Model Predictive Control (MPC) algorithms for trajectory tracking of UAVs into the edge cloud, adapting data sharing in multi-robot systems based on network conditions, and enhancing network-aware surrounding autonomy components. We have identified a set of key performance indicators (KPIs) crucially affecting the performance of network-dependent robots and applications. We have proposed novel solutions and mechanisms to meet these requirements, which aim to combine traditional robotics techniques to enhance mission reliability with the exploitation of 5G features such as the QoS framework. Ultimately, our goal was to develop solutions that adhere to the essential paradigm of co-designing robotics with networks. We thoroughly evaluated all presented research using real-life platforms and 5G networks.

The wireless world of today is essential to the everyday life of millions of people. Wireless technology is evolving at a rapid pace that's speed outmatches what the previous testing can handle. This necessitates the need for smarter and faster testing methods. One of the recent fast and efficient testing methods is fuzz testing. Fuzz testing is the generation and injection of unexpected input called "fuzzed" input for a system by slightly changing a base input hundreds or even thousands of times and introducing each change into a system to observe its effects. In this thesis, we developed and implemented a fuzz testing architecture to test 5G wireless system vulnerabilities. The proposed design uses multiple open-source software to create a virtual wireless environment for testing the fuzzed inputs' effects on the wireless attach procedure. Having an accessible and adaptable fuzzing architecture to use with wireless networks will help against malicious parties. Due to 5G simulation technology still being developed and the cost of ready-made 5G testing equipment, the architecture was implemented in an LTE environment using the srsRAN LTE simulation software, the Boofuzz fuzzing software, and Wireshark packet capture software. The results show consistent effects of the fuzz testing on the outputs of the LTE eNB. We also include a discussion of our future suggestions to improve the proposed fuzzing architecture. / Master of Science / The persistence of the cellular network is essential to the everyday life of millions of people. Cell phones and cell towers play an important role in business, communication, and recreation across the globe. The speed of advancements made in phones and cell towers technology is outpacing the speed of security testing, increasing the possibility of system vulnerabilities and unexplored back-doors. To cover the security testing gap, different automated testing models are being researched and developed, one of which is fuzz testing. Fuzz testing is the generation and injection of unexpected input called "fuzzed" input for a system by slightly changing a base input hundreds or even thousands of times and introducing each change into a system to observe its effects. The fuzzing architecture proposed in this thesis is used to test for security flaws in wireless cellular networks. We implemented our fuzz testing model in a simulated 4G cellular network, where the results show the effectiveness of the model on tracing network vulnerabilities. The results of the experiment show consistent effects of the fuzz testing on a wireless system. A discussion of how the proposed model can be further improved for future work is added to the end of this thesis.

The evolution from the fifth generation (5G) networks to 6G promises to revolution- ize connectivity, supporting a vast array of applications from high-definition video streaming and immersive augmented reality experiences to critical machine-type communications. However, this progression brings along the challenge of efficiently managing the limited radio spectrum (RF) resources to accommodate the diverse quality of service (QoS) requirements of a variety of service and user types. Another problem gaining traction with the advances of wireless communications technology is the coexistence between active communication systems and passive RF sensing operating in the same or adjacent bands. Central to addressing these challenges is the proposed application of deep reinforcement learning (DRL), which emerges as a tool for adaptive and intel- ligent radio resource management (RRM) in the face of the increasingly complex and dynamic RF system requirements. This dissertation investigates the application of DRL for service, user, and network management of advanced wireless networks operating in dedicated and shared spectrum. Through a series of innovative DRL-based frameworks and solutions to a variety of emerging RRM problems, this work contributes to the optimization of spectrum, transmission power, and band- width allocation, as well as network configuration. We contribute to the integration of cutting-edge technologies such as unmanned aerial vehicles as aerial base stations, reconfigurable intelligent sur- faces, and multi-user multiple input, multiple output systems for a seamless user experience. The core of the dissertation explores how DRL can adaptively manage spectrum resources that satisfy the QoS requirements of different 5G service classes, specifically enhanced mobile broadband and ultra-reliable low-latency communications, while also facilitating the integration of terrestrial and aerial network nodes to enhance coverage and capacity. This dissertation further extends into the domain of coexistence between active wireless communication systems and passive remote sensing technologies. We collect radiometric measurement data in a custom-built software-defined radio testbed for which we design different 5G downlink transmission patters and data sets. Based on the collected and processed data from the testbed’s radiometer, we propose a DRL-based strategy to manage 5G communications while reducing the RF interference impact on co-channel radiometric measurements. Through simulations, the proposed solution demonstrates the tradeoffs between communications and sensing operations in terms of common wireless network performance met- rics, such as sum data rate and user fairness, and brightness temperature readings obtained by the radiometer.