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This paper presents the design of a novel chipless harmonic RFID sensor in paper substrate based on a variable attenuator implemented as a π resistive network, which drives a single Schottky diode frequency doubler and a system of nested tapered annular slot antennas. The passive tag is interrogated by a signal at f0 = 1.2 GHz and the signal transmitted back to the reader is converted to 2f0 = 2.4 GHz in order for the system to be immune to clutter returns. The sensor information is encoded in the magnitude of the re-transmitted signal and a dynamic range around 20 dB is experimentally demonstrated.

Digitally-intensive PLLs have already demonstrated their effectiveness as frequency synthesizers for cellular applications, being able to fulfill the specifications in terms of phase noise, spurs and power dissipation thanks to the adoption of embedded digital processing that efficiently reduces the analog impairments. In this paper we review how these techniques further enable other capabilities, namely both wideband and linear frequency modulation. The application considered as a case study is the fast chirp generation for frequency-modulated continuous wave radar at millimeter waves. We illustrate how the combination of the two-point modulation of a digital PLL and the background digital pre-distortion of the DCO enable both fast and linear modulation.

Metallic materials are in a peculiar position for realization of electromagnetic shielding and antennas. Implanted devices, sometimes also responsible for vital functions of the hosting human body, should present reduced response to external electromagnetic interferences. In case transmission of data between the device and external environment is additionally required, the device should also be equipped with an antenna. The biocompatibility of such metallic parts is of fundamental importance: being them positioned on the external part of the device, they are the most exposed to be in close contact with the body environment. Investigations on the timely interaction between the metal based materials and the simulated hosting body by standardized physiological solution is described and quantified.

Software Defined Network (SDN) is considered as the key paradigm for the development of future networks, but there is still a lack of operational solutions, especially for an Internet Service Provider environment. In this work we propose the idea of an advanced SDN device, referred to as Smart SDN Forwarding Device (SSFD), able to implement Network Functions (NFs) on top of the Data Plane: in this way, it will be possible to realize hybrid SDN/IP networks and to reduce the load on the SDN Controller. We also provide a prototype, realized by means of open source software, that represents a first step toward the deployment of an operational device. The performance evaluation realized connecting the SSFD prototype to the experimental LISP network, shows that its performance are very close to the ones of a legacy device: the delay introduced for the control level operations is limited and negligible from an user perspective.

Combined with block diagonalization (BD) methods, Tomlinson-Harashima (TH) precoding and vector perturbation (VP) are attractive non-linear precoding techniques for multi-user multiple-input multiple-output (MU-MIMO) broadcast channels. In this paper, we first briefly review several non- linear precoding schemes including BD-VP, TH and zero-forcing (TH-ZF) and TH-VP, and then derive the achievable sum rate of the hybrid TH-VP precoding. After that, we compare the achievable sum rates and diversity gains of these non-linear precoding schemes with zero-forcing VP (ZF-VP) and dirty paper coding (DPC). The achievable sum rate of TH-VP is shown to approach the sum capacity of DPC asymptotically and outperforms BD-VP, TH-ZF and ZF- VP.

A cache-aided $K$-user Gaussian broadcast channel (BC) is studied. The transmitter has a library of $N$ files, from which each user requests one. The users are equipped with caches of different sizes, which are filled without the knowledge of the user requests in a centralized manner. Differently from the literature, it is assumed that each file can be delivered to different users at different rates, which may correspond to different quality representations of the underlying content, e.g., scalable coded video segments. Accordingly, instead of a single achievable rate, the system performance is characterized by a rate tuple, which corresponds to the vector of rates users' requests can be delivered at. The goal is to characterize the set of all achievable rate tuples for a given total cache capacity by designing joint cache and channel coding schemes together with cache allocation across users. Assuming that the users are ordered in increasing channel quality, each file is coded into $K$ layers, and only the first $k$ layers of the requested file are delivered to user $k$, $k=1,...,K$. Three different coding schemes are proposed, which differ in the way they deliver the coded contents over the BC; in particular, time-division, superposition, and dirty paper coding schemes are studied. Corresponding achievable rate regions are characterized, and compared with a novel outer bound. To the best of our knowledge, this is the first work studying the delivery of files at different rates over a cache-aided noisy BC., Comment: Part of this work was presented at the IEEE International Symposium on Information Theory, Colorado, USA, June 2018

In this paper, we consider the detection of suspiciously high correlation between malicious Internet users that are collaborating in order to cause a Denial of Service (DoS) Attack. The main goal is to recognise cyber incidents (more specifically, collaboration/dependency between different users) in order to ultimately isolate their behavior and avoid the consequenses of the DoS attack. The method relies on the analysis of the data traffic across the concerned network (with both incoming and outgoing traffic) in an effort to identify correlations between different users. The paper models normal and malicious behaviour via hidden Markov models, and analyses the performance of the method using both mathematical reasoning and simulations. © 2016 IEEE.

This paper presents a 2.4 GHz vector modulator fabricated on mechanically flexible, low-cost, environmentally friendly, celluose-based substrate. This circuit can be adopted either as a digitally controlled target for radars' testing, or, more in general, as an I/Q modulator in RF systems. The system is composed by a directional coupler, two mixers and a Wilkinson divider, all of them designed in microstrip technology and resulting in a (64 × 119) mm2 planar device. The modulator functionality is demonstrated by showing the results of a wired test in which the modulator is connected to a signal generator (input), to a spectrum analyzer (output) and digitally controlled by means of an Arduino board.

In this paper we propose two importance sampling methods for the efficient symbol error rate (SER) estimation of maximum likelihood (ML) multiple-input multiple-output (MIMO) detectors. Conditioned to a given transmitted symbol, computing the SER requires the evaluation of an integral outside a given polytope in a high-dimensional space, for which a closed-form solution does not exist. Therefore, Monte Carlo (MC) simulation is typically used to estimate the SER, although a naive or raw MC implementation can be very inefficient at high signal-to-noise-ratios or for systems with stringent SER requirements. A reduced variance estimator is provided by the Truncated Hypersphere Importance Sampling (THIS) method, which samples from a proposal density that excludes the largest hypersphere circumscribed within the Voronoi region of the transmitted vector. A much more efficient estimator is provided by the existing ALOE (which stands for "At Least One rare Event") method, which samples conditionally on an error taking place. The paper describes in detail these two IS methods, discussing their advantages and limitations, and comparing their performances. The work of V. Elvira was partially supported by Agence Nationale de la Recherche of France under PISCES project (ANR-17-CE40-0031-01) and the French-American Fulbright Commission. The work of I. Santamaria was partly supported by the Ministerio de Econom´ıa y Competitividad (MINECO) of Spain, and AEI/FEDER funds of the E.U., under grant TEC2016-75067-C4-4-R (CARMEN).

This paper briefly summarizes an ongoing investigation on millimetre-wave (mmWave) channel sounding using a low complexity single RF chain mode mixing lens–loaded cavity. The main advantage of using the mode–mixing technique is to be able to process the information required to estimate the direction-of-arrival (DoA) of the incoming signal just by reading the signal at the single RF–chain output. This massively reduces the system complexity compared to a standard N–element array antenna that requires around N times RF chains. Specifically, this paper presents a way by which signal directivity towards the coverage area can be enhanced by placing a lens in–front of an oversized cavity. This provides an extra channel gain to the incoming wave, consequently enhancing the DoA estimation resolution. This ongoing investigation can substantially simplify the physical hardware layer of the mmWave channel sounder, offering a great potential for the forthcoming mmWave 5G.

This paper reports a novel modular multilevel converter with interleaved sub-modules (ISM-MMC). The ISM-MMC exhibit a higher scalability in current rating then conventional MMC structures with parallel devices. It can employ low-cost, low-current power switches rather than their bulky and expensive counterparts normally designed in classical MMCs. Another remarkable feature is that the number of the output voltage levels is synthetically multiplied by the number of interleaved SMs. The ISM-MMC is capable of bringing the known advantages of MMC to low voltage - high power applications making it a good candidate for the sector of ultra-fast chargers for electrical vehicles where typical power rating in excess of 1 MW is required for the low voltage supply. A proper modulation scheme is implemented and explained in this paper. A comparison with a classical MMC topology is also provided in terms of number of voltage levels, output voltage harmonic content, and number of components by fixing the number of SMs. Simulation results are given to demonstrate the feasibility of the proposed topology and the implemented modulation scheme. Despite this paper is dealing with a single-phase configuration, the extension to a three-phase scheme can be obtained in a straightforward manner.

In this paper the design and first experimental results of surface mountable bandpass filters in the L- and C- bands are presented. Used for frequency converters in High Throughput Satellite (HTS) systems, the L-band filter is centred at 960MHz with 500MHz bandwidth (FBW=52%) while the C- band filter is centred at 5.35GHz with 2.5GHz bandwidth (FBW=47%). The results presented in this paper are the outcomes of an ESA ARTES AT project called SUMO (‘Surface Mountable Filters for Frequency Converters’). Pre-distorted filter characteristics are proposed for both L- and C-band architectures in order to obtain flatter in-band responses (IL- flatness

A self-reliant, economically-affordable and maximum-efficiency solar water pumping system is proposed in this paper. The autonomy is achieved powering the system through a PV source which well fits for remote or isolated applications. The costs are reduced by removing the DC-DC voltage converter usually present in these applications. The efficiency is enhanced by using a Synchronous Reluctance motor that directly control the pump speed through a Maximum Power Point Tracking algorithm. The paper includes novel implementation hints and a batch of experimental results that prove the effectiveness of the proposal.

In this paper, we study the potential advantages of integrating Unmanned Aerial Vehicles (UAVs) equipped with Base Stations, with a terrestrial mobile network infrastructure. In particular, our main focus here lays on handover and its role in B5G (Beyond 5G) networks. We consider a scenario where multiple UAVs and terrestrial bases jointly provide service to mobile ground users. By combining the UAV dynamic trajectory and radio access procedures, we investigate the impact and network performance of ground-to-air handovers. With respect to previous papers, we discuss how to optimise the UAV segment of the network. Final results show that the UAV needs to adjust its speed, height and antenna radiation angle to improve network performance.

Passive radars are notoriously robust to jamming because the receiver location cannot be detected. Moreover, the use of OFDM based reference signals further improves the robustness against jammers. Nevertheless, recent papers have shown that deception/spoofing-type of jamming may still be possible. The idea was to use a target-on-board deception jammer aimed at deceiving the receiver by preventing it from precisely locating and identifying the target when passive radar imaging is used. In this paper, the same authors test the proposed approach by using a measured DVB-T reference signal. A realistic scenario is emulated by using a multichannel DVB-T signal (three DVB-T channels - about 24 MHz bandwidth).

The fourth industrial revolution combines cutting-edge technologies such as Industrial Internet of Things (IIoT) and cloud computing. However, this inevitable revolution faces challenges due to the presence of legacy equipment in industrial systems. Legacy equipment hinders the adoption of emerging cloud technologies due to data privacy, security and interoperability issues. This paper proposes a secure cloud migration approach for industrial systems and investigates whether it can meet real-time control system requirements without compromising system safety and security. The proposed approach is generic enough to be applied for different industrial sectors with minimal interruption to operations during the cloud migration process. Due to the large number of IIoT devices, manual system monitoring to pin-point issues is a tedious and time-consuming task. This paper also proposes an automated monitoring and management framework for large complex IIoT network that tracks and reports issues using different forms of notifications. Experimental validation on a real microgrid testbed facility concluded that the proposed approach is promising for time-critical industrial systems.

In the last years the multimedia traffic on IP networks has increased significantly. According to Cisco, the video contents are expected to reach 82% of the total IP traffic by 2022. The explosion of video on demand and real time/live event videos causes several issues for Telco networks, such as increased delay in content delivery, frequent congestions and service unavailability. In this paper we analyse an integration model between the broadcaster’s network and the Telcos’ fixed access networks. In particular, contents from the distribution network of broadcasters are directly injected into the central offices of Telco’s network. This integrated architecture allows offloading the core and metro segments of the Telco network and, at the same time, it enables broadcasters to provide contents with reduced latency and to avoid typical inconveniences in Telco’s network. Performance analysis is carried out in terms of the required transmission power per multiplex. As shown in the paper, the considered integrated network architecture can achieve cost savings in terms of transmission power per multiplex. The possibility of improving current FTTC access networks for supporting broadcast by means of sharing of multiple copper pairs has been also investigated.

Network densification over space and spectrum is expected to be key to enabling the requirements of next generation mobile systems. The pitfall is that radio resource allocation becomes substantially more complex. In this paper we propose LaSR, a practical multi-connectivity scheduler for OFDMA-based multi-RAT systems. LaSR makes optimal discrete control actions by solving a sequence of simple optimization problems that do not require prior information of traffic patterns. In marked contrast to previous work, the flexibility of our approach allows us to construct scheduling policies that achieve a good balance between system cost and utility satisfaction, while jointly operate across heterogeneous RATs, accommodate real-system requirements, and guarantee system stability. Examples of system requirements considered in this paper include (but are not limited to): constraints on how scheduling data can be encoded onto signaling protocols (e.g. LTE’s DCI), delays when turning on/off radio units, or on/off cycles when using unlicensed spectrum. We evaluate our scheduler via a thorough simulation campaign in a variety of scenarios with e.g. mobile users, RATs using unlicensed spectrum (using a duty cycle access mechanism), imperfect queue state information, and constrained signaling protocol. The authors would like to thank the Spanish Government (Ministerio de Economía y Competitividad, Fondo Europeo de Desarrollo Regional, FEDER) for its support through the project ADVICE (TEC2015-71329-C2-1-R) and 5G-Transformer Project (Grant 761536).

In this paper, the authors present a study comparing the reliability and the availability of several architectures based on LoRaWAN Linear Sensor Networks, to be employed for the detection of Black Powder in pipelines. The paper describes how to maximize the network reliability and availability once the constraints related both to the number of nodes and to the number of gateways have been established. In particular, the paper presents a general approach based on the introduction of redundancies in the linear communication network infrastructure, aiming to provide a general methodology to overcome the risk of network failure in case on sensor nodes malfunctioning. A comprehensive set of six possible scenarios has been described and commented in order to identify the most efficient strategy depending on the desired reliability degree.

The current cellular technology and vehicular networks cannot satisfy the mighty strides of vehicular network demands. Resource management has become a complex and challenging objective to gain expected outcomes in a vehicular environment. The 5G cellular network promises to provide ultra-high-speed, reduced delay, and reliable communications. The development of new technologies such as the network function virtualization (NFV) and software defined networking (SDN) are critical enabling technologies leveraging 5G. The SDN-based 5G network can provide an excellent platform for autonomous vehicles because SDN offers open programmability and flexibility for new services incorporation. This separation of control and data planes enables centralized and efficient management of resources in a very optimized and secure manner by having a global overview of the whole network. The SDN also provides flexibility in communication administration and resource management, which are of critical importance when considering the ad-hoc nature of vehicular network infrastructures, in terms of safety, privacy, and security, in vehicular network environments. In addition, it promises the overall improved performance. In this paper, we propose a flow-based policy framework on the basis of two tiers virtualization for vehicular networks using SDNs. The vehicle to vehicle (V2V) communication is quite possible with wireless virtualization where different radio resources are allocated to V2V communications based on the flow classification, i.e., safety-related flow or non-safety flows, and the controller is responsible for managing the overall vehicular environment and V2X communications. The motivation behind this study is to implement a machine learning-enabled architecture to cater the sophisticated demands of modern vehicular Internet infrastructures. The inclination towards robust communications in 5G-enabled networks has made it somewhat tricky to manage network slicing efficiently. This paper also presents a proof of concept for leveraging machine learning-enabled resource classification and management through experimental evaluation of special-purpose testbed established in custom mininet setup. Furthermore, the results have been evaluated using Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and Deep Neural Network (DNN). While concluding the paper, it is shown that the LSTM has outperformed the rest of classification techniques with promising results. King Saud University

Already available WiFi direct and upcoming 5G Device-to-Device (D2D) communication mechanisms are paving the way for the development of Mobile Ad-hoc Networks (MANET) applications. This trend involves the cooperation of nearby mobile nodes in charge of dispatching messages. In addition, the consolidation of the Fog paradigm enables innovative scenarios characterized by the interaction of MANET and Edge nodes. For instance, tourists visiting a city form a MANET to share pictures while the municipality provides Internet connectivity via Edge devices. However, it is required to address specific issues stemming from the collaborative nature of D2D communication, ranging from limited node capabilities providing multi-hop networks to unreliable connectivity due to node mobility. This paper presents the Reliable and Dynamic Routing Technique (RaDRT) solution, adopting the Software Defined Networking (SDN) approach to regulate routing of traffic flows in such Edge-MANET environments. To this purpose, RaDRT originally exploits the joint combination of three primary guidelines: 1) SDN to monitor/manage the state of the mobile network also considering different Quality of Service (QoS) requirements of concurrently running applications, 2) dynamic management of service priority to tune if and how packets are forwarded in a fine-grained per-flow differentiated manner, and 3) joined mobile/fixed solution to maximize the overall QoS also evaluating path reliability based on node mobility. This paper presents the Reliable and Dynamic Routing Technique (RaDRT) solution, adopting the Software Defined Networking (SDN) approach to regulate routing of traffic flows in such Edge-MANET environments. To this purpose, RaDRT originally exploits the joint combination of three primary guidelines: 1) SDN to monitor/manage the state of the mobile network also considering different Quality of Service (QoS) requirements of concurrently running applications, 2) dynamic management of service priority to tune if and how packets are forwarded in a fine-grained per-flow differentiated manner, and 3) joined mobile/fixed solution to maximize the overall QoS also evaluating path reliability based on node mobility.

The advent of the Internet of Things (IoT) together with its spread in industrial environments have changed production lines, by dramatically fostering the dynamicity of data sharing and the openness of machines. However, the increased flexibility and openness of the industrial environment (also pushed by the adoption of Edge devices) must not negatively affect the security and safety of production lines and its operational processes. In fact, opening industrial environments towards the Internet and increasing interactions among machines may represent a security threat, if not properly managed. The paper originally proposes the adoption of the Blockchain to securely store in distributed ledgers topology information and access rules, with the primary goal of maximizing the cyber-resiliency of industrial networks. In this manner, it is possible to store and query topology information and security access rules in a completely distributed manner, ensuring data availability even in case a centralized control point is temporarily down or the network partitioned. Moreover, Blockchain consensus algorithms can be used to foster a participative validation of topology information, to reciprocally ensure the identity of interacting machines/nodes, to securely distribute topology information and commands in a privacy-preserving manner, and to trace any past modification in a non-repudiable manner. The paper originally proposes the adoption of the Blockchain to securely store in distributed ledgers topology information and access rules, with the primary goal of maximizing the cyber-resiliency of industrial networks. In this manner, it is possible to store and query topology information and security access rules in a completely distributed manner, ensuring data availability even in case a centralized control point is temporarily down or the network partitioned. Moreover, Blockchain consensus algorithms can be used to foster a participative validation of topology information, to reciprocally ensure the identity of interacting machines/nodes, to securely distribute topology information and commands in a privacy-preserving manner, and to trace any past modification in a non-repudiable manner.

Nowadays software systems are organized around several and heterogeneous components. For example, a modern application can be composed of different microservices, along with dedicated components for machine learning analytics and recurring batch processing jobs. While containers offer a means to deploy the system and tackle heterogeneity, these components have different execution models, can exploit different resource types (e.g., CPUs and GPUs) and result in completely different execution times (milliseconds vs hours). This complexity calls for a new, scalable architecture to allow the systems to operate efficiently. This paper presents COCOS, an architecture, based on containers and control-theory, that is able to manage large and heterogeneous software systems. The architecture is based on a three-level hierarchy of controllers that cooperatively enforce user-defined requirements on execution times and consumed resources. The paper also shows a prototype implementation of COCOS based on Kubernetes, a well-known container orchestrator. The evaluation shows the efficiency of COCOS when dealing with microservices, Spark jobs and machine learning applications.

This paper has been presented at the 2020 European Conference on Networks and Communications (EuCNC) In the Zero-touch network and service management (ZSM) architecture, devised by ETSI, making predictions on the observed data is among the functions provided by the analytics block of the control loop cycle. Prediction performance depends on several parameters, such as the utilized computational resources, the leveraged prediction techniques, the deployment location of the prediction tools with respect to the data.This paper proposes a Hybrid Forecast Framework (HFF) running at the network edge or in the cloud to provide fore-casting with the performance required by the control loop cycle. Forecasting at the edge might shorten the control loop cycle if resources shall be made available locally where data is collected. However, in general, edge computational resources are less abundant than the cloud ones, thus causing longer time to perform the prediction. On the opposite, forecasting in the cloud might require more time for the data to reach the utilized tools but more computational resources could be exploited. The HFF is based on utilizing traditional time series analysis prediction algorithms to minimize the utilized resources and energy at the edge while it exploits AI/ML tools to make predictions in the cloud.Results show that for short lead time (i.e., the time, in the future, at which the status of the considered parameter is predicted) edge-based prediction exploiting time series analysis provides better accuracy, requires less resources and time (thus energy) than cloud-based prediction. However, if the lead time is long, cloud-based prediction exploiting Artificial Intelligence/Machine Learning (AI/ML) provides better accuracy. Thus, if the lead time is long, it is preferable because the long lead time compensates for the higher time for prediction, mainly due to data transfer. This work has been partially supported by the project "Scheme for Promotion of Academic and Research Collaboration (SPARC)", MHRD, Govt. of India and the EU Commission through the 5GROWTH project (grant agreement no. 856709).

Generalized Frequency-Division Multiplexing (GFDM) is a candidate modulation for future wireless cellular networks. The main reason stands in the flexibility of its structure that could fulfill ideas and challenges of forthcoming network scenarios. A known issue of GFDM is its worse performance compared to orthogonal frequency-division multiplexing, which is due to the interference among transmitted symbols. A mathematical model of such an interference has been proposed in a recent paper by exploiting the parallelism that exists between GFDM and discrete Gabor transform. The model allows for the design of different types of linear and non-linear equalizers. With the goal of increasing the transmission reliability, in this paper the introduction of channel coding is considered together with an appropriate interleaving. The computation of the Log-Likelihood Ratio (LLR) is described, which allows for soft decoding in the case of maximum likelihood and linear minimum mean squared error detection. The gain in performance achieved with channel coding and time-frequency interleaving is demonstrated by means of Monte Carlo simulations for the standard 64-state rate-1/2 convolutional code. A comparison with an approach for soft decoding proposed in the literature for GFDM is also reported.

In this paper we analyse and compare the performance of Medium Access Control (MAC) protocols for networks of tags deployed over an industrial machine using THz communications. The challenging requirements of Industrial Internet of Things (IIoT) applications make the THz frequencies very attractive. However, one major drawback from the protocol viewpoint is that, even at short distances, propagation delays at THz frequencies can be of the same order of magnitude as the transmission time of the (short) packets sent by tags. This requires proper investigation of MAC protocols accounting for propagation delays. The paper compares contention-free and random MAC options considering two scenarios, where tags are still or they move in the automation machine.

This paper introduces the use of photon-added squeezed states (PASSs) for quantum pulse position modulation (QPPM). It is shown that the use of PASSs in QPPM communication systems can reduce the symbol error probability (SEP) with respect to the use of different classes of quantum states with the same energy, including squeezed states and photon-added coherent states. The impact of thermal noise and phase diffusion on the SEP is also evaluated. The findings of this paper show the utility of PASSs in quantum communication systems.

In this paper, two different but complementary techniques developed to generate limited-diffractive electromagnetic (EM) beams and pulses by using radial line slot arrays (RLSA) and leaky-wave (LW) planar devices at microwaves/millimeter waves are presented. In the first part of the paper, two kinds of RLSA Bessel beam launchers are proposed, obtained by implementing an inward cylindrical traveling-wave aperture distribution in the longitudinal and transverse electric field components. Moreover, in the second part, two different LW launchers are presented, namely based on forward and backward leaky-waves.

In this paper, we consider a NarrowBand-Internet of Things (NB-IoT) network where an Unmanned Aerial Vehicle (UAV) is employed to gather data from IoT devices deployed in a given area. It is well known that UAVs may fly over the terrestrial plane, where and when needed, acting as Unmanned Aerial Base Stations (UABs). In order to serve as many ground IoT devices as possible, a proper trajectory design is fundamental. As we show in the paper, the optimization of the UAV speed and the radio parameters are also essential. Specifically, this paper studies a cluster-based scenario, where IoT devices are deployed according to a Thomas process, and applies a Traveling Salesman Problem approach to design the UAB trajectory. Notably, our model considers the protocol constraints on the number of resource units available on the UAB’s NPUSCH, and the data rate that it can provide to IoT devices. Our results reveal the impact of different design parameters, such as UAB speed and NPRACH periodicity on the network throughput and the number of requests served.

Power consumption and task latency are two crucial issues in edge-cloud computing. This paper mainly aims to promote the use of clean power in geo-distributed data centers (DCs) in a deregulated electricity market where customers are allowed to buy power from multiple suppliers, combined with the guarantee of task latency. To alleviate the conflict between frequent switches of servers and the uncertainty of task arrivals in DCs, this paper proposes a two-timescale framework consisting of the long-term capacity planning of geo-distributed DCs and the real-time task dispatching from edge gateways (EGs) to DCs. First, DCs make long-term plans on the number of active servers aiming at the eco-friendly and delay-aware power cost minimization, which is formulated as problem $\mathcal {P}$ . Specifically, we introduce a convex pollution indicator function (PIF) to measure the pollution cost of the various types of powers sold by different suppliers, which can encourage the use of cleaner power and improve power savings. Second, in each sub-slot, each EG separately optimizes its individual mixed strategies of task dispatching to DCs with the knowledge of the planned capacities and the real-time queue backlogs of DCs, where a Lyapunov optimization framework is applied. Finally, we give the corresponding distributed algorithm design. Simulation results reveal that our method can realize the trade-off between the power cost and the delay cost of requests, and improve the clean power usage by up to 50%–60% of the total power usage in DCs. Additionally, comparisons with other schemes show that our approach can provide more stable guarantees of task latency in different situations of workload density, which benefits from the diverse-timescale optimizations of capacities of DCs and task routing from EGs to DCs.

With the advent of the Internet-of-Things (IoT), vehicular networks and cyber-physical systems, the need for real-time data processing and analysis has emerged as an essential pre-requite for customers' satisfaction. In this direction, Mobile Edge Computing (MEC) provides seamless services with reduced latency, enhanced mobility, and improved location awareness. Since MEC has evolved from Cloud Computing, it inherited numerous security and privacy issues from the latter. Further, decentralized architectures and diversified deployment environments used in MEC platforms also aggravate the problem; causing great concerns for the research fraternity. Thus, in this paper, we propose an efficient and lightweight mutual authentication protocol for MEC environments; based on Elliptic Curve Cryptography (ECC), one-way hash functions and concatenation operations. The designed protocol also leverages the advantages of discrete logarithm problems, computational Diffie-Hellman, random numbers and time-stamps to resist various attacks namely-impersonation attacks, replay attacks, man-in-the-middle attacks, etc. The paper also presents a comparative assessment of the proposed scheme relative to the current state-of-the-art schemes. The obtained results demonstrate that the proposed scheme incurs relatively less communication and computational overheads, and is appropriate to be adopted in resource constraint MEC environments., Comment: To appear in IEEE GLOBECOM 2019

Service Function Chaining (SFC) allows the forwarding of a traffic flow along a chain of Virtual Network Functions (VNFs, e.g., IDS, firewall, and NAT). Software Defined Networking (SDN) solutions can be used to support SFC reducing the management complexity and the operational costs. One of the most critical issues for the service and network providers is the reduction of energy consumption, which should be achieved without impact to the quality of services. In this paper, we propose a novel resource (re)allocation architecture which enables energy-aware SFC for SDN-based networks. To this end, we model the problems of VNF placement, allocation of VNFs to flows, and flow routing as optimization problems. Thereafter, heuristic algorithms are proposed for the different optimization problems, in order find near-optimal solutions in acceptable times. The performance of the proposed algorithms are numerically evaluated over a real-world topology and various network traffic patterns. The results confirm that the proposed heuristic algorithms provide near optimal solutions while their execution time is applicable for real-life networks., Comment: Extended version of submitted paper - v7 - July 2018

In this paper, a downlink wireless communication channel is considered. The base station (BS) has common data for all users, unicast data for a set of intended users, and transmits the superposition of these messages. This setting neither falls into the non-orthogonal multiple access (NOMA) nor into the multi-group multicasting literatures. In NOMA systems, the BS has unicast data for all users, and multiple users share the same resources. In multi-group multicasting, there are non-overlapping groups, each demanding a different multicast message. This paper studies precoder design to achieve maximum weighted sum rate (WSR). It is first shown that the precoders designed for WSR maximization and weighted minimum mean square error (WMMSE) minimization are equivalent. Second, an iterative low complexity algorithm (named WMMSE), based on WMMSE transmit precoders and receivers, is proposed. Another low-complexity precoder, the phase aligned zero forcing (PAZF) precoder, is also introduced. The results show that both algorithms converge fast. The WMMSE algorithm outperforms both PAZF and the zero-forcing (ZF) precoder for all signal-to-noise ratio ranges. It offers better interference management and high coherent combining gains for common data while PAZF finds the optimal phase rotation on the ZF precoder, and increases coherent combining gains.

Recently, there has been much interest by the cellular network industry in utilizing unlicensed spectrum to expand potential capacity. In particular, two LTE unlicensed technologies gained much attention: licensed-assisted access (LAA) and LTE unlicensed (LTE-U). While these are rapidly entering the market, there are not many studies in the literature that are providing a complete evaluation and comparison of their performance. Available work usually focuses on single technology standalone evaluations. Also, despite the vast body of simulation results by industry and academia, the simulators are not publicly available, and the analytical models proposed in the literature do not offer complex enough frameworks for thorough performance evaluations. To carry out an evaluation study, we have built a comprehensive simulation platform, strictly complying with the standards and specifications of each technology. The models are built upon popular ns-3 simulator, have been designed in close consultation with industry experts, and have been validated through calibration processes and against analytical proposals and experimental platforms. In this paper, we provide a detailed overview, performance evaluation, and comparison of LAA and LTE-U in a wide variety of scenarios, following 3GPP and Wi-Fi Alliance (WFA) guidelines. We show that despite the market is confirming LAA as the leading unlicensed LTE technology, in certain setups, efficient implementations of LTE-U may prove unexpectedly better in coexisting with Wi-Fi. Similarly, the expected behaviors of the LAA LBT procedure can reveal untrue, depending on the traffic or interference patterns and specific implementation details, even in Wi-Fi. This paper also includes scenarios involving TCP, which is a rarely treated topic in the literature in the context of LTE and Wi-Fi coexistence. The end-to-end and full protocol stack simulation platform is openly available to foster results' reproducibility and collaborative development. This work was supported in part by the Spanish Ministry of Economy and Business (MINECO) under Grant TEC2017-88373-R (5G-REFINE), in part by the Generalitat de Catalunya under Grant 2017 SGR 1195, in part by the Wi-Fi Alliance (WFA), and in part by the Spidercloud Wireless.

In this paper we consider the application of the LoRaWAN™ technology for metering purposes. We compare this technology with a well established technology for metering applications such as the WM-Bus. We take as key performance indicator the battery lifetime, keeping the same Quality of Service. The distinctive features of this paper is to collect real data from measurement campaigns in full fledged carrier grade networks and to consider two generations of meters from the same manufacturer. The results of the measurements show that the LoRaWAN meters outperforms the WMBus meters significantly as far as the battery lifetime is concerned.

Advances in the design of Full-Duplex (FD) transceivers with low residual Self-Interference (SI) levels has led to their deployment in various wireless communication applications. One promising field that FD transceivers could play a major role in reshaping its dynamics is physical layer security. This paper investigates the performance of FD transceivers in the context of Military FD Radios (MFDR). Particularly, the adopted system model builds on recent investigations regarding the feasibility of deploying an MFDR in a scenario where it simultaneously jams a receiver node while intercepting the signal of a transmitter node, thus simultaneously disrupting and intercepting a tactical communication link of an opponent team. The secrecy performance of the MFDR is theoretically quantified by deriving its outage in interception probability expression. The results reveal that a well-performing SI cancellation scheme can increase the secrecy performance of an MFDR. - 2019 IEEE. This paper was made possible by GSRA grant #2-1-0601-14011 and NPRP grant #8-627-2-260 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. Scopus

Internet of Things (IoT) and Wireless Sensor Networks (WSN) infrastructures are becoming more and more available and diffused. One major outcome is the development of new services that help to make everyday life easier and better. One of those to which this paper reserves special attention is asset tracking which refers to the method of tracking physical assets. This service is very well based on IoT infrastructure and, due to the enormous number of objects to be traced, desperately needs the availability of inexpensive tags with sensing capabilities, that can be conveniently monitored from a long distance and require no maintenance. For this, engineers are called to face very challenging issues. One of these is how to power a maintenance-free tag that consequently must be battery-free. This paper deals with the investigation of a system based on radio frequency (RF) Wireless Power Transfer (WPT) that powers a battery-free tag for asset tracking, in which the major challenge is that the WPT deals with dynamic objects at different speeds. The performances and key features of a system on chip (SoC) specifically designed to power a tag by means of RF WPT will be investigated. The aim is to provide a strategy and a model to design the infrastructure by providing the number of hot-spots needed to perform successfully the identification of an asset. Validation of the model has been done by means of specific tests and experimental results are provided.

The induced voltage on the pipeline is a critical parameters to be evaluated for equipment and personnel safety of the pipeline system. However, in the real life, such estimation is difficult especially at the transmission line planning and routing stage. In this paper, several factors affecting the induced voltage on underground pipeline due to inductive coupling with nearby transmission lines are investigated. A peak induced voltage calculation formula as the function of the angle and separation distance between the transmission line and the pipeline is determined through the surface fitting of the simulation data. It is proved in the paper that other factors such as the length of the transmission line and the soil model types do not have significant influence on the peak induced voltage values.

In this paper we consider a massive multiple-input multiple-output (MIMO) communication system using 5G New Radio-compliant multiple access, which is to co-exist with a radar system using the same frequency band. Building upon a recently proposed system model taking into account the reverberation (clutter) produced by the radar system at the massive MIMO receiver, we provide a theoretical analysis, in terms of a lower bound on the achievable uplink (UL) spectral efficiency (SE) and in terms of the mutual information of the cellular massive MIMO system, showing that for large number of antennas at the base station the radar clutter effects can be suppressed. Simulation results confirm the paper theoretical findings.

In this paper, the attention is focused on the design of a hybrid platoon system capable of minimising energy consumption in the vehicular environment. In this paper, we focused our attention on the design of a Intelligent Transportation System (ITS) system which offers support to the platooning management to achieve a global optimisation of the groups. In this way, new formations help vehicles to reduce energy consumption exploiting platooning. In this work, we propose a novel algorithm based on Gray Wolf Optimization (GWO) to perform the search of the best platoon. Moreover, in this work we propose a protocol to accomplish platoon tasks. We evaluated the system performances of the platoon formation by considering several constraints such as platoon size, platoon speed, average platoon energy consumption, and so on. For the analysis of the results, we use the Omnet++ framework for protocol issues and Matlab tools for carrying out algorithm performances.

The paper deals with the Low Power Wide Area Networks working in unlicensed spectrum. In particular, Lo-RaWAN™ networks are considered the most prominent technology in this field. Specifically, the paper addresses the coexistence in the same bands of LoRaWAN™ networks and the incumbent application featuring the so-called Short Range Devices, a category encompassing different type of devices ranging from gate openers to the traditional home automation technology. To assess this coexistence the paper is proposing a simulation approach using the standard tool used by the regulators in Europe and deriving the input data as well from the official regulators documentation. The results of the simulation campaign is that, by using the parameters of the current regulation in Europe, LoRaWAN™ can inter-operate flawlessly with the incumbent legacy Short Range Devices. These results are in contrast with some proposals one can find in literature which suggest to impose stricter limitations on LoRaWAN™ networks.

This paper discusses the use of an integrated ultrasonic transducer for the realization of a LoRa-based Smart Bin architecture, to be employed for waste management in the Smart Cities context. In particular, the paper analyses the usability of waterproof ultrasonic sensors for the measurement of waste level inside a trash bin: in this context, a solution is described to increase the directionality of the sensor. Indeed, ultrasonic sensors used in common off-the-shelf waterproof ranging systems are characterized by a wide radiation lobe, corresponding to an aperture angle up to 70°: this means that, when employed in trash bins, these sensors detect the presence of the lateral surface of the bin and are not able to detect the garbage layer top or its position in the bin. In this paper we propose a tailored cap, designed to be mounted on a commercial ultrasonic sensor, able to reduce the detection angle down to around 28° degrees. The modified sensor can thus be exploited in this application. The proposed sensing structure is integrated into a sensor node provided with a LoRa transmission module, that allows to employ it for the development of city-scale monitoring infrastructures.

In this paper a two-port network for wireless power transfer realized with three coils is considered. Usually, these networks are analyzed assuming that one of the three mutual couplings is negligible. However, this hypothesis is not always applicable, there are specific configurations for which no coupling can be neglected. Accordingly, in this paper the optimal terminating impedances are derived for the general case where all the couplings are taken into account. The performance of the network are described by using the three power gains (available, power, transducer gains). Analytical formulas and circuital simulations are reported and discussed.

This paper analyzes the effect of fast fading Doppler channel on user scheduling algorithms. Considering a millimeter wave (mmWave) downlink massive multiple-input multiple-output (M-MIMO) system, we adopt a two-stage precoding method to cancel the interference from users. Improved K-mean clustering method with weighted likelihood (WLD) similarity measure is employed to group the active users within a given region. After grouping the users, different scheduling methods, semi-orthogonal user selection (SUS) algorithm and greedy algorithm, are implemented. Initially, grouping and scheduling are performed based on the static channels. Then, the scheduled users are simultaneously served for the next time frames without rescheduling while the users are moving. With this approach, this paper reveals how static and time-varying user grouping and scheduling methods perform in terms of system sum-rate when the fast moving users experience the Doppler effect. Different scenarios of number of active users and time frames are simulated. It is observed that rescheduling is required when greedy algorithm is used in order to maintain high sum-rate, while SUS algorithm does not achieve high sum-rate compared to greedy algorithm. Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK)

The advent of Software-Defined Networking with OpenFlow first, and subsequently the emergence of programmable data planes, has boosted lot of research around many networking aspects: monitoring, security, traffic engineering. In the context of network monitoring, most of the proposed solutions show the benefits of data plane programmability by simplifying the complexity of the network with a one big-switch abstraction. Only few papers look at network-wide solutions, but consider the network as non heterogeneous: only composed by programmable devices. In this paper, we argue that the primary challenge for a successful adoption of those solutions is the deployment problem: how to compose and monitor a network consisting of both legacy and programmable switches? We propose an approach for incrementally deploy programmable devices in an ISP network with the goal of monitoring as many distinct network flows as possible. While assessing the benefits of our solution, we realized that proposed network-wide monitoring algorithms might not be optimized for a partial deployment scenario. We then also developed a novel strategy capable of detecting network-wide heavy flows with the same accuracy of state-of-the-art solutions but by relying on less information from the data plane.

Space applications rely on long and complex design processes, as they must deal with strict non-functional requirements such as criticality, timeliness, reliability and safety. The huge number of analysis and evaluations performed requires powerful simulations technologies combining high simulation speed and accuracy. Host-compiled simulation is a powerful approach to achieve fast, timed simulation of software running in complex embedded systems. However, in the general term, there is still the need of improving the speed and accuracy of these solutions, and there is a lack of host-compiled approaches oriented to space applications. To solve the first point, this paper presents an alternative that modifies the standard solution of adding the modeling of the cross-compiled control flow in the host computer by modifying the compiler's intermediate representation. That way, the host binary naturally follows the cross-compiled binary flow, avoiding a separate modeling, and improving simulation speed while maintaining accuracy. Additionally, the paper focuses on LEON processor, commonly used by the European Space Agency (ESA). This work has been funded by FEDER/Ministerio de Ciencia, Innovación y Universidades - Agencia Estatal de Investigación/ TEC2017-86722-C4-3-R and the EC through the FP7-JTI 621429 EMC2 project.

This paper investigates the performance of irregular low-density parity-check (LDPC) codes on memoryless BI-AWGN (Binary Input - Additive White Gaussian Noise) channels, with sum-product decoding. Objective of this work is to study the relationship between an LDPC code performance and some parameters specifying the code itself, such as the coefficients of its degree distributions. In fact, these coefficients where shown in Di et al.'s 2006 paper to determine the growth rate of the minimum distance of an LDPC code, which can be only sublinear in the block length in some well defined conditions of the degree distribution pair.

In this paper, we analyze two techniques allowing to significantly improve the bit rate per user in the current and future FTTx access networks. They are based on the possibility of sharing copper pairs at data link level among subscribers served by the same distributor. Sharing can be achieved by inserting low-cost devices in the current FTTx access networks. In particular, as shown in this paper, sharing of copper pairs is obtained according to two different approaches. The first approach considers the possibility of increasing bit rate by a radio-shared channel that can be accessed locally by all authorized customer premises equipments (CPEs) inside the building(s). The system providing radio access is connected to the DSLAM by means of extra and temporarily unused copper pairs in the main cable connecting the DSLAM to the distributor. The second approach considers the possibility of inserting an active transceiver device in the current passive distributor(s) bridging the DSLAM to the CPEs. Depending on the activity of CPEs connected at the same distributor, results show that both the solutions allow to achieve very high downstream bit rates per user (about 800 Mb/s at 100 m with 50% CPE activity). Devices to be inserted in the FTTx network can be realized using electronic components currently available on the market.

A Distortion Contribution Analysis (DCA) obtains the distortion at the output of an analog electronic circuit as a sum of distortion contributions of its sub-circuits. Similar to a noise analysis, a DCA helps a designer to pinpoint the actual source of the distortion. Classically, the DCA uses the Volterra theory to model the circuit and its sub-circuits. This DCA has been proven useful for small circuits or heavily simplified examples. In more complex circuits however, the amount of contributions increases quickly, making the interpretation of the results difficult. In this paper, the Best Linear Approximation (BLA) is used to perform the DCA instead. The BLA represents the behaviour of a sub-circuit as a linear circuit with the unmodelled distortion represented by a noise source. Combining the BLA with a classic noise analysis yields a DCA that is simple to understand, yet capable to handle complex excitation signals and complex strongly non-linear circuits., Preprint of the paper submitted to the IEEE transactions on Circuits and Systems - I: Regular papers

Nowadays, we are observing an explosion on recording and transmitting of videos from multiple sources such as Social Media (Periscope, Facebook, Youtube etc.) and owner of trains/coaches (Trenitalia-Frecce-Italy, TGV-France, Ryanair-Bus-Travels, etc.). In this paper, we investigate how to support the provisioning of videos to heterogeneous end user devices in different contexts, adapting the content to the specific requirements of the used end devices. In particular, we present a new Cloud-Edge Service for vIdeO delivery (CESIO) architecture, that exploits Cloud and Edge virtual resources to improve the delivery video contents at different quality resolutions. The paper describes architecture components and their behaviour in the system. Moreover, a possible application scenario is discussed to well explain how the proposed solution works.