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Battery-less sensors need a fast and stable wireless charging mechanism to ensure that they are being correctly activated and properly working. The major drawback of state-of-the-art wireless power transfer solutions stands in the maximum Equivalent Isotropic Radiated Power (EIRP) established from local regulations, even using directional antennas. Indeed, the maximum transferred power to the load is limited, making the charging process slow. To overcome such limitation, a novel method for implementing an effective wireless charging system is described. The proposed solution is designed to guarantee many independent charging contributions, i.e., multiple tones are used to distribute power along transmitted carriers. The proposed rectenna system is composed by a set of narrow-band rectifiers resonating at specific target frequencies, while combining at DC. Such orthogonal frequency schema, providing independent charging contributions, is not affected by the phase shift of incident signals (i.e., each carrier is independently rectified). The design of the proposed wireless-powered system is presented. The main advantage of the solution is the voltage delivered to the load, which is directly proportional to the number of used carriers. This is fundamental to ensure fast sensor wakes-up and functioning. To demonstrate the feasibility of the proposed system, the work has been complemented with the manufacturing of two rectennas, and the analysis of experimental results, which also validated the linear relationship between the number of used carriers.

The use of the Fast Multipole Method (FMM) in an equivalent current reconstruction technique, based on a dual-equation formulation, has been presented in the past for antenna design and diagnostics. The method was applied in design validation from measured data, demonstrating diagnostics feasibility of different large antennas up to an equivalent antenna volume of 2380 $\lambda^{\wedge}3$. Despite the computational advantages coming from the FMM, the memory request and the run time constraints could be still crucial in the processing of electrically large antennas. An enhancement of the equivalent current reconstruction technique based on a Nested Skeletonization Scheme is here presented. The new technique leads to a further reduction of memory requirements and computational time, applicable to diagnostic investigation of electrically larger problems in a wider frequency band. In this paper the nested skeletonization scheme enhancement of the equivalent current technique is applied and demonstrated for diagnostics on electrically large structures.

The equivalent source technique (EQC) has proved to be a useful aid in antenna processing, diagnostics and in the link with Computational ElectroMagnetic Tools (CEM). For broadband frequency antennas or in case of very large number of frequencies, reduction of the number of frequency points to be computed is a desirable feature, to significantly limit the global computational time. In recent applications this is a realistic need, since antennas are present in almost all commercial products, operating on a large set of frequency bands, and exhibiting a wide variety of pattern types. Therefore, they need to be analysed on a relevant number of frequency points, to finally check compliance with standards. For this purpose, in case of multifrequency processing, an interpolation technique based on radiation patterns and antenna S-parameters has been implemented in the EQC. In this paper the new implementation is applied and demonstrated on a large band antenna.

Near-field (NF) measurements with NF-to-far-field (FF) transformation are a powerful and standard approach to modern antenna measurements. This approach implies a relatively close distance between device under test (DUT) and probe and, since the latter is rarely an ideal probe, it will introduce effects that have to be removed to obtain a FF which is only expression of the DUT. In this study, the authors introduce a probe compensation technique applicable to a generic scan surface with non-uniform, possibly incomplete sampling. The procedure is based on a hybridisation between simulations and measurements of the DUT, originally devised to achieve a radical undersampling of the NF with respect to the Nyquist criteria, in order to perform fast and accurate measurements. They present results that prove the effectiveness of the proposed approach.

In this paper, we present a fully automated procedure for the direct design of a novel class of single-feed flat antennas with patterning of a conductive surface. We introduce a convenient surface discretization, based on hexagonal cells, and define an appropriate objective function, including both gain and input matching requirements. The reference geometry is constituted by a very thin, single feed-point square panel. It features a backing metal plate (“ground”) and a top conductive layer, which is automatically patterned to achieve the desired radiation and input matching properties. The process employs an evolutionary algorithm combined with a boundary element electromagnetic solver. By applying this method, we designed an antenna tailored to the 2.4 GHz ISM frequency band, with a size of $$24\,\hbox {cm} \times 24\,\hbox {cm}$$24cm×24cm, i.e., $$2 \times 2$$2×2 wavelengths and an height of 4 mm, or 0.03 wavelengths. Measured data confirmed the expected high gain (13 dBi), with a remarkable aperture efficiency (higher than 50%, including losses), thus validating the proposed approach.

These days, level of environmental pollution seriously concern people’s health risk. For this reason, the demand of innovative techniques to determine pollution in sensible areas is ever increasing. This work presents a novel method for the control of environmental emissions. The proposed solution deploys an Unmanned Aerial Vehicle (UAV) to facilitates the responsible authorities to quickly act and real-time monitoring specific areas. The work encompasses both hardware and software integration to develop a new measurement tool that will be hosted by an UAV. The platform comprises digital optics sensors and toxic/pollutant gas concentration detectors along with low-power computing and communication capabilities.

Navigation in the Arctic region is strongly compromised due to extreme environmental conditions. Among the others, correct positioning is the most critical aspect to manage in such environmental conditions. The main criticality for this can be ascribed to the low-orbit of satellites used for positioning, which implies very weak signals received at ground. To overcome such limitations, this work aims to investigate and develop a solution that provides highly accurate positioning by monitoring and mitigating the ionospheric impact on GNSS signals. Improving quality of the received signals allows for safer routes for Arctic shipping. To this end, this study foresees the deployment of an ad-hoc regional wireless network, where each node is a GNSS station. This paper describes the technological choices made to guarantee the operation of the GNSS stations network in such harsh environments. Specifically, the paper focuses on the description of the low power communication and computing subsystems.

The success and worldwide diffusion of microsatellites lies mainly in the time reduction for mission preparation and launch costs. Testing and validation of the installed antenna using conventional Near-field (NF) techniques can be prohibitive in terms of cost and duration in some cases. An advanced and innovative RF test methodology that allows to dramatically reduce time and costs associated with the microsatellites integration phase has been developed, consolidated and validated. The time reduction has been achieved by dramatically reducing the number of measurement points. This has been achieved by combining measurements and fast numerical modelling using Numerically Defined Basis Function Expansion (NDBFE). Considerably faster testing is accomplished, with a known level of confidence with respect to traditional measurements. In this paper, we present the methodology together with validation results on a microsatellite mock-up.

Modern Cloud architectures encompass computing and communication elements that span from traditional data center computing nodes (offering almost infinite resources to satisfy any application demands) to edge-computing and IoT devices (to sense and act on the real world). This paper presents the Cloud architecture devised within the OPERA project [1], which provides new levels of energy efficiency as a full chip-to-Cloud solution. Focusing on a smart vision application (i.e., road traffic monitoring), the paper presents novel architectural solutions optimised to achieve high energy efficiency at any level: i) the computing elements supporting the acceleration of State-of-the-Art CNNs; and ii) an innovative wireless communication subsystem. Unlike conventional designs, our wireless communication subsystem exploits the advantages of software defined radio (SDN) firmware to control a reconfigurable antenna. To further extend the application range, an energy harvesting module is used to supply power. Besides the edge-IoT, high-density accelerated servers offer capabilities of running complex algorithms within a small power envelop. The effectiveness of the whole architecture has been tested in a real context (i.e., 2 installation sites). In-field measurements demonstrate our claim: high-performance coupled with high energy efficiency over the whole system.

The current state-of-the-art of Internet of Things witnesses the development of low-cost and smart-connected wireless sensor networks (WSNs) placed at the edge of clouds, enabling new services over the Internet. In these interconnected smart sensors, energy consumption is an important issue. This paper deals with decreasing energy consumption in WSN nodes by means of antennas with reconfigurability at radiofrequency. Our research has yielded two important novelties. First, the reconfiguration is accomplished with a platform comprised of a commercial ultra low-power (ULP) micro-controller and system-on-chip radio. Second, we consider explicitly the energy overhead involved in the antenna configuration process and its impact on the global energy efficiency of the system. We discuss two complementary ways of reducing the energy consumption; one by lowering the amount of transmitted power, the other by increasing the transmission rate. We employ an antenna array with a steerable beam, controlled by an algorithm embedded in the firmware of the ULP platform. This is designed for line-of-sight conditions, and the beam steering maximizes the received power. Our results show that with a common IEEE 802.11 b/g system-on-chip module and an antenna gain of 12 dB, a net power saving factor of 28% can be obtained by reducing the transmitted power, at unchanged data rate; additionally, by keeping the transmit power constant, but increasing the data rate, an energy saving from 18% to 96% can be achieved, depending on the link distance and achievable data rate. Our experiments have confirmed both routes of energy saving.

Cloud computing is an emerging paradigm in which users’ access to a shared pool of computing resources is dynamically allocated (i.e. ubiquitous computing service), depending on their specific needs. Such paradigm exploits the infrastructural capabilities of modern data centers to provide computational power and storage space required to satisfy modern application demands. The seamless integration of Cyber-Physical Systems (CPS) and Cloud infrastructures allows the effective processing of the huge amount of data collected by smart embedded systems, towards the creation of new services for the end users. However, trying to continuously increase data center capabilities comes at the cost of an increased energy consumption. The OPERA project aims at bringing innovative solutions to increase the energy efficiency of Cloud infrastructures, by leveraging on modular, high-density, heterogeneous and low-power computing systems, spanning data center servers and remote CPS. The effectiveness of the proposed solutions is demonstrated with key scenarios: a road traffic monitoring application, the deployment of a virtual desktop infrastructure, and the deployment of a compact data center on a truck.

This work proposes a low-cost and low-power software-defined radio open-source platform with IEEE 802.11 a/g/p wireless communication capability. A state-of-the-art version of the IEEE 802.11 a/g/p software for GNU Radio (a free and open-source software development framework) is available online, but we show here that its computational complexity prevents operations in low-power general purpose processors, even at throughputs below the standard. We therefore propose an evolution of this software that achieves a faster and lighter IEEE 802.11 a/g/p transmitter and receiver, suitable for low-power general purpose processors, for which GNU Radio provides very limited support; we discuss and describe the software radio processing structuring that is necessary to achieve the goal, providing a review of signal processing techniques. In particular, we emphasize the advanced reduced-instruction set (RISC) machine (ARM) study case, for which we also optimize some of the processing libraries. The presented software will remain open-source.

The necessity of managing acquisition instruments installed in remote areas (e.g., polar regions), far away from the main buildings of the permanent observatories, provides the perfect test-case for exploiting the use of low power computing and communication systems. Such systems are powered by renewable energy sources and coupled with reconfigurable antennas that allow radio-communication capabilities with low energy requirements. The antenna reconfiguration is performed via Software Defined Radio (SDR) functionalities by implementing a phase controller for the array antenna in a flexible low power General Purpose Platform (GPP), with a single Front-End (FE). The high software flexibility approach of the system represents a promising technique for the newer communication standards and could be also applied to Wireless Sensor Networks (WSNs). This paper presents the prototype that is devoted to ionospheric analysis and that will be tested in Antarctica, in the Italian base called Mario Zucchelli Station, during summer campaigns. The system, developed to guarantee its functionality in critical environmental conditions, is composed of three main blocks: Communication, Computing and Power supply. Furthermore, the computing and communication system has been designed to take into account the harsh environmental conditions of the deployment site.

The ability to reconfigure an antenna can also allow energy saving in autonomous system as, e.g. the nodes of a deployable wireless sensor network. This option appears not yet fully exploited. Software-defined radio (SDR) plays an important role in this scenario. This paper shows how a simple antenna with reconfigurable beam can reduce the energy consumption of wireless links (WI-FI), while preserving channel capacity and reducing interferers.