The continuous development of internet of things (IoT) infrastructure and applications is paving the way for advanced and innovative ideas and solutions, some of which are pushing the limits of state-of-the-art technology. The increasing demand for Wireless Sensor Nodes (WSNs) able to collect and transmit data through wireless communication channels, while often positioned in locations that are difficult to access, is driving research into innovative solutions involving energy harvesting (EH) and wireless power transfer (WPT) to eventually allow battery-free sensor nodes. Due to the pervasiveness of radio frequency (RF) energy, RF EH and WPT are key technologies with the potential to power IoT devices and smart sensing architectures involving nodes that need to be wireless, maintenance free, and sufficiently low in cost to promote their use almost anywhere. This paper presents a state-of-the-art, ultra-low power 2.5 $\mathsf{\mu }$ W highly integrated mixed signal system on chip (SoC), for multi-source energy harvesting and wireless power transfer. It introduces a novel architecture that integrates an ultra-low power intelligent power management, an RF to DC converter with very low power sensitivity and high power conversion efficiency (PCE), an Amplitude-Shift-Keying/Frequency-Shift-Keying (ASK/FSK) receiver and digital circuitry to achieve the advantage to cope, in a versatile way and with minimal use of external components, with the wide variety of energy sources and use cases. Diverse methods for powering Wireless Sensor Nodes through energy harvesting and wireless power transfer are implemented providing related system architectures and experimental results.

In this article, we propose a method based on the aperture antennas theory to understand the limitations of orbital angular momentum (OAM) antennas in far-field links. Additional insight is also given by analyzing the properties of the operators relating source and farfield distributions for a given order of the vortex and emphasizing additional drawbacks. The degrees-of-freedom (DoF) of the fields associated with the different orders of the vortices are also discussed.

With reference to the mask-constrained power synthesis of shaped beams, we extend the Spectral Factorization method to both uniformly and non-uniformly spaced linear arrays wherein mutual coupling and mounting-platform effects are present. The overall design procedure does not rely on any restriction on the nature and the shape of the fields, and it is cast as a couple of convex optimizations plus a polynomial factorization. Moreover, it allows one to ascertain the actual feasibility of the radiating system before performing the synthesis, and it is able to identify very many different arrayexcitation solutions all corresponding to the desired power pattern. The given theory is supported by numerical experiments concerning the full-wave synthesis of realistic arrays affected by mutual coupling and mounting-platform effects.

The linearity of the scattering phenomenon with respect to primary sources allows to recombine a posteriori the available experiments and build, in a synthetic fashion, new “virtual” experiments. Starting from this circumstance, an iterative procedure is proposed as an effective approach to tackle nonlinear inverse scattering problems. In this procedure, the virtual experiments, the Green's function, and the corresponding physical inspired field approximations are updated at each iteration. The structure and the complexity of the approach are comparable with those of the widely adopted distorted Born iterative method, but its performances are remarkably better, thanks to extended validity of the exploited field approximation. The overall approach also takes advantage of a compressive sensing inspired regularization scheme to promote sparsity in the search of piecewise constant dielectric profiles and further improve the accuracy of the imaging results. Examples with numerical and experimental data are given to assess the method.

In this paper, we present a new model-based linear inversion approach for cross-borehole ground penetrating radar quantitative imaging. The approach is reliable and computationally effective as it consists of the cascade solution of two linear inverse problems. The first problem yields a qualitative image of the targets (i.e., their location and approximate shape) and the information needed to cast a set of virtual experiments wherein a linear scattering model that implicitly depends on unknown targets holds true. By relying on such a model, it is possible to achieve, via linear inversion, a quantitative estimate of the targets' electric permittivity and conductivity in a much broader range of cases as compared with traditional approximations, such as the Born approximation. The quantitative imaging capabilities of the proposed method are enhanced by means of an original strategy, in which the features of virtual experiments are exploited to counteract the data reduction caused by the aspect limitation of the measurement configuration. Results against simulated data are reported to show the capability to successfully image nonweak scatters.

Compressive sensing (CS)-based techniques can represent a very attractive approach to inverse scattering problems. In fact, if the unknown has a sparse representation and the measurements are properly organized, CS allows to considerably reduce the number of measurements and offers the possibility to achieve optimal (or nearly optimal) reconstruction performance. Unfortunately, the inverse scattering problem is nonlinear, while CS theory is well established only for linear recovery problems. As a contribution to overcome this issue, in this letter, we introduce two different CS-inspired approaches that exploit the “virtual experiments” framework, wherein it is possible to cast the inverse scattering problems in a linear form even in the case of nonweak targets.