Every new generation of mobile systems should provide higher capacity, serve more users, be more energy efficient, and have lower cost. Radio-access hardware constitutes a major bottleneck for reaching these goals, which is a particularly noticeable issue now that 5G communication systems are being developed. A combination of breakthroughs in communication theory-as in massive multiple input/multiple output (MIMO) [1], highly integrated semiconductor and packaging technologies, and extended spectrum allocations- has enabled a paradigm shift in the way radio hardware will be realized. Today's high-power, fewantenna, sectorized systems will soon be replaced with highly integrated active antenna systems having up to hundreds of individually driven low-power radios operating with very wideband signals.

This article attempts to improve the average efficiency and linearize the work-horse of RF power amplification- the class-B (or class AB) PA-relying, for example, on predistortion, dynamic load modulation or ET. Nevertheless, whenever higher efficiencies are desired, the current-mode class-B PA must be replaced by switchedmode PAs (for example, class-E or class-F), completely modifying the paradigm of RF amplification. In fact, as these are saturated circuits, they cannot respond to excitations of variable amplitude; and thus the original signal envelope must be restored by operating the PA as an AM modulator via dynamic supply adaptation. A good example of this is the EER arrangement.

This paper presents an efficient and effective approach to pruning the Volterra series for behavioral modeling of RF and microwave power amplifiers. Rather than adopting a pure "black-box" approach, this model pruning technique is derived from a physically meaningful block model, which has a clear linkage to the underlying physical behavior of the device. This allows all essential physical properties of the PA to be retained, but significantly reduces model complexity by removing unnecessary coefficients from the general Volterra series. A reduced-order model of this kind can be easily extracted from standard time/frequency-domain measurements or simulations, and may be simply implemented in system-level simulators. A complete physical analysis and a systematic derivation are presented, together with both computer simulations and experimental validations

The highly dynamic nature of some sandy shores with continuous morphological changes require the development of efficient and accurate methodological strategies for coastal hazard assessment and morphodynamic characterisation. During the past decades, the general methodological approach for the establishment of coastal monitoring programmes was based on photogrammetry or classical geodetic techniques. With the advent of new geodetic techniques, space-based and airborne-based, new methodologies were introduced in coastal monitoring programmes. This paper describes the development of a monitoring prototype that is based on the use of global positioning system (GPS). The prototype has a GPS multiantenna mounted on a fast surveying platform, a land vehicle appropriate for driving in the sand (four-wheel quad). This system was conceived to perform a network of shore profiles in sandy shores stretches (subaerial beach) that extend for several kilometres from which high-precision digital elevation models can be generated. An analysis of the accuracy and precision of some differential GPS kinematic methodologies is presented. The development of an adequate survey methodology is the first step in morphodynamic shore characterisation or in coastal hazard assessment. The sample method and the computational interpolation procedures are important steps for producing reliable three-dimensional surface maps that are real as possible. The quality of several interpolation methods used to generate grids was tested in areas where there were data gaps. The results obtained allow us to conclude that with the developed survey methodology, it is possible to Survey sandy shores stretches, under spatial scales of kilometers, with a vertical accuracy of greater than 0.10 m in the final digital elevation models

Modern and future transmitter architectures are being driven toward multi-input multi-output (MIMO) transceivers, which make use of several radio frequency (RF) power amplifiers (PAs) to drive an antenna array. When moving to high integration scenarios, as is expected for fifth-generation communications, the isolation between the array and the PAs is often removed. Since the array elements are electromagnetically coupled, the waves fed to the antennas are also driving the output ports of the PAs. This effect creates an apparent variable load at the output of each PA, depending on the operation of the transmitter. In this system, the behavior of each PA cannot be fully described solely as a function of its input, as it will change according to the coupled signal. To predict and understand the behavior of these MIMO systems, simulation becomes a powerful tool. These simulators should be able to reproduce the main figures of merit (FoMs) of the transmitter, namely, output power, distortion, and efficiency. In this paper, we show how a recently proposed dc behavior model and an RF signal behavior model can be used in simulation setups to predict the MIMO transmitter FoMs of interest.