Pedro M. Lavrador

The Linearity-Efficiency Compromise

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.

Modeling nonlinear behavior of band-pass memoryless and dynamic systems

This paper addresses nonlinear distortion arising in microwave band-pass memoryless and dynamic systems, focusing on wideband power amplifiers (PA). It first identifies the minimum requirements for their correct representation. Then, it shows that the complex behavior of long term memory effects does not allow a unique characterization procedure, but requires various nonlinear distortion figures according to the type of nonlinear RF impairments the actual system is sensitive to.

A Multiple Time-Scale Power Amplifier Behavioral Model for Linearity and Efficiency Calculations

This work describes a new power amplifier, PA, behavioral model intended to predict both the PA amplitude and phase input-output signal relationship and the average or instantaneous dc power consumption and thus average or instantaneous signal-dependent efficiency. Hence, contrary to other previously published PA behavioral models, such a model is not only capable of describing the complex low-pass equivalent fundamental zone output, but also the real low-pass current consumption output. In addition, a special attention is paid to accurately account for the multiple time-scale dynamics shown by modern GaN HEMT based high power amplifiers.

A new Volterra series based orthogonal behavioral model for power amplifiers

In this paper a Volterra series based behavioral model for active nonlinear RF power amplifiers is presented. The proposed models main advantage is the possibility of extraction of its parameters orthogonally. Some validation results are presented both in the time and frequency domains, using an IS-95 CDMA signal.

Rational function-based model with memory for power amplifier behavioral modeling

Polynomials have been extensively used to model power amplifier (PA) behavior because of their linearity in the parameters, which eases their identification. However, these models are inherently local, being unable to extrapolate the PA behavior for conditions not considered during model extraction. This paper presents a model which, based on the ratio of two polynomials, avoids the catastrophic error degradation of polynomials (being thus suitable for large-signal behavior prediction) but still can be extracted using linear regression techniques. This model is tested with measured data from a class-AB PA.

Stimuli-responsive nanocarriers for delivery of bone therapeutics – Barriers and progresses

&NA; The development of stimuli‐responsive nanomedicines with tunable cargo release is gathering an increased applicability in bone regeneration and precision biomedicine. Yet, the formulation of nanocarriers that explore skeletal‐specific stimuli remains remarkably challenging to materialize due to several endogenous and disease‐specific barriers that must be considered during particle design stages. Such anatomo‐physiological constrains ultimately hinder nanocarriers bioavailability in target bone tissues and impact the overall therapeutic outcome. This review aims to showcase and critically discuss the hurdles encountered upon responsive nanocarriers delivery in the context of skeletal diseases or tissue regeneration scenarios. Such focus is complemented with an in‐depth and up‐to‐date analysis of advances in the development of stimuli‐responsive, bone‐focused delivery systems. In a holistic perspective, a deeper knowledge of human osteology combined with advances in materials functionalization via simple precision‐chemistry is envisioned to incite the manufacture of stimuli‐triggered nanomedicines with more realistic potential for clinical translation.

A new power amplifier behavioral model for simultaneous linearity and efficiency calculations

This paper proposes an innovative power amplifier, PA, low-pass equivalent behavioral model, BM, intended to enable the simultaneous prediction of linearity and efficiency in modern wireless transmitter chains. Contrary to the main PA behavioral modeling stream that has been exclusively focused in predicting the devices input-output power characteristics in the fundamental zone, this new model also provides the system designer with predictions of the PA absorbed dc power, this way enabling power efficiency calculations. For that, this new BM gives the fundamental output current or voltage across the load, as well as the base-band current flowing from the power supply to the PA dc bias terminal, Idc. Beyond the model format, a model extraction methodology and the corresponding laboratory test bench are shown. These were then validated comparing static and dynamic Idc-versus-Vin modeled and experimental data.

A Formal Procedure for Microwave Power Amplifier Behavioral Modeling

This work presents a formal behavioral modeling procedure for microwave power amplifier devices. By relying on the solid background of nonlinear system identification theory, a new behavioral model formulation was especially conceived to simplify the parameter set extraction from measurements made in a microwave laboratory. Indeed, the model now proposed is an optimal approximator of the real PA, for the nonlinear order considered, and is extracted, in a separable way, from measurements of the PA response when the device is excited by one of the easiest signals to generate in a RF laboratory: a multi-sine

Nonlinear compensation with DBP aided by a memory polynomial

Using digital backpropagation (DBP) based on the split step Fourier method (SSFM) aided by a memory polynomial (MP) model, we demonstrate an improved DBP approach for fiber nonlinearity compensation. The proposed technique (DBP-SSFM&MP) is numerically validated and its performance and complexity are compared against the benchmark DBP-SSFM, considering a single-channel 336 Gb/s PM-64QAM transmission system. We demonstrate that the proposed technique allows to maintain the performance achieved by DBP-SSFM, while decreasing the required number of iterations, by over 60%. For a transmission length of 1600 km we obtain a complexity reduction gain of 50.7% in terms of real multiplications in comparison with the standard DBP-SSFM.

Higher locality non-linear basis functions of Volterra series based models to improve extraction conditioning

Extraction of Volterra based nonlinear systems models can be hindered by conditioning problems. This is especially true when working with low precision arithmetic, typical of hardware implemented DPD systems. Traditionally, monomials are chosen as the basis functions because they are continuous and easy to manipulate, although other bases could be used. Spline bases, for example, have been chosen instead of polynomials for their increased locality. However, we now show that it is also possible to construct polynomials with increased locality and thus, keeping continuity but still improving the condition numbers of the regression matrix. This polynomial basis can be seen as a bridge between LUT and polynomial models.