Dynamic selection and estimation of the digital predistorter parameters for power amplifier linearization

© © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents a new technique that dynamically estimates and updates the coefficients of a digital predistorter (DPD) for power amplifier (PA) linearization. The proposed technique is dynamic in the sense of estimating, at every iteration of the coefficient's update, only the minimum necessary parameters according to a criterion based on the residual estimation error. At the first step, the original basis functions defining the DPD in the forward path are orthonormalized for DPD adaptation in the feedback path by means of a precalculated principal component analysis (PCA) transformation. The robustness and reliability of the precalculated PCA transformation (i.e., PCA transformation matrix obtained off line and only once) is tested and verified. Then, at the second step, a properly modified partial least squares (PLS) method, named dynamic partial least squares (DPLS), is applied to obtain the minimum and most relevant transformed components required for updating the coefficients of the DPD linearizer. The combination of the PCA transformation with the DPLS extraction of components is equivalent to a canonical correlation analysis (CCA) updating solution, which is optimum in the sense of generating components with maximum correlation (instead of maximum covariance as in the case of the DPLS extraction alone). The proposed dynamic extraction technique is evaluated and compared in terms of computational cost and performance with the commonly used QR decomposition approach for solving the least squares (LS) problem. Experimental results show that the proposed method (i.e., combining PCA with DPLS) drastically reduces the amount of DPD coefficients to be estimated while maintaining the same linearization performance.Peer ReviewedPostprint (author's final draft

Lessons Learned and Next Steps in Energy Efficiency Measurement and Attribution: Energy Savings, Net to Gross, Non-Energy Benefits, and Persistence of Energy Efficiency Behavior

This white paper examines four topics addressing evaluation, measurement, and attribution of direct and indirect effects to energy efficiency and behavioral programs: Estimates of program savings (gross); Net savings derivation through free ridership / net to gross analyses; Indirect non-energy benefits / impacts (e.g., comfort, convenience, emissions, jobs); and, Persistence of savings

Supply Curves for Conserved Electricity

In this paper, we introduce a new top-down approach to modeling the effects of publicly financed energy-efficiency programs on electricity consumption and carbon dioxide emissions. The approach draws on a partial-adjustment econometric model of electricity demand and represents the results of a reverse auction for electricity savings from different levels of public investment. The model is calibrated to recent estimates of the cost-effectiveness of rate payer–funded efficiency programs at reducing electricity consumption. The results suggest that supply curves for conserved electricity are upward sloping, convex, and dependent on policy design and electricity prices. Under the scenarios modeled, electricity savings of between 1 and 3 percent are achievable at a marginal cost of $50 per megawatt hour (MWh) and a corresponding average cost of$25–$35/MWh.energy efficiency, climate change

EU Merger Remedies: A Preliminary Empirical Assessment

Mergers that substantially lessen competition are challenged by antitrust authorities. Instead of blocking anticompetitive transitions straight away, authorities might choose to negotiate with the merging parties and allow the transactions to proceed with modifications that restore or preserve the competition in the involved markets. We study a sample of 167 mergers that were under the European Commission’s scrutiny from 1990 to 2002. We use an event study methodology to identify the potential anticompetitive effects of mergers as well as the remedial provisions on these transactions. Stock market reactions around the day of the merger’s announcement provide information on the first question, whereas the stock market reactions around the commission’s final decision day convey information about the outcome of the bargaining process between the authority and the merging parties. We first classify mergers according to their effects on competition and then we develop hypotheses on the effects that remedies are supposed to achieve depending on the merger’s competitive outcome. We isolate several stylized facts. First, we find that remedies were not always appropriately imposed. Second, the market seems to be able to predict remedies’ effectiveness when applied in phase I. Third, the market also seems able to produce a good prior to phase II’s clearances and prohibitions, but not to remedies. This can be due either to a measurement problem or related to the increased merging firms’ bargaining power during the second phase of the merger review

Generating reversible circuits from higher-order functional programs

Boolean reversible circuits are boolean circuits made of reversible elementary gates. Despite their constrained form, they can simulate any boolean function. The synthesis and validation of a reversible circuit simulating a given function is a difficult problem. In 1973, Bennett proposed to generate reversible circuits from traces of execution of Turing machines. In this paper, we propose a novel presentation of this approach, adapted to higher-order programs. Starting with a PCF-like language, we use a monadic representation of the trace of execution to turn a regular boolean program into a circuit-generating code. We show that a circuit traced out of a program computes the same boolean function as the original program. This technique has been successfully applied to generate large oracles with the quantum programming language Quipper.Comment: 21 pages. A shorter preprint has been accepted for publication in the Proceedings of Reversible Computation 2016. The final publication is available at http://link.springer.co

BeSpaceD: Towards a Tool Framework and Methodology for the Specification and Verification of Spatial Behavior of Distributed Software Component Systems

In this report, we present work towards a framework for modeling and checking behavior of spatially distributed component systems. Design goals of our framework are the ability to model spatial behavior in a component oriented, simple and intuitive way, the possibility to automatically analyse and verify systems and integration possibilities with other modeling and verification tools. We present examples and the verification steps necessary to prove properties such as range coverage or the absence of collisions between components and technical details

How Life Experience Shapes Cognitive Control Strategies: The Case of Air Traffic Control Training

Although human flexible behavior relies on cognitive control, it would be implausible to assume that there is only one, general mode of cognitive control strategy adopted by all individuals. For instance, different reliance on proactive versus reactive control strategies could explain inter-individual variability. In particular, specific life experiences, like a highly demanding training for future Air Traffic Controllers (ATCs), could modulate cognitive control functions. A group of ATC trainees and a matched group of university students were tested longitudinally on task-switching and Stroop paradigms that allowed us to measure indices of cognitive control. The results showed that the ATCs, with respect to the control group, had substantially smaller mixing costs during long cue-target intervals (CTI) and a reduced Stroop interference effect. However, this advantage was present also prior to the training phase. Being more capable in managing multiple task sets and less distracted by interfering events suggests a more efficient selection and maintenance of task relevant information as an inherent characteristic of the ATC group, associated with proactive control. Critically, the training that the ATCs underwent improved their accuracy in general and reduced response time switching costs during short CTIs only. These results indicate a training-induced change in reactive control, which is described as a transient process in charge of stimulus-driven task detection and resolution. This experience-based enhancement of reactive control strategy denotes how cognitive control and executive functions in general can be shaped by real-life training and underlines the importance of experience in explaining inter-individual variability in cognitive functioning