Adaptive gain and delay mismatch cancellation for LINC transmitter

Linear amplification with Nonlinear Component (LINC) transmitter architecture is an efficient solution for high efficiency amplification of signals. Nonetheless, this solution suffers both from gain impairment and delay mismatch between the two signal paths. Indeed, a mismatch in propagation time between the paths degrades the quality of the transmit signal but also disrupts the convergence of the gain correction algorithm resulting in a degradation of its performance. In this paper, we present an adaptive algorithm based on a gradient descent formulation for the identification and correction of these delays. We also demonstrate its effectiveness when applied prior to the gain adjustment procedure. The identification approach is preferred here, to ensure monitoring facilities.     

Envelope and phase delays correction in an EER radio architecture

This article deals with synchronization in the Envelope Elimination and Restoration (EER) type of transmitter architecture. To illustrate the performances of such solution, we choose to apply this architecture to a 64 carriers 16QAM modulated OFDM. We first introduce the problematic of the realisation of a highly linear transmitter. We then present the Envelope Elimination and Restoration solution and draw attention to its major weakness: a high sensitivity to desynchronization between the phase and envelope signal paths. To address this issue, we propose an adaptive synchronization algorithm relying on a feedback loop, a Least Mean Square formulation and involving an interpolation step. It enables the correction of delay mismatches and tracking of possible variations. We demonstrate that the quality of the interpolator has a direct impact on Error Vector Magnitude (EVM) value and output spectrum. Implementation details are provided along with an analysis of the behaviour and performances of the method. We present Agilent-ADS and Matlab simulation results and then focus on the enhancement of the transmitter performances using the proposed algorithm.     

Acute and subchronic experiments on the effects of microcrystalline cellulose on various pharmacological and biochemical parameters in mongrel rabbits

The subchronic intravenous application of microcrystalline cellulose (MCC), in a dose of 5 mg/kg twice weekly for 10 weeks, resulted in servere crystal embolism in the lungs of the animals. The clinical parameters were either unchanged (erythrocyte and leucocyte counts, differential blood picture, osmotic resistance of the erythrocytes, total serum bilirubin, serum protein and serum protein fractions) or slightly pathological (hemoglobin content, hematocrit, GOT and GPT). The results from tests of the liver function (by means of bromosulphthaleine clearance) and of the renal function as well as the ophthalmologic examination were not indicative of damaged parenchyma or disturbed microcirculation. Intra-arterial infusions of MCC affected the peripheral muscular blood supply, blood pressure and heart rate.     

A transmitter architecture for nonconstant envelope modulation

This paper presents a transmitter architecture which is less sensitive to power amplifier AM/AM and AM/PM conversions. Indeed, most radio communication standards employ nonconstant envelope modulation such as in the 802.11 series. Owing to power amplifiers' nonlinearities, distortions on the modulations degrade the overall transmitter performance. As a consequence, linearization methods, such as envelope elimination and restoration, have to be employed. The architecture relies on the transformation of a nonconstant envelope modulation to a constant or switched one. This signal coding enables the efficient amplification of the signal without undergoing power amplifier distortions. The envelope variation is restored by bandpass filtering just after the power amplifier.     

On minimum Fisher information distributions with restricted support and fixed variance

Fisher information is of key importance in estimation theory. It also serves in inference problems as well as in the interpretation of many physical processes. The mean-squared estimation error for the location parameter of a distribution is bounded by the inverse of the Fisher information associated with this distribution. In this paper we look for minimum Fisher information distributions with a restricted support. More precisely, we study the problem of minimizing the Fisher information in the set of distributions with fixed variance defined on a bounded subset S of R or on the positive real line. We show that the solutions of the underlying differential equation can be expressed in terms of Whittaker functions. Then, in the two considered cases, we derive the explicit expressions of the solutions and investigate their behavior. We also characterize the behavior of the minimum Fisher information as a function of the imposed variance.     

Estimating the entropy of a signal with applications

We present a new estimator of the entropy of continuous signals. We model the unknown probability density of data in the form of an AR spectrum density and use regularized long-AR models to identify the AR parameters. We then derive both an analytical expression and a practical procedure for estimating the entropy from sample data. We indicate how to incorporate recursive and adaptive features in the procedure. We evaluate and compare the new estimator with other estimators based on histograms, kernel density models, and order statistics. Finally, we give several examples of applications. An adaptive version of our entropy estimator is applied to detection of law changes, blind deconvolution, and source separation