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Digital predistortion (DPD) is an effective linearization technique for RF power amplifiers (PAs), but conventional full sampling (FS) DPD systems use ADCs with three to five times signal bandwidth, and high-speed ADCs are expensive and power-hungry. In this article, we develop a novel band-limited DPD for reducing feedback sampling rate and acquisition bandwidth based on a general framework for semisupervised learning called manifold regularization (MR), which utilizes the geometry of unlabeled data to construct regularization terms for mitigating the overfitting problem. Considering the properties of DPD, we design a basis MR term and introduce it into the classical MR to obtain the extended MR (ExMR) method. To validate the proposed ExMR DPD method, experiments were conducted on two different RF PAs operating at 2.4 and 39 GHz, respectively. The test results demonstrate that the proposed ExMR DPD can linearize the RF PA with a 40-MHz acquisition bandwidth at 100-MHz input. The proposed method significantly reduces the cost and power consumption of the DPD system in comparison with the conventional FS DPD method, which provides a promising solution for broadband communication systems. [ABSTRACT FROM AUTHOR]

SUMMARY Taking place within more extensive work that focuses on hybrid methods in aeroacoustics, the present study is devoted to the data transfer operations that are to be performed between two stages of a hybrid calculation. More precisely, the article focuses on two typical operations that usually accompany such data transfer, which are (i) the sampling rate reduction and (ii) the interpolation of the unsteady perturbations to be transmitted from one stage to the other. First part of the paper analyzes the two main issues of such operations, which are the spuriousing and the aliasing phenomena. For doing so, the usual notions of the interpolation theory are revisited before they are synthesized within an original approach. The here proposed formalism allows to understand better both the spuriousing and the aliasing phenomena, as well as to accurately predict the impact of the latter on the data to be transmitted in terms of signal degradation. Second part of the paper provides an illustration and a validation of these theoretical developments via a direct application to a typical aerodynamic noise problem (aeroacoustic emission by a 2 D cylinder cross flow). There, it is further shown how the here proposed formalism can help in improving aeroacoustics hybrid calculations by predicting (and thus possibly minimizing) the bias to be induced on the acoustic extrapolation stage because of the aliasing and/or spuriousing effects inherited from the sampling rate reduction and/or interpolation of CFD data-which is likely to occur in any hybrid scenario. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A novel pseudo noise code acquisition combined with the newly proposed adaptive sampling rate and threshold control (ASTC) algorithm is derived for low-power spread-spectrum systems with complementary metal-oxide-semiconductor implementations. Low-power performance can be achieved by reducing the sampling rate of the proposed system while maintaining the system performance. The sampling rate is dynamically updated due to the change of the channel noise level. Under the assumptions that the channel is additive white Gaussian noise slow-fading channel, up to 74.3% reduction in power consumption compared to the conventional fixed-sampling rate and fixed-threshold architecture is demonstrated with insignificant increase of system complexity. The proposed architecture can be applied to the design of low-power and controllable-performance spread-spectrum communication systems. [ABSTRACT FROM PUBLISHER]