Alcatel-Lucent

About: Alcatel-Lucent is a based out in Stuttgart, Germany. It is known for research contribution in the topics: Signal & Network packet. The organization has 37003 authors who have published 53332 publications receiving 1430547 citations. The organization is also known as: Alcatel-Lucent S.A. & Alcatel.

Gauss-Newton approximation to Bayesian learning

Abstract: This paper describes the application of Bayesian regularization to the training of feedforward neural networks. A Gauss-Newton approximation to the Hessian matrix, which can be conveniently implemented within the framework of the Levenberg-Marquardt algorithm, is used to reduce the computational overhead. The resulting algorithm is demonstrated on a simple test problem and is then applied to three practical problems. The results demonstrate that the algorithm produces networks which have excellent generalization capabilities.

A Generalized Memory Polynomial Model for Digital Predistortion of RF Power Amplifiers

Abstract: Conventional radio-frequency (RF) power amplifiers operating with wideband signals, such as wideband code-division multiple access (WCDMA) in the Universal Mobile Telecommunications System (UMTS) must be backed off considerably from their peak power level in order to control out-of-band spurious emissions, also known as "spectral regrowth." Adapting these amplifiers to wideband operation therefore entails larger size and higher cost than would otherwise be required for the same power output. An alternative solution, which is gaining widespread popularity, is to employ digital baseband predistortion ahead of the amplifier to compensate for the nonlinearity effects, hence allowing it to run closer to its maximum output power while maintaining low spectral regrowth. Recent improvements to the technique have included memory effects in the predistortion model, which are essential as the bandwidth increases. In this paper, we relate the general Volterra representation to the classical Wiener, Hammerstein, Wiener-Hammerstein, and parallel Wiener structures, and go on to describe some state-of-the-art predistortion models based on memory polynomials. We then propose a new generalized memory polynomial that achieves the best performance to date, as demonstrated herein with experimental results obtained from a testbed using an actual 30-W, 2-GHz power amplifier

Large-scale complementary integrated circuits based on organic transistors

Abstract: Thin-film transistors based on molecular and polymeric organic materials have been proposed for a number of applications, such as displays and radio-frequency identification tags. The main factors motivating investigations of organic transistors are their lower cost and simpler packaging, relative to conventional inorganic electronics, and their compatibility with flexible substrates. In most digital circuitry, minimal power dissipation and stability of performance against transistor parameter variations are crucial. In silicon-based microelectronics, these are achieved through the use of complementary logic-which incorporates both p- and n-type transistors-and it is therefore reasonable to suppose that adoption of such an approach with organic semiconductors will similarly result in reduced power dissipation, improved noise margins and greater operational stability. Complementary inverters and ring oscillators have already been reported. Here we show that such an approach can realize much larger scales of integration (in the present case, up to 864 transistors per circuit) and operation speeds of approximately 1 kHz in clocked sequential complementary circuits.

Femtocells: Past, Present, and Future

Abstract: Femtocells, despite their name, pose a potentially large disruption to the carefully planned cellular networks that now connect a majority of the planet's citizens to the Internet and with each other. Femtocells - which by the end of 2010 already outnumbered traditional base stations and at the time of publication are being deployed at a rate of about five million a year - both enhance and interfere with this network in ways that are not yet well understood. Will femtocells be crucial for offloading data and video from the creaking traditional network? Or will femtocells prove more trouble than they are worth, undermining decades of careful base station deployment with unpredictable interference while delivering only limited gains? Or possibly neither: are femtocells just a "flash in the pan"; an exciting but short-lived stage of network evolution that will be rendered obsolete by improved WiFi offloading, new backhaul regulations and/or pricing, or other unforeseen technological developments? This tutorial article overviews the history of femtocells, demystifies their key aspects, and provides a preview of the next few years, which the authors believe will see a rapid acceleration towards small cell technology. In the course of the article, we also position and introduce the articles that headline this special issue.

Proof verification and hardness of approximation problems

Abstract: The class PCP(f(n),g(n)) consists of all languages L for which there exists a polynomial-time probabilistic oracle machine that used O(f(n)) random bits, queries O(g(n)) bits of its oracle and behaves as follows: If x in L then there exists an oracle y such that the machine accepts for all random choices but if x not in L then for every oracle y the machine rejects with high probability. Arora and Safra (1992) characterized NP as PCP(log n, (loglogn)/sup O(1)/). The authors improve on their result by showing that NP=PCP(logn, 1). The result has the following consequences: (1) MAXSNP-hard problems (e.g. metric TSP, MAX-SAT, MAX-CUT) do not have polynomial time approximation schemes unless P=NP; and (2) for some epsilon >0 the size of the maximal clique in a graph cannot be approximated within a factor of n/sup epsilon / unless P=NP. >