Reduction of the envelope fluctuations of multi-carrier modulations using adaptive neural fuzzy inference systems

In this paper, a novel scheme for reducing the envelope fluctuations in multi-carrier signals applying Adaptive Neural Fuzzy Inference Systems (ANFIS) is proposed and analyzed. Once trained with signals with very low envelope fluctuations, such as those obtained by the Active Constellation Expansion - Approximate Gradient Project (ACE-AGP) algorithm, ANFIS approximately reaches a similar reduction as with ACE-AGP for multi-carrier signals without the complexity and the large convergence time of conventional ACE-AGP. We show that our approach is less complex than other previous schemes and with better performanceThis work has been partly funded by projects MULTI-ADAPTIVE (TEC2008-06327-C03-02), COMONSENS (CSD2008-00010) and AECI Program of Research Cooperation with Morocco (A/027714/09)Publicad

Etude de performance d’un système de communication ECMA-368 dans un canal réaliste Ultra Large Bande

L’ECMA-368 est une norme récente, qui décrit la couche physique ULB (PHY-UWB) pour un réseau personnel sans fil (WPAN). Dans cet article, nous allons concevoir et évaluer les performances en termes de taux d'erreur binaire (TEB) d’un système de communication qui respecte la norme ECMA-368 en utilisant les différents modèles de canal ULB définis par la norme IEEE802.15.3a et avec l’ensemble des débits binaires

Reduction of power envelope fluctuations in OFDM signals by using neural networks

One of the main drawbacks of Orthogonal Frequency Division Multiplexing (OFDM) are the large fluctuations of its power envelope. In this letter, a novel and efficient scheme based on Multilayer Perceptron (MLP) Neural Networks (NN) is proposed. The NN synthesizes the Active Constellation Expansion - (ACE) technique which is able to drastically reduce envelope fluctuations. This is achieved with much lower complexity, faster convergence, and better performance compared to previously available methods.This work has been partly funded by the projects MULTI-ADAPTIVE (TEC2008-06327-C03-02), COMONSENS (CSD2008-00010), and the AECI Program of Research Cooperation with Morocco.Publicad

High power amplifier pre-distorter based on neural-fuzzy systems for OFDM signals

In this paper, a novel High Power Amplifier (HPA) pre-distorter based on Adaptive Networks - Fuzzy Inference Systems (ANFIS) for Orthogonal Frequency Division Multiplexing (OFDM) signals is proposed and analyzed. Models of Traveling Wave Tube Amplifiers (TWTA) and Solid State Power Amplifiers (SSPA), both memoryless and with memory, have been used for evaluation of the proposed technique. After training, the ANFIS linearizes the HPA response and thus, the obtained signal is extremely similar to the original. An average Error Vector Magnitude (EVM) of 10-6 can be easily obtained with our proposal. As a consequence, the Bit Error Rate (BER) degradation is negligible showing a better performance than what can be achieved with other methods available in the literature. Moreover, the complexity of the proposed scheme is reducedThis work was supported in part by projectsMULTIADAPTIVE (TEC2008-06327-C03-02) and AECI Program of Research Cooperation with MoroccoPublicad

Diagnostic and modeling of elderly flow in a French healthcare institution

One of the highest priorities in the French health care system is to deal with the continuous growth of the percentage population older than 65 years, expected to reach 31% in 2030. This development poses enormous challenges to the operations of the health care system, especially, related to elder patients. The elderly flow in the hospital services is typically uncertain and subject to variations on the length of stay in each stage and on the path or sequence of stages followed by the patient. For that reason, we propose to model the patient flow in a hospital as a continuous-time Markov chain with an absorbing state representing the elderly discharge from the hospital. Three Markov chains are provided with different levels of details and computation complexity. The first model called aggregated provides a prediction of the length of stay per service, the second model called Coxian provides a reliable prediction of the total length of stay, and the third model called detailed provides a prediction of the length of stay per class of elderly. A classification of elderly based on multiple correspondence technique is considered before the application of the third model. Our models are fitted with the data collected from Roanne Hospital, a typical French health care structure

Subcarrier and power allocation for the downlink of multiuser OFDM transmission

In this paper, a new algorithm for subcarrier and power allocation for the downlink of multiuser OFDM transmission is presented. The proposed algorithm is more stable and it offers a lower complexity and better performance than previous existing algorithms.This work has been partly funded by the Spanish government with project TIC 2002-03498 (ORISE), Education Chamber of Madrid Community and European Social Fund.Publicad

Multi-user aub-carrier and power allocation algorithm for OFDM/Offset-QAM

In this letter, the multiuser bit and power allocation problem for an Orthogonal Frequency Division Multiplexing (OFDM)/Offset—Quadrature Amplitude Modulation (OQAM) system is investigated. The Signal-to-Interference-plus-Noise Ratio (SINR) and required power expressions for the formulation of the problem in an OFDM/OQAM system are developed. Next, a suboptimal algorithm based on this formulation is proposedThis work supported in part by Project TEC2008-06327-C03-02 and AECIPublicad