Search results for: M. Belkasmi

Authors: Fouad Ayoub, Mohammed Lahmer, Mostafa Belkasmi, El Houssine Bouyakhf

Abstract:

In this paper we present a study of the impact of connection schemes on the performance of iterative decoding of Generalized Parallel Concatenated block (GPCB) constructed from one step majority logic decodable (OSMLD) codes and we propose a new connection scheme for decoding them. All iterative decoding connection schemes use a soft-input soft-output threshold decoding algorithm as a component decoder. Numerical result for GPCB codes transmitted over Additive White Gaussian Noise (AWGN) channel are provided. It will show that the proposed scheme is better than Hagenauer-s scheme and Lucas-s scheme [1] and slightly better than the Pyndiah-s scheme.

Keywords: Generalized parallel concatenated block codes, OSMLD codes, threshold decoding, iterative decoding scheme, and performance.

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Authors: A. Khafaji, R. Saadane, J. El Abbadi, M. Belkasmi

Abstract:

The main objectif of this paper is to present a tool that we have developed subject to characterize and modelling indoor radio channel propagation at millimetric wave. The tool is based on the ray tracing technique (RTT). As, in realistic environment we cannot neglect the significant impact of Human Body Shadowing and other objects in motion on indoor 60 GHz propagation channel. Hence, our proposed model allows a simulation of propagation in a dynamic indoor environment. First, we describe a model of human body. Second, RTT with this model is used to simulate the propagation of millimeter waves in the presence of persons in motion. Results of the simulation show that this tool gives results in agreement with those reported in the literature. Specially, the effects of people motion on temporal channel properties.

Keywords: Simulation. 60 GHz band, Ray Tracing Technique, Indoor channel, Propagation, Human Body Model, Level crossing rate,

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Authors: Hassan Berbia, Faissal Elbouanani, Rahal Romadi, Mostafa Belkasmi

Abstract:

This paper introduces two decoders for binary linear codes based on Metaheuristics. The first one uses a genetic algorithm and the second is based on a combination genetic algorithm with a feed forward neural network. The decoder based on the genetic algorithms (DAG) applied to BCH and convolutional codes give good performances compared to Chase-2 and Viterbi algorithm respectively and reach the performances of the OSD-3 for some Residue Quadratic (RQ) codes. This algorithm is less complex for linear block codes of large block length; furthermore their performances can be improved by tuning the decoder-s parameters, in particular the number of individuals by population and the number of generations. In the second algorithm, the search space, in contrast to DAG which was limited to the code word space, now covers the whole binary vector space. It tries to elude a great number of coding operations by using a neural network. This reduces greatly the complexity of the decoder while maintaining comparable performances.

Keywords: Block code, decoding, methaheuristic, genetic algorithm, neural network

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