Adaptive optimisation of MIMO Channel for Smart sensor networks

The aim of this work is to study from a signal processing point of view the use of MIMO (Multiple Input Multiple Output) communication systems for algorithms dedicated to wireless sensor networks. We investigate energy-constrained wireless sensor networks and we focus on cluster topology of the network. This topology permits for the use of MIMO communication system model. First, we review different aspects that characterize the wireless sensor network. Then, we introduce the existing strategies for energy conservation in the network. The basic concepts of MIMO systems are presented in the second chapter and numerical results are provided for evaluating the performances of MIMO techniques. Of particular interest, polarization diversity over rich scattering environment is studied. Thereafter, beamforming approach is proposed for the development of an original localization algorithm in wireless sensor network. The novel algorithm is described and performances are evaluated by simulation. We determine the optimal system configuration between a pair of clusters that permits for the highest capacity to energy ratio in the fourth chapter. The final chapter is devoted to sensor nodes selection in wireless sensor network. The aim of using such technique is to make energy conservation in the network.

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Source https://theses.hal.science/tel-00745006
Author Ben Zid, Maha
Maintainer CCSD
Last Updated October 30, 2026, 13:40 (UTC)
Created October 30, 2026, 13:40 (UTC)
Identifier NNT: 2012GRENT017
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Grenoble Images Parole Signal Automatique (GIPSA-lab) ; Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS)
creator Ben Zid, Maha
date 2012-07-09T00:00:00
harvest_object_id fe9f5ab5-b5e7-4e23-9f46-03531a900e2a
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-10-23T00:00:00
relation info:eu-repo/semantics/altIdentifier/doi/10.70675/45342737z553az4c8cz8749z70e18c658d0b
set_spec type:THESE