test_moissonnage_selune
type: Agent

Decision making algorithms for cognitive radio and optimization of the reconfigurability mapping for the numerical architecture of implementation
type: Distribution
access URL: https://theses.hal.science/tel-00931350
format: HTML
issued: 2026-05-05T10:28:55.105398
modified: 2026-05-05T10:28:55.080012

Decision making algorithms for cognitive radio and optimization of the reconfigurability mapping for the numerical architecture of implementation
type: Dataset
contact point: Organization
  fn: CCSD
keyword: green-radio
keyword: cognitive-radio
keyword: radio-intelligente
keyword: computational-complexity
keyword: prise-de-decision
keyword: decision-making
keyword: complexite-de-calcul
keyword: theses
keyword: eco-radio
keyword: spiotherengineering-sciences-physicsother
keyword: infoeu-reposemanticsdoctoralthesis
landing page: https://theses.hal.science/tel-00931350
description: In this thesis we focus on the development of a decision making method for the cognitive radio receiver that dynamically adapts to its environment. The approach that we use is based on the statistical modeling of the radio environment. By statistically characterizing the observations provided by the radio sensor, we set up statistical decision rules that take into account the observations’ errors. This helps to minimize the rate of bad decisions. Also, we aim to use the intelligent capacities to reduce the computational complexity in the receiver chain. Indeed, we identify decision scenarios that limit some operators. In particular, we address two decision scenarios that adapt the presence of the equalization and of the beamforming to the environment. The limitation of these two operations helps to reduce the computational complexity in reception. Finally, we integrate our decision method and the two decision scenarios in a management architecture of reconfiguration and intelligence.
identifier: NNT: 2013SUPL0027
issued: 2026-05-05T10:28:55.096648
language: fr
modified: 2026-05-05T10:28:55.096654