Cognitive resource manager framework for optimal resource allocation
type: CreativeWork
description: Wireless networks are under constant pressure to provide ever higher data rates to increasing numbers of users with greater reliability. At the same time they are becoming more complex and challenging to manage. Great efforts are being done to make the wireless devices and networks adaptive and self-optimizing in order to more efficiently use the resources and deliver good quality services. High spectral efficiency, environmental adaptivity, user-awareness and energy efficiency are highly desired features in the future networks. It has also become important to support these goals at all OSI-layers in a cross-layer manner. Making the wireless systems smarter has been a matter of research under the cognitive radio (CR) paradigm for ten years now. While CR is a very interdisciplinary and wide topic, including dynamic spectrum access and policies, flexible system architectures, learning, context awareness, cooperative networking, etc., most of the contributions so far have been limited to novel spectrum access approaches and spectrum sensing techniques. Mitola's original vision on context-sensitive smart radios was a precursor, but the current work has been still lacking precise proposal beyond high-level arguments. In this thesis we study the cognitive radios from a system point of view focusing closely on architectures, techniques and algorithms that can enable intelligent operations. We propose a modular cognitive resource manager (CRM) framework, which can facilitate a development of complex control and optimization techniques for resource management in wireless networks on diverse radio environments and problem scenarios. This work contributes towards bringing cognitive radio a step closer to practical implementation by conducting both theoretical and experimental studies of suitable optimization methods and algorithms under the proposed CRM framework. We study in this thesis automatic and adaptive system configuration mechanisms for different resource allocation p…
abstract: Wireless networks are under constant pressure to provide ever higher data rates to increasing numbers of users with greater reliability. At the same time they are becoming more complex and challenging to manage. Great efforts are being done to make the wireless devices and networks adaptive and self-optimizing in order to more efficiently use the resources and deliver good quality services. High spectral efficiency, environmental adaptivity, user-awareness and energy efficiency are highly desired features in the future networks. It has also become important to support these goals at all OSI-layers in a cross-layer manner. Making the wireless systems smarter has been a matter of research under the cognitive radio (CR) paradigm for ten years now. While CR is a very interdisciplinary and wide topic, including dynamic spectrum access and policies, flexible system architectures, learning, context awareness, cooperative networking, etc., most of the contributions so far have been limited to novel spectrum access approaches and spectrum sensing techniques. Mitola's original vision on context-sensitive smart radios was a precursor, but the current work has been still lacking precise proposal beyond high-level arguments. In this thesis we study the cognitive radios from a system point of view focusing closely on architectures, techniques and algorithms that can enable intelligent operations. We propose a modular cognitive resource manager (CRM) framework, which can facilitate a development of complex control and optimization techniques for resource management in wireless networks on diverse radio environments and problem scenarios. This work contributes towards bringing cognitive radio a step closer to practical implementation by conducting both theoretical and experimental studies of suitable optimization methods and algorithms under the proposed CRM framework. We study in this thesis automatic and adaptive system configuration mechanisms for different resource allocation p…
author: Petrova, Marina
language: eng
keywords: info:eu-repo/classification/ddc/620, Kognitiver Funk, Mehrkriterielle Optimierung, Ingenieurwissenschaften, cognitive radio, resource management, multi-objective optimization, channel allocation, minority games
date published: 2011
date modified: 2026-07-30T19:42:39Z
provider: RWTH Aachen University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Publikationsserver der RWTH Aachen University