The world of information technology and communications is in a stage of continuous improvement. These new developments are accompanied by a very rapid data traffic growth, particularly for mobile wireless networks. An important effect is the increase of the consumed energy by the network, particularly the radio access section, i.e. the base station systems. This latter issue causes that operational costs associated to energy consumption become more significant for telecommunication operators. In addition to the question of the availability of energy, this problem has an ecological aspect, due to the CO2 emissions associated with the operation of the network but also an issue related to public health given the effects of electromagnetic radiation from wireless transmission. For these reasons, great research efforts in the so-called field of Green Radio are being done in the recent years. The aim of this thesis consisted of finding ways to reduce the energy consumption in wireless and mobile networks respecting the QoS levels assigned to users. After a study of the state of the art analysing the possible approaches, we proposed a set of energy efficient techniques supported on the cell breathing and hybrid cellular networks (macro/femtocells). Our proposed decision making mechanisms include distributed strategies and other features such as the use of a novel multimetric approach. In our work, we also take into account the energy consumption of mobile devices, an issue that to the best of our knowledge was not quite analysed so far. The use of renewable energy sources is also considered into our proposals. Our thesis work includes the study of the consequences of our radio resource management algorithms on the electromagnetic radiation taking into account the acceptable EM exposure thresholds. In the perspectives of future work, we can mention the improvement of our techniques with learning mechanisms and cognitive radio.
| Identifer | oai:union.ndltd.org:CCSD/oai:tel.archives-ouvertes.fr:tel-00959467 |
| Date | 13 December 2013 |
| Creators | SUAREZ RIVERA, Luis Alberto |
| Source Sets | CCSD theses-EN-ligne, France |
| Language | English |
| Detected Language | English |
| Type | PhD thesis |
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