The development of cellular communications during the 1980s made wireless networks
one of the most important areas of technology. Fueled by the advances in wireless computer
networks, high data rate connections have recently become the focus of research
in the communication domain. The growth of the Internet and the introduction of a
multitude of applications culminated in a new era of communications in which wireless
networks play a very important role.
However, the wireless environment still offers some challenges that need to be addressed
before reaching the prerequisites of future wireless networks. Due to imprecise
channel characterization, much of the potential of the wireless environment is wasted.
Furthermore, the requirements caused by multiple connections lead to the use of multiple
access schemes that were not designed to cope with some of the wireless environment
phenomenons. These two points are treated in this thesis.
The first part of this thesis is dedicated to the use of probability theory tools that
enable the creation of models based only on partial knowledge of the environment. Using
Jaynes' maximum entropy principle, we present a framework that allows us to infer on
the channel characteristics by choosing probability distributions that maximize entropy
under the constraints that represent our state of knowledge. This technique is considered
as the most reliable method to perform inferences. Models for two different types of environment
are derived: wideband channels and multiple-input multiple-output (MIMO)
In the second part, the multiple access problem for ultra wideband (UWB) systems
is assessed. Despite the large amount of work conducted during recent years on UWB
technology, no scheme can cope with the high dispersion of UWB channels and still offer
reasonable spectral efficiency. An innovative scheme that exploits the users' channels
to guarantee multiple access is introduced, entitled Channel Division Multiple Access
(ChDMA). This scheme provides a very simple solution and achieves high spectral efficiency.