| dc.description.abstract | The demand for wireless data is continuously rising and is expected to
increase. To cope with this growth, it is necessary to work towards higher
network capacity and improved network capabilities.
In the recent period, opportunistic concepts started to take hold and
being part of research into communication technologies. Opportunistic
Scheduling (OS) is a scheduling approach for wireless channels, where channel
quality is considered, when making scheduling decisions. The scheduler
transmits to users with relatively better signal quality, so the average
amount of transmitted data can be increased. The focus of this thesis
will be on OS as a method for increasing the transmission eciency and
its implementation in wireless networks. The main research topic of the
dissertation is thus multicasting with OS, i.e. Opportunistic Multicasting
(OM), and its adaptation to Cognitive Radio (CR) and Multimedia Broadcast
multicast service Single Frequency Network (MBSFN) networks. More
speci cally, how it ts into the these types of networks and what kind of
obstacles need to be tackled, before OM can be successfully deployed.
First we study the theory of Multiuser Diversity (MUD) and provide
a novel concept unifying internal and external MUD, enabling us to formulate
the system sum and user throughput. The resulting CR algorithm
design approaches the derived throughput advantage. Second, we look
at Signal-to-interference-plus-noise Ratio (SINR) distribution in MBSFN
networks and Spectrum Eciency (SE) of OM under extended Modulation
and Coding Scheme (MCS) adaptation interval. Using the results, we design
a low feedback, low complexity, and slow MCS change based algorithm
suited for MBSFN.
The resulting algorithm designs are well suited to the studied CR
and MBSFN networks. Extensive simulations show, that the presented
algorithm designs perform better than previous designs, enabling better
quality service to users. | en_US |