Congestion control and spectrum sharing in multi-operator multi-hop wireless network
1University of Oulu, Faculty of Information Technology and Electrical Engineering, Department of Communications Engineering, Communications Engineering
|Online Access:||PDF Full Text (PDF, 22.1 MB)|
|Persistent link:|| http://urn.fi/URN:NBN:fi:oulu-201503111139
|Publish Date:|| 2015-03-16
|Thesis type:||Master's thesis (tech)
Emergence of dramatic increase in applications provided by smart devices, such as smart phones, is no longer supported by traditional telecommunications systems such as wireless cellular systems. Arising challenges are ever increasing traffic demand, shortage of available spectrum and congestion over wireless systems. On the other hand, network resources such as spectrum and computational capability, are severely under-utilized. With regard to efficient use the available resources, promising trend is to develop heterogeneous networks (HetNets) such that different operators can share their excess capacities among themselves with the previous agreement. The most research done in spectrum sharing is focused only on the network access point. In this thesis work we extend the modelling of the spectrum sharing problem to include all links on the route for a given session. While this problem might have been analyzed from the point of view of route availability our control system is focused on queue management across the network that maintains predetermined spectra sharing rules at the session level of each operator. Addressing an issue of congestion over wireless system different congestion control mechanisms are presented and analyzed enabling a variety of options for managing traffic across the spectra sharing network. These models are generalized to include different pricing mechanisms. Two approaches are taken for analyzing pricing models with congestion control mechanism. First, network nodes are modeled as two-dimensional Markov processes. Since memoryless nature of Markov process imposes restrictions on analyzed system, in order to generalize analysis, averaged non-Markov models are introduced. Performance metric used for assessing different models is average packet dropping rate.
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