Time: April 20, 2017, h. 14:00 pm
Location: Room Garda, Polo scientifico e tecnologico “Fabio Ferrari”, Building Povo 1 - Povo (Trento)
Dr. Anteneh Atumo Gebremariam
Abstract of Dissertation
To cope up with the booming of data traffic and to accommodate new and emerging technologies such as machine-type communications, Internet-of-Things, the 5th Generation (5G) of mobile networks require multiple complex operations (i.e., allocating non-overlapping radio resources, monitoring interference, etc.). Software-defined networking (SDN) and network function virtualization (NFV) are the two emerging technologies that promise to provide programmability and flexibility in terms of managing, configuring and optimizing wireless networks such that a better performance is achieved. In this dissertation, we particularly focus on inter-cell-interference (ICI) mitigation techniques and efficient radio resource utilization schemes through the adoption of these two technologies in wireless environment.
We exploit the SDN approach in order to expose the lower layers (i.e., physical and medium access control) parameters of the wireless protocol stack to a centralized control module such that it is possible to dynamically configure the network in a logically centralized manner, through specifically designed network functions (algorithms). In the first part of this work, we proposed two ICI mitigation solutions, one via an Interference Graph (IG) abstraction technique to control ICI in macro base stations and the second one is through dynamic strict fractional frequency reuse technique to overcome the limitations of ICI in dense small cell base station deployments where ICI arises from frequency reuse one in multi-tier networks. Then based on the fractional frequency reuse (FFR) technique, we propose a spatial scheduling schemes that aim to schedule users in the spatial domain through layered schedulers operating in different time scales, short and long. The cell coverage area is dynamically divided into multiple scheduling areas based on the antenna beamwidth and steerable signal-tointerference-plus-noise-ratio (SINR) threshold values. Simulation results show our proposed approaches outperform the legacy static FFR schemes in terms of spectral efficiency, aggregate throughput and packet blocking probability. Moreover, we provided the detailed analysis of the computational complexity of our proposed algorithms in comparison to the once existing in the literature.
The 5G networks will be built around people and things targeted to meet the requirements different groups of uses cases (i.e., massive broadband, massive machine-type communication and critical machine-type communication). In order to support these services it is very costly and impractical to make a separate dedicated network corresponding to each of the services. The most attractive solution in terms of reducing cost at the same time improving backward compatibility is through the implementation of service- dedicated virtual networks, network slicing. Thus we proposed a dynamic spectrum-level slicing algorithm to share radio resources across different virtual networks. Through virtualization, the physical radio resources of the heterogeneous mobile networks are first abstracted into a centralized pool of virtual radio resources. Then we investigated the performance gains of our proposed algorithm though dynamically sharing the abstracted radio resources across multiple virtual networks. Simulation results show that for representative user arrival statistics, dynamic allocation of radio resources significantly lowers the percentage of dropped packets. Moreover, this work is the preliminary step towards enabling an end-to-end network slicing for 5G mobile networking, which is the base for implementing service differentiated virtual networks over a single physical infrastructure. Finally, we presented a test-bed implementation of dynamic spectrum-level slicing algorithm using an open-source software/hardware platform called OpenAirInterface that emulates the long-term evolution (LTE) protocol stack.