2 research outputs found

    Topology Management for Wireless Mesh Self-Organizing Mobile Backhauls

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    The mobile data consumption is increasing exponentially, creating demand for more capacity from the network. Cell densification with small cells, also known as Heterogeneous networks, is seen as a solution for the capacity problem. On the downside, this creates a problem for providing a cost-effective backhaul connection to these small cells. The Self-optimizing Wireless Mesh Network (SWMN) backhaul has been proposed as a backhaul solution for small cells. In SWMN, the nodes form a partial mesh topology, where routing and data transmission is based on pre-computed prioritized set of routes and link-schedules. Hence, an entity that handles topology management functionalities is required, which enables automatic network configuration, network monitoring, optimization and management. The main aim of this thesis is to verify the topology management functionalities. The work involved development of a simulator for creating test topology scenarios. Additionally, the task involved verifying the feasibility of functionalities in the proof-of-concept system

    Traffic-Aware User Association in Heterogeneous LTE/WiFi Radio Access Networks

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    WiFi networks are known to be a cost-efficient traffic offloading solution for mobile networks. The Multi Access Packet Data Network Connectivity is a feature introduced in LTE Release 10 in order to allow users to be simultaneously connected to multiple radio access networks (RAN). Although this feature brings many advantages, such as the possibility to implement QoS-based traffic steering, it poses also many challenges, one of which is distributing traffic among the two radio access technologies. In this paper, we propose a traffic- aware user association algorithm for heterogeneous LTE/WiFi RANs. The proposed algorithm is formulated as an Integer Linear Programming (ILP) problem jointly optimizing user association and resource allocation. A heuristic is also proposed in order to address the scalability issues of the ILP-based algorithm. Numerical simulations are used in order to compare the proposed approaches. Finally, we implemented and tested the heuristic in small-scale testbed using the 5G-EmPOWER platform
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