The exponentially increasing traffic demand for mobile services requires innovative solutions in both access and backhaul segments of 5th generation (5G) mobile networks. Although, heterogeneous networks (HetNets) are a promising solution for the wireless access, the backhaul segment has received considerably less attention and falls short in meeting the stringent requirements of 5G in terms of capacity and availability. HetNets together with mobility requirements motivate the use of microwave backhauling that supports fiber-like capacity with millimeter-wave communications. However, higher carrier frequencies are subject to weather disturbances like rain that may substantially degrade the network throughput. To mitigate this effect, we develop a fast and accurate rain detection algorithm that triggers a network-layer strategy, i.e., rerouting. The results show that with small detection error the network throughput increases while posing small overhead on the network. The rain impact can be alleviated by centralized rerouting under the software defined networking paradigm. However, careless reconfiguration may impose inconsistency that leads to a significant temporary congestion and limits the gain of rerouting. We propose a consistency-aware rerouting framework by considering the cost of reconfiguration. At each time, the centralized controller may either take a rerouting or no-rerouting decision in order to minimize the total data loss. We use a predictive control algorithm to provide such an online sequence of decisions. Compared to the regular rerouting, our proposed approach reduces the throughput loss and substantially decreases the number of reconfigurations. In the thesis we also study which backhaul option is the best from a techno-economic perspective. We develop a comprehensive framework to calculate the total cost of ownership of the backhaul segment and analyze the profitability in terms of cash flow and net present value. The results highlight the importance of selecting proper backhaul solution to increase profitability. / <p>QC 20170308</p>
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-202940 |
| Date | January 2017 |
| Creators | Yaghoubi, Forough |
| Publisher | KTH, Optical Network Laboratory (ON Lab) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Licentiate thesis, comprehensive summary, info:eu-repo/semantics/masterThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | TRITA-ICT ; 2017:06 |
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