On the Efficiency of Intelligent Technologies for Next Generation Heterogeneous Networks
Date Issued
2015
Date
2015
Author(s)
Chen, Zanyu
Abstract
Today''s heterogeneous networks comprised of mostly macrocells and small cells will not be able to meet the upcoming traffic demands. Indeed, it is forecasted that at least a 100$ imes$ network capacity increase will be required to meet the traffic demands in 2020. As a result, vendors and operators are now looking at using every tool at hand to improve network capacity. In this epic campaign, three paradigms are noteworthy, i.e., network densification, the use of of higher frequency bands, and spectral efficiency enhancement technique. In this dissertation, we focus on the issue on network densification, which contains many small cells in the network such as femtocells, picocells and relay nodes. The dissertation can be divided into two parts: the first one is about relay node selection in cooperative communication, and the other is about interference management in heterogeneous networks. We proposed an fully decentralized algorithm call ""Decentralized Learning based Relay Assignment"" algorithm to solve the relay assignment problem in cooperative communication. On the other hand, in the topic about interference management, we propose an approach called ""Multi-Tone Subframes"" to mitigate the interference in heterogeneous networks.
Subjects
Heterogeneous Network
Cooperative Communication
Relay Selection
Interference Management
Almost Blank Subframe
Primal-Dual Interior Point Method
Type
thesis
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