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Green scheduling and resource allocation in clustered dense small cells.

Yang, Ting (2018) Green scheduling and resource allocation in clustered dense small cells. Doctoral thesis, University of Surrey.

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Future communication networks promise to provide ubiquitous high-speed services for numerous users, as such, it is envisioned that one of the key aspects of the next generation of communication network is the deployment of different types of access points, e.g. small cells (SCs), on a massive scale. Meanwhile, energy efficiency (EE) has become an important feature for designing the next generation of communication networks and offering good user experience to all users while incurring low operational cost to the operators. In this context, this thesis focuses on the design of a novel green scheduling framework for improving both the EE and user fairness in the underlay HetNet scenario. Focusing on the user/subcarrier allocation, we design an EE-based allocation boundary which dynamically categorises users into inner area and cell-edge users. Our dynamic resource allocation boundary is updated at every scheduling interval such that it can capture the time-varying characteristics of the mobile networks, contrary to the fixed boundaries used in long-term planning schemes (e.g. fractional frequency reuse). This dynamic allocation boundary is used to design a green scheduling scheme and can improve the EE of an underlay HetNet system by up to 70% as compared to existing schemes. Focusing on the power allocation algorithm, a low-complexity energy-efficient power allocation algorithm is designed to coordinate the macro and underlay SCs and fully exploit the transmit power reduction capability of SCs. By applying a symmetric user grouping method, it is shown that the original non-convex EE optimisation problem can be transformed into a pseudo-convex problem, where the optimal power allocation can be obtained for a given user/subcarrier allocation. This energy-efficient power allocation algorithm is further incorporated with the dynamic allocation boundary which improves the EE (up to 70%) and user fairness (up to 50%) compared to existing algorithms in the underlay HetNet.

Item Type: Thesis (Doctoral)
Divisions : Theses
Authors :
Yang, Ting
Date : 31 July 2018
Funders : Self-funded
Contributors :
Depositing User : Ting Yang
Date Deposited : 06 Aug 2018 08:12
Last Modified : 09 Nov 2018 16:39

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