Energy aware management of 5G networks

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dc.contributor.author Liu, Chang
dc.date.accessioned 2016-04-18T15:53:13Z
dc.date.available 2016-04-18T15:53:13Z
dc.date.issued 2016-05-01
dc.identifier.uri http://hdl.handle.net/2097/32506
dc.description.abstract The number of wireless devices is predicted to skyrocket from about 5 billion in 2015 to 25 billion by 2020. Therefore, traffic volume demand is envisioned to explode in the very near future. The proposed fifth generation (5G) of mobile networks is expected to be a mixture of network components with different sizes, transmit powers, back-haul connections and radio access technologies. While there are many interesting problems within the 5G framework, we address the challenges of energy-related management in a heterogeneous 5G networks. Based on the 5G architecture, in this dissertation, we present some fundamental methodologies to analyze and improve the energy efficiency of 5G network components using mathematical tools from optimization, control theory and stochastic geometry. Specifically, the main contributions of this research include: • We design power-saving modes in small cells to maximize energy efficiency. We first derive performance metrics for heterogeneous cellular networks with sleep modes based on stochastic geometry. Then we quantify the energy efficiency and maximize it with quality-of-service constraint based on an analytical model. We also develop a simple sleep strategy to further improve the energy efficiency according to traffic conditions. • We conduct a techno-economic analysis of heterogeneous cellular networks powered by both on-grid electricity and renewable energy. We propose a scheme to minimize the electricity cost based on a real-time pricing model. • We provide a framework to uncover desirable system design parameters that offer the best gains in terms of ergodic capacity and average achievable throughput for device-to-device underlay cellular networks. We also suggest a two-phase scheme to optimize the ergodic capacity while minimizing the total power consumption. • We investigate the modeling and analysis of simultaneous information and energy transfer in Internet of things and evaluate both transmission outage probability and power outage probability. Then we try to balance the trade-off between the outage performances by careful design of the power splitting ratio. This research provides valuable insights related to the trade-offs between energy-conservation and system performance in 5G networks. Theoretical and simulation results help verify the performance of the proposed algorithms. en_US
dc.language.iso en_US en_US
dc.publisher Kansas State University en
dc.subject Electrical engineering en_US
dc.subject Energy efficiency
dc.subject 5G networks
dc.subject Stochastic geometry
dc.title Energy aware management of 5G networks en_US
dc.type Dissertation en_US
dc.description.degree Doctor of Philosophy en_US
dc.description.level Doctoral en_US
dc.description.department Department of Electrical and Computer Engineering en_US
dc.description.advisor Balasubramaniam Natarajan en_US
dc.date.published 2016 en_US
dc.date.graduationmonth May en_US


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