| Summary: | The number of wireless connected devices is increasing rapidly, owing to the increasing applications of Internet of Things (IoT) devices. To address the coverage and capacity demand in the future, the fifth generation (5G) network will have heterogeneous architecture with densely deployed small cells and relay nodes for cooperative communication. Since dense deployment of base stations and relay nodes incur high energy consumption, renewable energy harvesting is a promising technique of reducing non-renewable energy consumption. Meanwhile, with increasing demand of IoT applications, self-sustaining battery life is direly needed in low power sensor-like devices. Since installation of bulky renewable energy harvesting infrastructure is not feasible in such miniature sensor-like devices, wireless energy harvesting is another promising technique that enables self-sustaining battery life of such devices. In this thesis, we address the challenges of resource allocation in cooperative and heterogeneous wireless communication networks with renewable and wireless energy harvesting.
First, we consider relay-based and user-based cooperation in uplink wireless-powered communication (WPC) to mitigate the ``doubly near-far" problem. We propose algorithms to jointly optimize resource allocation for downlink energy harvesting and uplink information transmission in uplink WPC network with relay-based and user-based cooperation. Our algorithms improve throughput performance of user equipments that are far from access point. Next, we address new challenges of interference management in heterogeneous networks (HetNets) when downlink simultaneous information and power transfer (SWIPT) is enabled in small cells. We jointly maximize energy harvesting rate and throughput of small cell users while keeping interference within tolerable level. In time-switching approach of SWIPT, we demonstrate significant improvement in the energy harvesting rate by enabling flexible interference tolerance in macrocell users. Finally, we address the conflict between maximization of throughput and minimization of power cost in HetNets with renewable energy harvesting. We propose different online and offline algorithms to determine dynamic base station activation policy jointly with downlink resource allocation to optimize the trade-off between throughput performance and the associated power cost. Our algorithms demonstrate significant increase in throughput and decrease in non-renewable power consumption when compared to the baseline schemes. Performances of the proposed algorithms are analyzed through numerical simulations. === Applied Science, Faculty of === Electrical and Computer Engineering, Department of === Graduate
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