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PERFORMANCE ANALYSIS OF ENERGY HARVESTING IN WIRELESS NETWORKS USING STOCHASTIC GEOMETRY
Title
PERFORMANCE ANALYSIS OF ENERGY HARVESTING IN WIRELESS NETWORKS USING STOCHASTIC GEOMETRY
Creator
Chen, Ziru
Date
2017, 2017-07
Description
As the era of Internet of things (IoT) approaches, energy harvesting over radio frequency (RF) energy, has been proposed recently as a...
Show moreAs the era of Internet of things (IoT) approaches, energy harvesting over radio frequency (RF) energy, has been proposed recently as a promising solution to charge an ever increasing number of users for wireless communications. Exploiting the wireless signals in the surrounding environment coming from TV towers, Wi-Fi networks and cellular base stations (BSs), wireless devices such as wireless sensors scavenge ambient RF energy and operate self-sustainably without replacing or recharging their batteries. In this dissertation, the downlink performance of wireless networks with RF energy harvesting is investigated. We consider a large scale cellular network, where BSs and RF energy powered mobile users (MUs) are deployed as a homogeneous Poisson Point Process (HPPP) with different spatial densities. Downlink transmissions for multiple MUs associated with one BS are scheduled in a time division multiple access (TDMA) manner, which allows each MU to harvest the ambient RF energy from concurrent transmissions in other cells when it is not transmitting. Applying stochastic geometry, we develop an analytical model to investigate the energy harvesting performance of MUs and the throughput performance of the wireless network under different densities of BSs and MUs. The successful transmission probability of MUs, i.e., when an MU has charged enough energy for one transmission and the achieved signal to interference ratio is larger than a threshold, is derived. Based on the analysis, the conditions that MUs can be fully energy sustainable with RF charging are further quantified. Finally, the analytical results and the full sustainability conditions of the proposed network model have been verified by extensive simulations with Matlab.
M.S. in Electrical Engineering, July 2017
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Performance Analysis of Energy Harvesting- Non-Orthogonal Multiple Access IoT Network
Title
Performance Analysis of Energy Harvesting- Non-Orthogonal Multiple Access IoT Network
Creator
Ni, Zhou
Date
2019
Description
Internet of Things (IoT) systems in general consist of a lot of devices with massive connectivity. Those devices are usually constrained with...
Show moreInternet of Things (IoT) systems in general consist of a lot of devices with massive connectivity. Those devices are usually constrained with limited energy supply and can only operate at low power and low rate. One solution to limited energy is to use energy harvesting to provide sustainable energy. The set of technologies adopted in next-generation wireless communication systems, such as massive MIMO and Non-Orthogonal Multiple Access (NOMA), can provide solutions to increase the throughput of IoT systems. In this thesis, we investigate a cellular-based IoT system combined with energy harvesting and NOMA. We consider all base stations (BS) and IoT devices follow the Poisson Point Process (PPP) distribution in a given area. The unit time slot is divided into two phases, energy harvesting phase in downlink (DL) and data transmission phase in uplink (UL). That is, IoT devices will first harvest energy from all BS transmissions and then use the harvested energy to do the NOMA information transmission. We define an energy harvesting circle within which all IoT devices can harvest enough energy for NOMA transmission. The design objective is to maximize the total throughput in UL within the circle by varying the duration T of energy harvesting phase. In our work, we also consider the inter-cell interference in the throughput calculation. The analysis of Probability Mass Function (PMF) for IoT devices in the energy harvesting circle is also compared with simulation results. It is shown that the BS density needs to be carefully set so that the IoT devices in the energy harvesting circle receive relatively smaller interference and energy circles overlap only with small probability. Our simulations show that there exists an optimal T to achieve the maximum throughput. When the BSs are densely deployed consequently the total throughput will decrease because of the interference.
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