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Biason, Alessandro (2018) Stochastic Optimization of Energy Harvesting Wireless Communication Networks. [Ph.D. thesis]

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Abstract (english)

Energy harvesting from environmental energy sources (e.g., sunlight) or from man-made
sources (e.g., RF energy) has been a game-changing paradigm, which enabled the possibility
of making the devices in the Internet of Things or wireless sensor networks operate
autonomously and with high performance for years or even decades without human
intervention. However, an energy harvesting system must be correctly designed to achieve
such a goal and therefore the energy management problem has arisen and become a critical
aspect to consider in modern wireless networks. In particular, in addition to the hardware
(e.g., in terms of circuitry design) and application point of views (e.g., sensor deployment),
also the communication protocol perspective must be explicitly taken into account; indeed,
the use of the wireless communication interface may play a dominant role in the energy
consumption of the devices, and thus must be correctly designed and optimized. This
analysis represents the focus of this thesis.
Energy harvesting for wireless system has been a very active research topic in the past
decade. However, there are still many aspects that have been neglected or not completely
analyzed in the literature so far. Our goal is to address and solve some of these new
problems using a common stochastic optimization setup based on dynamic programming.
In particular, we formulate both the centralized and decentralized optimization problems
in an energy harvesting network with multiple devices, and discuss the interrelations
between these two schemes; we study the combination of environmental energy harvesting
and wireless energy transfer to improve the transmission rate of the network and achieve a
balanced situation; we investigate the long-term optimization problem in wireless powered
communication networks, in which the receiver supplies wireless energy to the terminal
nodes; we deal with the energy storage inefficiencies of the energy harvesting devices,
and show that traditional policies may be strongly suboptimal in this context; finally, we
investigate how it is possible to increase secrecy in a wireless link where a third malicious
party eavesdrops the information transmitted by an energy harvesting node.

Abstract (italian)

Energy harvesting from environmental energy sources (e.g., sunlight) or from man-made
sources (e.g., RF energy) has been a game-changing paradigm, which enabled the possibility
of making the devices in the Internet of Things or wireless sensor networks operate
autonomously and with high performance for years or even decades without human
intervention. However, an energy harvesting system must be correctly designed to achieve
such a goal and therefore the energy management problem has arisen and become a critical
aspect to consider in modern wireless networks. In particular, in addition to the hardware
(e.g., in terms of circuitry design) and application point of views (e.g., sensor deployment),
also the communication protocol perspective must be explicitly taken into account; indeed,
the use of the wireless communication interface may play a dominant role in the energy
consumption of the devices, and thus must be correctly designed and optimized. This
analysis represents the focus of this thesis.
Energy harvesting for wireless system has been a very active research topic in the past
decade. However, there are still many aspects that have been neglected or not completely
analyzed in the literature so far. Our goal is to address and solve some of these new
problems using a common stochastic optimization setup based on dynamic programming.
In particular, we formulate both the centralized and decentralized optimization problems
in an energy harvesting network with multiple devices, and discuss the interrelations
between these two schemes; we study the combination of environmental energy harvesting
and wireless energy transfer to improve the transmission rate of the network and achieve a
balanced situation; we investigate the long-term optimization problem in wireless powered
communication networks, in which the receiver supplies wireless energy to the terminal
nodes; we deal with the energy storage inefficiencies of the energy harvesting devices,
and show that traditional policies may be strongly suboptimal in this context; finally, we
investigate how it is possible to increase secrecy in a wireless link where a third malicious
party eavesdrops the information transmitted by an energy harvesting node.

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EPrint type:Ph.D. thesis
Tutor:Zorzi, Michele
Ph.D. course:Ciclo 30 > Corsi 30 > INGEGNERIA DELL'INFORMAZIONE
Data di deposito della tesi:13 January 2018
Anno di Pubblicazione:13 January 2018
Key Words:energy harvesting; energy transfer; energy management; network optimization; stochastic optimization; Markov Decision Processes
Settori scientifico-disciplinari MIUR:Area 09 - Ingegneria industriale e dell'informazione > ING-INF/03 Telecomunicazioni
Struttura di riferimento:Dipartimenti > Dipartimento di Ingegneria dell'Informazione
Codice ID:10751
Depositato il:09 Nov 2018 09:46
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