1,720,980 research outputs found
Stochastic Optimization of Energy Harvesting Wireless Communication Networks
Get PDFEnergy 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
Multicast via point to multipoint transmissions in directional 5G mmWave communications
No full textmmWave communications have been shown to be feasible in future networks. Thanks to their very large available bandwidth, they have captured the interest of academia and industry alike as a key enabler to solve the spectrum crunch problem. Nevertheless, the new characteristics of mmWaves call for a paradigm change in wireless protocols and many challenges still remain unaddressed. Among these, an important feature to analyze is the use of multicast via point-to-multipoint communications to further increase spectrum efficiency, improve reliability and reduce the access point load. The combination of multicast and mmWaves presents many issues, starting with how the beams should be shaped to communicate to the users. This article will cover some important aspects at the intersection of the two technologies and, in particular, it will show that restricting the wireless links to be unicast only may be strongly suboptimal
Joint Online Transmission and Energy Transfer Policies for Energy Harvesting Devices with Finite Batteries
No full textOne of the main concerns in traditional Wireless Sensor Networks (WSNs) is energy efficiency. In this work, we analyze two techniques that can extend network lifetime. The first is Ambient Energy Harvesting (EH), i.e., the capability of the devices to gather energy from the environment, whereas the second is Wireless Energy Transfer (ET), that can be used to exchange energy among devices. We study the combination of these techniques, showing that they can be used jointly to improve the system performance. In particular we focus on the online optimization process, solving a dynamic programming problem with a Markov approach. We derive the performance upper bounds that can be achieved with and without ET. Moreover, we show that if one of the two devices receives much more energy than the other, then it is possible to use ET to increase the system performance. Finally, we present simulation results based on realistic energy arrivals in indoor and outdoor environments, discussing how ET can be used in such environments
Multicast Transmissions in Directional mmWave Communications
No full textMulticast transmissions have been widely analyzed in traditional networks as a way to improve spectrum efficiency when multiple users are interested in the same data. However, their application to mmWave communications has been studied only marginally so far. The goal of this paper is to partially fill this gap by investigating optimal and suboptimal multicast schemes for mmWave communications with directional beams. In particular, we propose a Markov setup to model the retransmission status of the unsuccessfully transmitted packets and, because of the computational complexity of the optimal solution, we introduce a suboptimal hierarchical optimization procedure, which is much easier to derive. Finally, we numerically show that restricting the link to unicast beams is suboptimal, especially when many packets have to be transmitted
Joint Transmission and Energy Transfer Policies for Energy Harvesting Devices With Finite Batteries
No full textOne of the main concerns in traditional wireless sensor networks (WSNs) is energy efficiency. In this work, we analyze two techniques that can extend network lifetime. The first is ambient energy harvesting (EH), i.e., the capability of the devices to gather energy from the environment, whereas the second is wireless energy transfer (ET), that can be used to exchange energy among devices. We study the combination of these techniques, showing that they can be used jointly to improve the system performance. We consider a transmitter-receiver pair, showing how the ET improvement depends upon the statistics of the energy arrivals and the energy consumption of the devices. With the aim of maximizing a reward function, e.g., the average transmission rate, we find performance upper bounds with and without ET, define both online and offline optimization problems, and present results based on realistic energy arrivals in indoor and outdoor environments. We show that ET can significantly improve the system performance even when a sizable fraction of the transmitted energy is wasted and that, in some scenarios, the online approach can obtain close to optimal performance
Achievable Secrecy Rates of an Energy Harvesting Device
Get PDFThe secrecy rate represents the amount of information per unit time that can be securely sent on a communication link. In this work, we investigate the achievable secrecy rates in an energy harvesting communication system composed of a transmitter, a receiver and a malicious eavesdropper. In particular, because of the energy constraints and the channel conditions, it is important to understand when a device should transmit and to optimize how much power should be used to improve security. Both full knowledge and partial knowledge of the channel are considered under a Nakagami fading scenario. We show that high secrecy rates can be obtained only with power and coding rate adaptation. Moreover, we highlight the importance of optimally dividing the transmission power in the frequency domain, and note that the optimal scheme provides high gains in secrecy rate over the uniform power splitting case. Analytically, we explain how to find the optimal policy and prove some of its properties. In our numerical evaluation, we discuss how the maximum achievable secrecy rate changes according to the various system parameters. Furthermore, we discuss the effects of a finite battery on the system performance and note that, in order to achieve high secrecy rates, it is not necessary to use very large batteries
On the effects of battery imperfections in an energy harvesting device
No full textEnergy Harvesting allows the devices in a Wireless Sensor Network to recharge their batteries through environmental energy sources. While in the literature the main focus is on devices with ideal batteries, in reality several inefficiencies have to be considered to correctly design the operating regimes of an Energy Harvesting Device (EHD). In this work we describe how the throughput optimization problem changes under real battery constraints in an EHD. In particular, we consider imperfect knowledge of the state of charge of the battery and storage inefficiencies, i.e., part of the harvested energy is wasted in the battery recharging process. We formulate the problem as a Markov Decision Process, basing our model on some realistic observations about transmission, consumption and harvesting power. We find the performance upper bound with a real battery and numerically discuss the novelty introduced by the real battery effects. We show that using the old policies obtained without considering the real battery effects is strongly suboptimal and may even result in zero throughput
Long-Term throughput optimization in WPCN with battery-powered devices
No full textWireless powered communication networks are becoming an effective solution for improving self sustainability of mobile devices. In this context, a hybrid access point transfers energy to a group of nodes, which use the harvested energy to perform computation or transmission tasks. While the availability of the wireless energy transfer mechanism opens up new frontiers, it also requires an appropriate choice of the network parameters (e.g., transmission powers, transmission duration, amount of transferred energy, etc.) in order to achieve high performance. In this work, we study the throughput optimization problem in a system composed of an access point which recharges the batteries of two devices at different distances. In the literature, the main focus so far has been on slot-oriented optimization, in which all the harvested energy is used in the same slot in which it is harvested. However, this approach may be strongly suboptimal because it does not exploit the possibility to store the energy and use it at a later time. Thus, instead of considering the slot-oriented case, we address the long-term maximization. This assumption greatly increases the optimization complexity, as it requires to consider, e.g., the channel state realizations, its statistics and the batteries time evolution. Our objective is to find the best scheduling scheme, both for the energy transferred by the access point and for the data sent by the two nodes. We discuss how to perform the optimization and show that the slot-oriented policies proposed so far are strongly sub-optimal in the long-term case. Our scenario can be considered as a first step toward the study of more complex and distributed schemes in wireless energy-transfer scenarios in the presence of battery-powered nodes
Transmission policies in wireless powered communication networks with energy cooperation
No full textEnergy Harvesting (EH) has been recognized as one of the most appealing solutions for extending the devices lifetime in wireless sensor networks. Despite the vast literature available about ambient EH, in the last few years Energy Transfer (ET) has been introduced as a new and promising paradigm. With ET, it becomes possible to actively control the energy source and thus improve the network performance. We focus on two particular applications of ET which have been studied separately in the literature so far: Energy Cooperation (EC) and Wireless Powered Communication Networks (WPCNs). In the first case, energy is wirelessly shared among terminal devices according to their requirements and energy availability, whereas, in a WPCN, energy can be purposely transferred from an energy-rich network node (e.g., an access point) to terminal devices. We solve a weighted throughput optimization problem for the two-node case using optimal as well as sub-optimal schemes. Numerically, we explain the role of EC in improving the system performance
Energy harvesting communication system with SOC-dependent energy storage losses
No full textThe popularity of Energy Harvesting Devices (EHDs) has grown in the past few years, thanks to their capability of prolonging the network lifetime. In reality, EHDs are affected by several inefficiencies, e.g., energy leakage, battery degradation or storage losses. In this work we consider an energy harvesting transmitter with storage inefficiencies. In particular, we assume that when new energy has to be stored in the battery, part of this is wasted and the losses depend upon the current state of charge of the device. This is a practical realistic assumption, e.g., for a capacitor, that changes the structure of the optimal transmission policy. We analyze the throughput maximization problem with a dynamic programming approach and prove that, given the battery status and the channel gain, the optimal transmission policy is deterministic. We derive numerical results for the energy losses in a capacitor and show the presence of a loop effect that degrades the system performance if the optimal policy is not considered
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