197 research outputs found
Power Beacon’s deployment optimization for wirelessly powering massive Internet of Things networks
Abstract. The fifth-generation (5G) and beyond wireless cellular networks promise the native support to, among other use cases, the so-called Internet of Things (IoT). Different from human-based cellular services, IoT networks implement a novel vision where ordinary machines possess the ability to autonomously sense, actuate, compute, and communicate throughout the Internet. However, as the number of connected devices grows larger, an urgent demand for energy-efficient communication technologies arises. A key challenge related to IoT devices is that their very small form factor allows them to carry just a tiny battery that might not be even possible to replace due to installation conditions, or too costly in terms of maintenance because of the massiveness of the network. This issue limits the lifetime of the network and compromises its reliability.
Wireless energy transfer (WET) has emerged as a potential candidate to replenish sensors’ batteries or to sustain the operation of battery-free devices, as it provides a controllable source of energy over-the-air. Therefore, WET eliminates the need for regular maintenance, allows sensors’ form factor reduction, and reduces the battery disposal that contributes to the environment pollution.
In this thesis, we review some WET-enabled scenarios and state-of-the-art techniques for implementing WET in IoT networks. In particular, we focus our attention on the deployment optimization of the so-called power beacons (PBs), which are the energy transmitters for charging a massive IoT deployment subject to a network-wide probabilistic energy outage constraint. We assume that IoT sensors’ positions are unknown at the PBs, and hence we maximize the average incident power on the worst network location. We propose a linear-time complexity algorithm for optimizing the PBs’ positions that outperforms benchmark methods in terms of minimum average incident power and computation time. Then, we also present some insights on the maximum coverage area under certain propagation conditions
Sustainable Radio Frequency Wireless Energy Transfer for Massive Internet of Things
Reliable energy supply remains a crucial challenge in the Internet of Things
(IoT). Although relying on batteries is cost-effective for a few devices, it is
neither a scalable nor a sustainable charging solution as the network grows
massive. Besides, current energy-saving technologies alone cannot cope, for
instance, with the vision of zero-energy devices and the deploy-and-forget
paradigm which can unlock a myriad of new use cases. In this context,
sustainable radio frequency wireless energy transfer emerges as an attractive
solution for efficiently charging the next generation of ultra low power IoT
devices. Herein, we highlight that sustainable charging is broader than
conventional green charging, as it focuses on balancing economy prosperity and
social equity in addition to environmental health. Moreover, we overview the
key enablers for realizing this vision and associated challenges. We discuss
the economic implications of powering energy transmitters with ambient energy
sources, and reveal insights on their optimal deployment. We highlight relevant
research challenges and candidate solutions.Comment: 12 pages, 6 figures, 2 tables, submitted to IEEE Internet of Things
Journa
Massive Wireless Energy Transfer with Multiple Power Beacons for very large Internet of Things
The Internet of Things (IoT) comprises an increasing number of low-power and
low-cost devices that autonomously interact with the surrounding environment.
As a consequence of their popularity, future IoT deployments will be massive,
which demands energy-efficient systems to extend their lifetime and improve the
user experience. Radio frequency wireless energy transfer has the potential of
powering massive IoT networks, thus eliminating the need for frequent battery
replacement by using the so-called power beacons (PBs). In this paper, we
provide a framework for minimizing the sum transmit power of the PBs using
devices' positions information and their current battery state. Our strategy
aims to reduce the PBs' power consumption and to mitigate the possible impact
of the electromagnetic radiation on human health. We also present analytical
insights for the case of very distant clusters and evaluate their
applicability. Numerical results show that our proposed framework reduces the
outage probability as the number of PBs and/or the energy demands increase.Comment: 7 pages, 6 figures, Submitted to "The International Workshop on Very
Large Internet of Things (2021)
RIS-Aided Cell-Free Massive MIMO Systems for 6G: Fundamentals, System Design, and Applications
An introduction of intelligent interconnectivity for people and things has
posed higher demands and more challenges for sixth-generation (6G) networks,
such as high spectral efficiency and energy efficiency, ultra-low latency, and
ultra-high reliability. Cell-free (CF) massive multiple-input multiple-output
(mMIMO) and reconfigurable intelligent surface (RIS), also called intelligent
reflecting surface (IRS), are two promising technologies for coping with these
unprecedented demands. Given their distinct capabilities, integrating the two
technologies to further enhance wireless network performances has received
great research and development attention. In this paper, we provide a
comprehensive survey of research on RIS-aided CF mMIMO wireless communication
systems. We first introduce system models focusing on system architecture and
application scenarios, channel models, and communication protocols.
Subsequently, we summarize the relevant studies on system operation and
resource allocation, providing in-depth analyses and discussions. Following
this, we present practical challenges faced by RIS-aided CF mMIMO systems,
particularly those introduced by RIS, such as hardware impairments and
electromagnetic interference. We summarize corresponding analyses and solutions
to further facilitate the implementation of RIS-aided CF mMIMO systems.
Furthermore, we explore an interplay between RIS-aided CF mMIMO and other
emerging 6G technologies, such as next-generation multiple-access (NGMA),
simultaneous wireless information and power transfer (SWIPT), and millimeter
wave (mmWave). Finally, we outline several research directions for future
RIS-aided CF mMIMO systems.Comment: 30 pages, 15 figure
Extending Wireless Powered Communication Networks for Future Internet of Things
Energy limitation has always been a major concern for long-term operation of wireless networks. With today's exponential growth of wireless technologies and the rapid movement towards the so-called Internet of Things (IoT), the need for a reliable energy supply is more tangible than ever. Recently, energy harvesting has gained considerable attention in research communities as a sustainable solution for prolonging the lifetime of wireless networks. Beside conventional energy harvesting sources such as solar, wind, vibration, etc. harvesting energy from radio frequency (RF) signals has drawn significant research interest in recent years as a promising way to overcome the energy bottleneck. Lately, the integration of RF energy transfer with wireless communication networks has led to the emergence of an interesting research area, namely, wireless powered communication network (WPCN), where network users are powered by a hybrid access point (HAP) which transfers wireless energy to the users in addition to serving the functionalities of a conventional access point. The primary aim of this thesis is to extend the baseline model of WPCN to a dual-hop WPCN (DH-WPCN) in which a number of energy-limited relays are in charge of assisting the information exchange between energy-stable users and the HAP. Unlike most of the existing research in this area which has merely focused on designing methods and protocols for uplink communication, we study both uplink and downlink information transmission in the DH-WPCN. We investigate sum-throughput maximization problems in both directions and propose algorithms for optimizing the values of the related parameters. We also tackle the doubly near-far problem which occurs due to unequal distance of the relays from the HAP by proposing a fairness enhancement algorithm which guarantees throughput fairness among all users
- …