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Towards Cognitive IoT Networks pp 125–150Cite as

Internet of Energy Harvesting Cognitive Radios

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Part of the book series: Internet of Things ((ITTCC))

Abstract

The Internet of Things (IoT) offers enhanced connectivity so that any system, being, or process can be reached from anywhere at any time by perpetual surveillance, which results in very large and complex data sets, i.e., Big Data. Despite numerous advantages, IoT technology comes with some unavoidable drawbacks. Considering the number of devices to be added to the current electromagnetic spectrum, it is a fact that wireless communications will severely suffer and eventually become inoperable. Furthermore, as wireless devices are equipped with limited capacity batteries, frequent replenishments and/or maintenance will be needed. However, this is neither practical nor achievable due to the excessive number of devices envisioned by the IoT paradigm. Here, the unification of Energy Harvesting (EH) and Cognitive Radio (CR) stands highly promising to alleviate the current drawbacks, enabling more efficient data generation, acquisition, and analysis. This chapter outlines a new vision, namely Internet of Energy Harvesting Cognitive Radios (IoEH-CRs), to take the IoT-enabled Big Data paradigm a step further. It discusses the basics of the EH-assisted spectrum-aware communications and their implications for the IoT, as well as the challenges posed by the unification of these techniques. An operational framework together with node and network architectures is also presented.

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Abbreviations

ACC:

Autonomous connection circuit

APs:

Access points

CR:

Cognitive radio

CTs:

Current transformers

EFEG:

Electric field energy harvesting

EH:

Energy harvesting

EH-CRs:

Energy harvesting cognitive

EM:

Electromagnetic

FCC:

Federal communications

HANs:

Home area networks

IoEH-CRs:

Internet of energy harvesting cognitive radios

IoT:

Internet of things

IPs:

Internet protocols

ISM:

Industrial, scientific, and medical

ITU:

International telecommunication union

KEC:

Kinetic energy conversion

MEEG:

Mechanical-to-electrical energy generators

MFEG:

Magnetic field energy harvesting

MPTT:

Maximum power point tracking

NANs:

Neighborhood area networks

PPDR:

Public protection and disaster relief

PUs:

Primary users

PV:

Photovoltaic

QoS:

Quality of service

RF:

Radio frequency

SCs:

Smart cities

SGs:

Smart grids

TEG:

Thermoelectric generation

WANs:

Wide area networks

Wi-Fi:

Wireless fidelity

WSNs:

Wireless sensor networks

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Author information

Authors and Affiliations

  1. Next-Generation and Wireless Communications Laboratory (NWCL), Department of Electrical and Electronics Engineering, Koc University, Istanbul, 34450, Turkey

    O. Cetinkaya, M. Ozger & O. B. Akan

  2. Internet of Everything (IoE) Group, Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, CB3 0FA, UK

    O. B. Akan

Authors
  1. O. Cetinkaya
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  2. M. Ozger
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  3. O. B. Akan
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Corresponding author

Correspondence to O. Cetinkaya .

Editor information

Editors and Affiliations

  1. North South University, Dhaka, Bangladesh

    Mohammad Abdul Matin

Glossary

Big Data

is a term that describes huge amount of structured, semi-structured and unstructured data.

Energy Harvesting (EH)

is a phenomenon which refers exploiting a stray source or converting energy from one form to another.

Cognitive Radio (CR)

is a technology that enables accessing the spectrum opportunistically via sensing the spectrum.

Energy Harvesting Cognitive Radios (EH-CRs)

are the wireless devices with energy harvesting and cognitive radio capability.

Internet of Energy Harvesting Cognitive Radios (IoEH-CRs)

It is the Internet of Things, in which the things have energy harvesting and cognitive radio capability.

Wireless Sensor Networks (WSNs)

are the autonomous sensors that monitor a parameter of interest such as temperature, humidity, presence etc. and accordingly convey the gathered data through the network to an authority.

Industrial, Scientific, and Medical (ISM) radio bands

are the vacant bands that are reserved for industrial, scientific and medical purposes in international order.

Primary Users

are the licensed users and can access to their spectrum bands without any limitations.

Spectrum Sensing

is one of cognitive cycle operations that reveals information about the spectrum usage.

Spectrum Decision

is the determination of operating spectrum band after sensing the spectrum bands.

Spectrum Handoff

is the cognitive cycle operation that ceases the transmission of cognitive radio when PU starts to communicate on the channel CR operates.

Photo-voltaic (PV) Effect

is a chemical phenomenon, in which PV cells emit electrons when they exposed to light. This effect yields in generating electrical energy.

Smart City (SC)

is a vision to enable information and communication technologies to observe the city elements to provide better management of the city resources/services.

Smart Grid (SG)

provides two-way communication between the utilities and homes to provide better electric services.

Maximum Power Point Tracking (MPPT)

is a method that maximizes power extraction from (mostly) environmental sources under all conditions.

Kinetic Energy Conversion (KEC)

is a process, which is simply based on converting movement resultant energy into utilizable electrical power.

Mechanical-to-Electrical Generators (MEEG)

are devices, which contribute KEC process by taking advantage of vibrations, pressure variations and stress-strains.

Thermo-electric Generation (TEG)

is a process of converting temperature difference resultant energy into utilizable electrical power.

Autonomous Connection Circuit (ACC)

operates as a switch between harvester and nodal circuitry in a EH sensor node to efficiently manage the harvested energy.

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Cetinkaya, O., Ozger, M., Akan, O.B. (2020). Internet of Energy Harvesting Cognitive Radios. In: Matin, M. (eds) Towards Cognitive IoT Networks. Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-030-42573-9_9

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  • DOI: https://doi.org/10.1007/978-3-030-42573-9_9

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  • Online ISBN: 978-3-030-42573-9

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