Next-Generation IoT Devices: Sustainable Eco-Friendly Manufacturing, Energy Harvesting, and Wireless Connectivity

Abstract

This invited paper presents potential solutions for tackling some of the main underlying challenges toward developing sustainable Internet-of-things (IoT) devices with a focus on eco-friendly manufacturing, sustainable powering, and wireless connectivity for next-generation IoT devices. The diverse applications of IoT systems, such as smart cities, wearable devices, self-driving cars, and industrial automation, are driving up the number of IoT systems at an unprecedented rate. In recent years, the rapidly-increasing number of IoT devices and the diverse application-specific system requirements have resulted in a paradigm shift in manufacturing processes, powering methods, and wireless connectivity solutions. The traditional cloud-centering IoT systems are moving toward distributed intelligence schemes that impose strict requirements on IoT devices, e.g., operating range, latency, and reliability. In this article, we provide an overview of hardware-related research trends and application use cases of emerging IoT systems and highlight the enabling technologies of next-generation IoT. We review eco-friendly manufacturing for next-generation IoT devices, present alternative biodegradable and eco-friendly options to replace existing materials, and discuss sustainable powering IoT devices by exploiting energy harvesting and wireless power transfer. Finally, we present (ultra-)low-power wireless connectivity solutions that meet the stringent energy efficiency and data rate requirements of future IoT systems that are compatible with a batteryless operation.

Full text

Received 4 October 2022; revised 21 November 2022; accepted 8 December 2022.
Date of current version 6 January 2023.
Digital Object Identifier 10.1109/JMW.2022.3228683
Next-Generation IoT Devices: Sustainable
Eco-Friendly Manufacturing, Energy
Harvesting, and Wireless Connectivity
HAMED RAHMANI 1(Member, IEEE), DARSHAN SHETTY 2(Student Member, IEEE),
MAHMOUD WAGIH 3(Member, IEEE), YASAMAN GHASEMPOUR 4(Member, IEEE),
VALENTINA PALAZZI 5(Member, IEEE), NUNO B. CARVALHO 6,7 (Fellow, IEEE),
RICARDO CORREIA6(Member, IEEE), ALESSANDRA COSTANZO 8(Fellow, IEEE),
DIEFF VITAL 9(Member, IEEE), FEDERICO ALIMENTI 5(Senior Member, IEEE), JEFF KETTLE 3,
DIEGO MASOTTI 8(Senior Member, IEEE), PAOLO MEZZANOTTE 5(Member, IEEE),
LUCA ROSELLI 5(Fellow, IEEE), AND JASMIN GROSINGER 10 (Senior Member, IEEE)
(Invited Paper)
1IBM T. J. Watson Research Center, Yorktown Heights, NY 10598 USA
2Infineon Technologies Austria AG, 8020 Graz, Austria
3James Watt School of Engineering, University of Glasgow, G12 8QQ Glasgow, U.K.
4Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ 08540 USA
5Department of Engineering, University of Perugia, 06125 Perugia, Italy
6Departamento de Eletrónica, Telecomunicações e Informática, Universidade de Aveiro, 3800 Aveiro, Portugal
7Instituto de Telecomunicações, 3800 Aveiro, Portugal
8DEI “Guglielmo Marconi”, University of Bologna, 40126 Bologna, Italy
9Department of Electrical and Computer Engineering, University of Illinois Chicago, Chicago, IL 60607 USA
10Institute of Microwave and Photonic Engineering, Graz University of Technology, 8010 Graz, Austria
CORRESPONDING AUTHOR: Jasmin Grosinger (e-mail: jasmin.grosinger@tugraz.at).
The work of Valentina Palazzi, Paolo Mezzanotte, and Luca Roselli was supported by the Italian Ministry of University and Research (MUR) through the PRIN
Project “Development and promotion of the Levulinic acid and Carboxylate platforms by the formulation of novel and advanced PHA-based biomaterials and their
exploitation for 3D printed green-electronics applications” under Grant 2017FWC3WC 003.
This work did not involve human subjects or animals in its research.
ABSTRACT This invited paper presents potential solutions for tackling some of the main underlying
challenges toward developing sustainable Internet-of-things (IoT) devices with a focus on eco-friendly
manufacturing, sustainable powering, and wireless connectivity for next-generation IoT devices. The di-
verse applications of IoT systems, such as smart cities, wearable devices, self-driving cars, and industrial
automation, are driving up the number of IoT systems at an unprecedented rate. In recent years, the
rapidly-increasing number of IoT devices and the diverse application-specific system requirements have
resulted in a paradigm shift in manufacturing processes, powering methods, and wireless connectivity
solutions. The traditional cloud-centering IoT systems are moving toward distributed intelligence schemes
that impose strict requirements on IoT devices, e.g., operating range, latency, and reliability. In this article, we
provide an overview of hardware-related research trends and application use cases of emerging IoT systems
and highlight the enabling technologies of next-generation IoT. We review eco-friendly manufacturing for
next-generation IoT devices, present alternative biodegradable and eco-friendly options to replace existing
materials, and discuss sustainable powering IoT devices by exploiting energy harvesting and wireless power
transfer. Finally, we present (ultra-)low-power wireless connectivity solutions that meet the stringent energy
efficiency and data rate requirements of future IoT systems that are compatible with a batteryless operation.
INDEX TERMS Antennas, backscattering, biodegradable, CMOS, energy harvesting, green substrates,
harmonic transponders, MTT 70th Anniversary Special Issue, recyclable electronics, rectifier, RFID, system-
on-chip, sustainable IoT, wireless power transmission.
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
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I. INTRODUCTION
The evolution of “Internet-of-Things” has opened limitless
potential solutions to enable the world around us to function
more intelligently and efficiently. A widespread network of
devices with sensing, processing, and communication capa-
bilities is a powerful tool to revolutionize every aspect of
our lives. An excellent testament to this statement is the
emergence of IoT devices in various applications such as
smart cities, intelligent agriculture, enhanced robotics, man-
ufacturing, wearables, implants, and health monitoring sys-
tems. [1], [2], [3]. The use cases for some of these appli-
cations and their projected global economic value by 2035
are demonstrated in Fig. 1. These emerging applications im-
pose strict performance requirements on IoT devices that a
paradigm shift toward intelligent distributed systems could
only address. The traditional cloud-centering schemes are ex-
pected to be replaced by distributed innovative configurations
to meet future IoT technology’s diverse system require-
ments, e.g., latency, power consumption, and reliability. The
fast adoption of IoT technology in various applications has
yielded an explosive number of IoT devices, and the number
of connected objects is expected to surpass 43 billion by
2023 [1].
To ensure that IoT technology can sustainably grow to be
a part of the future connected world, we need to consider
the potential environmental, economic, and societal impacts
and challenges – to name a few – introduced by the massive
upscaling of IoT devices and address them in the early stages
of IoT ecosystem development. For example, raw materi-
als used for manufacturing, supplying energy to ubiquitous
IoT devices, and getting rid of the eco-toxicity of batteries
will be a prevalent part of this new IoT ecosystem. How-
ever, the emerging use cases impose demanding requirements,
e.g., operating range, latency, and reliability. In some cases,
the traditional design techniques and technologies are inade-
quate and cannot meet the required specifications. Thus, the
sustainable growth of IoT devices could be enabled by: 1
– Addressing environmental concerns by using eco-friendly
materials, reducing carbon footprints, and removing toxic
materials from the manufacturing processes. 2 – Exploiting
energy harvesting and wireless power transfer technologies to
get rid of the eco-toxicity of batteries at the IoT device side
or at least to reduce the cost of battery replacement. Further-
more, 3 – Enhancing or inventing new communication and
sensing methods by applying (ultra-)low-power or batteryless
communication technologies capable of meeting the stringent
design requirements.
This article discusses eco-friendly manufacturing, sustain-
able powering, and wireless connectivity for next-generation
IoT devices and presents unique design solutions for these
challenges. In particular, the invited paper presents IoT de-
sign solutions from MTT-S’s technical committee members of
TC-26 RFID, Wireless Sensors, and IoT Committee. Section
II reviews eco-friendly manufacturing for next-generation IoT
devices, presenting alternative biodegradable and eco-friendly
options to replace existing materials. Section III discusses sus-
tainable powering IoT devices by exploiting energy harvesting
and wireless power transfer. Section IV discusses low-power
wireless connectivity solutions that meet stringent energy ef-
ficiency and data rate requirements of future IoT systems
compatible with a batteryless operation. Section V concludes
the work.
II. ECO-FRIENDLY MANUFACTURING OF IoT DEVICES
The environmental footprint of pervasive IoT devices, includ-
ing flexible and large-area electronics, must be factored into
the early design stages of IoT networks. In this section, we
focus on the sustainability issues of current manufacturing
processes and highlight the new opportunities and research
trends on wireless devices implemented on green substrates.
A. SUSTAINABLE MANUFACTURING AND RECYCLING
IoT products based on conventional electronics could suffer
from similar sustainability issues, and unintended outcomes
will afflict consumer electronics [4], [5], including:
rHeavy reliance on Critical Rare Metals (CRMs) used in
most electronics components (e.g., batteries, energy har-
vesters, integrated circuits), some of which are depleting
and almost 100% dependent on imports.
rEmissions from the manufacturing process; the electron-
ics sector is identified as one of the top 8 sectors that
account for more than 50% of global carbon emissions,
with 77% coming from the supply chain [6].
rAt the End-of-Life (EoL), IoT devices are classified as
Waste Electrical and Electronic Equipment (WEEE) by
the EU’s Directive (2012/19/EU). The WEEE is a par-
ticularly pertinent problem and is the fastest growing
waste stream globally; approximately 50 million tonnes
of WEEE is produced, growing at 3–5% per year. Less
than 20% of generated WEEE is formally recycled in-
ternationally. Rapidly expanding global demand for IoT
products makes the current ‘take-make-waste’ model of
consumption unsustainable [7].
There is no mainstream circular economy approach for
electronics and, thus, IoT products. Encouraging the repair
and reuse of IoT products is the best method to encourage cir-
cular electronics and to improve the sustainability [8], but this
may not be enough in the short term as the use of IoT devices
rises. Fig. 2 highlights two complementary approaches to
manufacturing sustainable devices: (a)–(c) robust, recyclable,
and re-usable devices; and (d)–(g) bio-derived and biodegrad-
able electronics [9], potentially leading to zero-waste IoT but
often possessing lower performance.
Improving the durability of flexible and harsh-
environments electronics is essential for sustainability
improvement. Structural integrity can be preserved using
vacuum-formed organic polymer encapsulation of discrete
components, e.g., passives, RF and analog Integrated Circuits
(ICs), and antennas [10], to withstand cyclic bending and
washing. As in Fig. 2(a), such encapsulation is conformable
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FIGURE 1. Expansion of the mobile ecosystem to future applications of IoT devices and the projected global economy value by 2035 [1].
FIGURE 2. From reusable to disposable sustainable devices: (a) robust
encapsulation of flexible RF circuits [14]; (b) mechanically and
thermally-reliable passives replacing discrete parts [12]; (c) programmable
and modular flexible sensing platforms [15]; (d) cellulose nanofibril-based
RF passives [16]; (e) bioresorbable Mg antennas and diodes [17];
(f) ultra-thin bendable RFIC [18]; (g) biodegradable carbon antennas [19].
and does not significantly add to the thickness or weight of
a flexible circuit. Both the flexibility and power handling can
also be improved by replacing ceramic discrete components
with printable passives [11], [12], as demonstrated in a
50 GHz DC-blocking line using screen-printed capacitors,
seen in Fig. 2(b) [12].
Modular and re-configurable hardware is crucial in increas-
ing the lifespan of IoT nodes. For instance, the approach of
using a single device, a wearable antenna in Fig. 2(c), as a
platform for mounting multiple sensors and energy harvesters
(flexible solar cells) can be re-configured during the device
lifetime by adding new sensing interfaces. Moreover, design-
ers could extend the antenna’s role to act as a simultaneous
wireless power receiver [13], reducing the number of required
components while adding functionality.
Several biodegradable materials and components have
been proposed while moving to transient and disposable
devices. Wood-based cellulose nanofibril (CNF) substrates
have been used for RF passives and low-density digital logic
circuits [16]. GaAs diodes were also packaged in CNF,
demonstrating green RF energy harvesters [16]. Biodegrad-
able and bio-compatible, i.e., bioresorbable, devices leverag-
ing magnesium (Mg) find applications in wireless biomedical
sensing, where an all Mg-based rectennas was previously
demonstrated [17]. Antennas have also been realized using
poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PE-
DOT:PSS) [20], [21] and carbon black [19], both of which
are biodegradable conductors [5]. A broadband PEDOT:PSS
antenna was characterized up to 20 GHz showing a radia-
tion efficiency exceeding 80% [21]. Printing a PEDOT:PSS
antenna on textiles for off-body communication resulted in
a radiation efficiency of around 28% [20]. Fig. 2(g) shows
a carbon black S-band microstrip antenna printed directly
on textiles for wearable applications. The approach of print-
ing biodegradable conductive tracks on degradable substrates
is key to minimizing the PCB disposal waste arising from
commercial-grade FR4 substrates, adhesives, and the waste
generated during the photolithography process.
Nevertheless, we can only realize devices such as high-
density logic circuits or millimeter wave (mmWave) frontends
in complementary metal-oxide semiconductor (CMOS) or
monolithic microwave integrated circuit (MMIC) processes.
Therefore, rigid semiconductor die thinning is a common ap-
proach for realizing bendable and potentially biodegradable
ICs, while retaining most of the performance of conventional
ICs. Recently, a 120 GHz transmitter with an on-chip an-
tenna was fabricated in a standard SiGe BiCMOS process and
demonstrated high mechanical flexibility after being thinned
to 20 μm [18]. The reduction in the die’s thickness resulted
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RAHMANI ET AL.: NEXT-GENERATION IoT DEVICES: SUSTAINABLE ECO-FRIENDLY MANUFACTURING, ENERGY HARVESTING
in around 4 dB loss in the radiated power output but had a
minimal influence on the frequency stability. Fig. 2(g) shows
the bendable RFIC.
While biodegradable electronics offer exciting possibilities
to eliminate WEEE, most commercial and research efforts
of EoL have focused on minimizing WEEE by recycling.
Recycling of WEEE generally follows a sequential approach;
removable or bulky components are manually dismantled.
Afterward, the particle sizes are progressively reduced by
shredding, crushing, pulverizing, grinding, and (sometimes)
ball milling. After the pulverization step, different separators
are used to separate raw metal and non-metal materials [5].
This might create a particular challenge for sensing devices
attached to, e.g., food packaging. Such products would have
to be treated as WEEE rather than standard plastic waste.
The obsolesce of IoT devices is resulting in large electronic
waste. Consumers must take back their broken devices to
the original manufacturer for repairs. However, there have
been rising movements to remove monopolistic repair tac-
tics and restore the right of repair to consumers. These
movements seek repair-friendly policies and regulations to
enable consumers and third parties to repair and modify elec-
tronic devices. Hence, it will empower consumers to behave
more sustainably by reducing the WEEE, directly and indi-
rectly, [22]. For example, the EU introduced new rules in
2021, with similar initiatives already in force in the USA.
These challenges are not insurmountable but need deeper con-
siderations as researchers develop other products.
B. GREEN MATERIALS
Recurring low-environmental-impact materials and processes
are essential to prevent future risks of electronics pollution (e-
pollution) and to foster a granular distribution of autonomous
wireless devices. Substrates are most of the mass of electronic
printed circuit boards (PCBs). Therefore, replacing standard
highly polluting substrates (such as FR4 epoxy glass lami-
nates) with green materials helps to significantly reduce the
volume of toxic electronic waste (e-waste).
Green Materials include both recyclable (i.e., materials
that can still be reused at the EoL stage of electronics) and
biodegradable materials (i.e., materials that can be decom-
posed by living organisms and do not pose any environmental
risks). The most popular green materials are paper and bio-
plastics, such as polylactic acid (PLA). The electromagnetic
properties of common green substrates used for electronics are
shown in Table 1. They have unique mechanical and optical
properties, allowing innovative sensing solutions. However,
these materials are not specifically made for electronics and
radio-frequency components and can feature variable elec-
tromagnetic properties and high dielectric loss. Additionally,
they cannot withstand high temperatures (for instance, the
glass transition temperature of PLA is about 60 ◦C [23]),
which limits the processes and materials that we can use
to manufacture the circuits. Hence, research trends on eco-
friendly implementation of IoT devices focus on addressing
the shortcomings of the green substrates by innovative design
TAB L E 1. Electromagnetic Properties of Common Green Materials
FIGURE 3. Harmonic crack sensor: (a) schematic, (b) photo of the intact
sensor, and (c) photo of the cracked sensor. From [29].
and taking advantage of their unique properties to enable
novel low-power sensing and telemetry schemes. Here a few
examples of RF circuits and sensors based on paper and PLA
are reported, where green materials are used not only as di-
electric substrates but also as sensors.
Fig. 3 shows a wireless passive harmonic crack sensor
manufactured on a paper substrate. The transponder is based
on harmonic backscattering: the tag is interrogated with a
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TAB L E 2. Comparison With State-of-the-Art Passive Crack Sensors
sinusoidal signal with frequency f0and responds at the sec-
ond harmonic. The sensor consists of an open-circuited stub
placed in a shunt with the input port of a passive frequency
doubler. Two antennas, working at harmonic frequencies,
complete the circuit. The stub is a quarter-wave long at f0.
Therefore, the input signal is short-circuited when the tag is
intact, and no second harmonic is generated. On the other
hand, when the stub is torn off, the input signal reaches the
frequency doubler, and a second harmonic signal is generated
and backscattered. The reader detects this signal which plays
the role of an alarm. It is worth noting that, unlike traditional
radio backscattering, no coding is needed to separate the tag
response from the clutter reflections, allowing for a fully pas-
sive, simple, and long-range transponder. The metal traces
are manufactured by applying photo-lithography to an adhe-
sive copper laminate (alternatively, laser cutting can be used)
which is finally stuck to the substrate. Two lumped compo-
nents (a ceramic capacitor and a Schottky diode) are soldered
to the metal traces. In the reported study, with f0=2.45 GHz,
the authors observed a transmitted power of 25 dBm effective
isotropic radiated power (EIRP) and a receiver sensitivity of
−100 dBm, an operating range from 1 to 5 m. In this ex-
ample, the fragility of the paper is leveraged to manufacture
a disposable crack sensor. At the same time, a simple yet
effective tag architecture allows us to minimize the number
of surface-mount commercial components.
Table 2 compares the proposed crack sensing system with
other passive wireless crack sensors at the state of the art. As
can be seen, the proposed solution outperforms other passive
crack sensing solutions for its read range, and it represents a
competitive alternative green solution compared to the other
circuits manufactured on standard PCBs.
In [37], the porosity of paper is used to realize a humidity
sensor instead. The transducer is based on a series resonator,
with a variable capacitance consisting of a paper-aluminum
bimorph cantilever above a rigid metal plate. As the relative
humidity increases, the length of the paper layer increases to
that of the Al layer, thus determining the cantilever deflection.
FIGURE 4. Bimorph paper-aluminum cantilever photographs and
measured scattering parameters for two values of relative humidity (RH),
40% RH (left panels) and 80% RH (right panels): As the relative humidity
increases, the cantilever bends, reducing the filter capacitance.
Consequently, the reflection coefficient peak (yellow line) moves from
2186 MHz to 2714 MHz. From [37].
The consequent capacitance decrease causes a frequency shift
of the filter notch frequency, as shown in Fig. 4. This sensor
can be read wirelessly by simply connecting the resonator to
an antenna, leading to a chipless tag.
The same hybrid approach adopted for the harmonic crack
sensor, involving an alternative flexible substrate, copper
adhesive laminate, and discrete lumped components, is used
to manufacture an autonomous radio-frequency identification
(RFID) sensor for precision agriculture [23]. The sensor is
based on a commercial RFID chip (model EM4325 from EM
Microelectronic) with an integrated temperature sensor; the
chip is connected to a folded dipole antenna manufactured on
a PLA substrate. The chip can operate in passive mode and
semi-active mode. In the passive case, the interrogating RF
signal transmitted by the reader is used both for backscatter
communication and to activate the transponder circuitry. In
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RAHMANI ET AL.: NEXT-GENERATION IoT DEVICES: SUSTAINABLE ECO-FRIENDLY MANUFACTURING, ENERGY HARVESTING
FIGURE 5. 24-GHz Doppler radar front-end on cellulose: (a) Layout of the
top layer. (b) Layout of the bottom layer. (c) Output signal obtained by
observing the movement of a cooling fan at a 1 m distance from the radar.
The circuit area is 35 mm x 28 mm. After [39], [40].
a semi-active case, the interrogation signal is used only for
communication, while an additional energy source is used for
the circuitry, which increases the chip sensitivity significantly.
In the proposed solution, flexible solar cells from Ribes Tech
provide the extra power the tag needs in semi-active mode.
Leveraging the transparency of the PLA substrate, future
developments can be envisioned in which the same transpar-
ent substrate is used both for the antenna and for the solar
cell [38].
In [39], [40], for the first time, a 24-GHz radar front-end
and its antenna were integrated on a multilayer cellulose-
based substrate, manufactured by alternating paper, glue, and
copper layers. The circuit exploits a distributed microstrip
structure that is realized using a copper adhesive laminate,
which guarantees a low conductive loss. The radar shown in
Fig. 5 operates at 24 GHz and transmits 5 mW of power. The
antenna has a gain of 7.4 dBi and features a half-power beam
width of 48 degrees. The sensor has a size of a stamp. It can
detect the movement of a walking person up to 10 m in the
distance, measuring a minimum speed of 5 cm/s up to 3 m/s.
This experiment demonstrates that circuits on cellulose can
operate at record frequencies and that ultra-low cost, green
(i.e., recyclable and biodegradable) materials can be a viable
solution to implement, at least in part, the radio-frequency
hardware for the upcoming IoT era.
In all of the above-described solutions, the transponders
feature some residual non-recyclable parts due to a few
commercial lumped components and interconnects that must
be separately discarded. Significant research is being done on
realizing green organic non-linear devices. So far, the limiting
factor is represented by the reduced transit frequency of the
developed diodes and transistors. In [48], an attempt to obtain
a close to 100% green harmonic transponder (tag) is reported.
The harmonic tag is based on a pentacene diode, and a couple
of concentric copper coils stuck on a paper substrate. The tag,
operating at 7.5 MHz, although still characterized by a short
read range and high conversion loss, represents a promising
way for future all-natural IoT electronics.
The proposed solution on paper is compared with other
24 GHz state-of-the-art radar frontends in Table 3. Although
we currently find integrated radar frontends up to sub-THz
frequencies, this work demonstrates the possibility of im-
plementing multilayer RF frontends on paper at millimeter
waves.
III. SUSTAINABLE POWERING IoT DEVICES
The urge for energy-independent electronic devices is intensi-
fying with the advances in IoT technology. Currently, the most
common solution for powering electronics is batteries. On
the other hand, recent advances in semiconductor technology
have resulted in a significant integration capability and size
reduction of electronics. Yet, the overall size of an IoT device
is not scaled at the same rate since it is dominated by the size
of powering and energy storage components. State-of-the-art
batteries have centimeter-scale footprints due to the limited
power density of energy storage technologies. They fail to
address the demands of long-term miniaturized devices. In
addition, the raw materials used in battery manufacturing,
such as lead, fluorinated electrolytes, and cobalt, are toxic and
lead to undesired consequences. Therefore, it is essential to
eliminate batteries from IoT devices and explore alternative
powering sources for realizing self-powered devices.
A. ENERGY HARVESTING
In the past few years, various energy harvesting techniques
have been proposed to tackle the issues of battery-powered
devices. Some major advantages of using energy harvesting
are: 1 – They are easy to manufacture and reduce the cost
and rounds of maintenance. 2 – They result in much less
carbon emission compared with battery-based solutions. 3 –
They can be implemented on green materials (substrates) that
are biodegradable [71], bio-compatible, pollution-free [61].
4 – They are easily integrated with readily available wire-
less communication systems [71]. The energy sources can
be categorized as ambient and dedicated energy sources. The
ambient energy sources are more attractive because they do
not require any additional power transmission link and utilize
already-existing energy sources, solar, wind, motion, and RF
radiations. However, in many wireless applications, ambient
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TAB L E 3. Comparison With 24 GHz State-of-the-Art Doppler Radar Frontends
FIGURE 6. Summary of different sustainable powering solutions for IoT devices with parameters including types of system (energy source), working
principle, advantages, power density, and efficiency [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68],
[69], [70].
energy sources do not guarantee the Quality-of-Service (QoS)
due to uncertainties in time, location, and weather conditions.
Dedicated energy sources, e.g., narrow beam RF radiations,
are alternative energy sources to ensure reliability and QoS
in wireless applications at the expense of higher cost and
resources [72].
Fig. 6 reports a summary of some of the popular
sources in energy harvesting applications along with their
working principles, advantages, power density, and effi-
ciency. The state-of-the-art sustainable energy sources in-
clude biofuel cells [73], enhanced tribo-electric/piezo-tribo-
electric nanogenerators [61], [63], [74], perovskite solar
cells [53], [75], acoustic energy sources [51], piezoelec-
tric sources [60], thermoelectric generators [55], and py-
roelectric energy sources [51], [59] with sensitivities of
7900 μW/cm2, 2.5 W/m2, 100000 μW/cm2, 1436 μW/cm2,
29.2 μW/mm3, 147 mW/cm2,3.5μW/cm3[51], respectively.
Electromagnetic-based power transmission, in particular, is
one of the most commonly used mechanisms in WPT and
energy harvesting schemes [76]. Inductive coupling, ambient
RF radiation, and dedicated RF radiations are three different
types of EM-based energy harvesting schemes that enable
various applications and provide a wide range of power den-
sities. One of the most popular energy harvesting solutions is
electromagnetic waves. However, we can use the RF energy
sources in ambient and dedicated fashions. Inductive WPT is
commonly used in medical implants, wearables, and portable
devices with a short operating range (≤1 m). It is considered
a dedicated energy source that is predictable, controllable,
and achieves high efficiencies (≥80%). The ambient RF ra-
diation is commonly used for wireless sensor nodes with an
operating range of a few tens of meter and provide a power
density of 0.2 nW/cm2∼1μW/cm2. On the other hand, RF
radiation can be used as a dedicated energy source to guar-
antee reliability and contractility. A dedicated RF radiation
requires additional resources to ensure energy transmission
is carried through a dedicated link and can function at long
operating ranges (hundreds of meters) by focusing the ra-
diated beam and operating at GHz or mmWave frequency
ranges [72].
Hybrid energy harvesters have been considered to improve
the reliability of battery-free IoT devices. Multiple energy
sources are combined to alleviate the limitations of a partic-
ular energy source. For instance, solar cells cannot operate at
night, but ambient or dedicated RF radiation can be used in
the absence of light [77]. EM-based techniques are emerging
among various energy sources as promising generic solutions
compatible with next-generation IoT devices. EM radiation at
a higher frequency range makes it possible to integrate energy
harvesting circuitry and components on commercial CMOS
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FIGURE 7. Conceptual schematic of an RF energy harvester with an
optional matching network.
technology to realize low-cost and miniaturized system-on-
chip (SoC) IoT devices [78], [79], [80].
B. RF ENERGY HARVESTERS
The ambient RF radiation with a power density of sev-
eral nW/cm2opens up applications of sustainable batteryless
wireless sensor nodes with minimal functional capabilities.
These batteryless wireless sensor nodes can be deployed
in harsh and remote environments for sensing and moni-
toring applications [81]. The batteryless operation improves
the sustainability of the sensor nodes, ensuring zero battery
replacement and low maintenance costs. The batteryless wire-
less sensor nodes are driven by an RF energy harvester which
harvests the incoming RF energy to DC energy. Given the low
available input RF power, the performance of the RF energy
harvester depends on the PCE, the startup sensitivity, and the
strength of the incident RF energy [82].
Fig. 7 shows the conceptual picture of an RF energy har-
vester. The RF energy harvester typically includes an antenna,
an optional matching network, an ultra-low-power (on-chip)
RF-DC converter, and an output load. The ultra-low-power
RF-DC converters in [83], [86], [87], [88], [89], [90], [91],
[92], [93], [94] have a very high input impedance that is of
capacitive nature. It presents a challenge to match the RF-DC
converter to a 50 system.
Here, we delve into the challenges and possible solutions
for designing RF energy harvesters for the target batteryless
wireless sensor nodes. We present two specific implemen-
tations of RF energy harvesters optimized for high-power
conversion efficiency and ultra-low-power startup. The pre-
sented RF energy harvesters include the ultra-low-power
RF-DC converter in [83]. However, the presented RF energy
harvesters can also be designed using the ultra-low-power RF-
DC converters in [86], [87], [88] and [93]-[94]. The RF-DC
converter sub-system designed in an Infineon 130 nm CMOS
process is a modified Dickson charge pump with threshold
compensated CMOS diodes, which help to achieve a low-
power startup.
Design-I of the RF energy harvester shown in Fig. 8(a)
includes the RF-DC converter mounted on a low-dielectric
Rogers 4350B board, including an L-matching network. In
post-layout simulations, the RF-DC converter shows an input
impedance of 2-j240 at 868 MHz. The ultra-low-power na-
ture of the RF-DC converter demands an L-matching network
comprising a high-quality (Q) factor 27 nH CoilCraftTM RF
FIGURE 8. RF energy harvester prototypes on Rogers 4350B boards:
(a) design-I with a matching network to interface to a 50 antenna and
(b) design-II with a matched single-ended loop antenna.
inductor and a 10 pF ATC RF capacitor to connect to a 50 
antenna.
The design-II includes a conjugate-matched single-ended
loop antenna directly connected to the RF-DC converter to
achieve resonance at 868 MHz. The single-ended loop an-
tenna on a Rogers 4350B substrate in Fig. 8(b) is designed
using electromagnetic (EM) simulations with an impedance
of (2+j240) to power-match the chip impedance and a
maximum realized gain of 1 dBi [84]. The RF-DC converter
has been optimized for sub-microwatt input power startup.
Thus, the single-ended loop antenna has been designed to
match the RF-DC converter’s input impedance at this power
level of −30 dBm.
The measurement results of the two designs of the RF
energy harvester at 868 MHz are shown in Fig. 9, i.e., the
sensitivity and PCE. For a fair comparison, the antenna gain
of design-II has been de-embedded to compare the perfor-
mance of the two RF energy harvester designs. Design-I,
which includes a matching network, suffers from an additional
insertion loss due to the limited quality factor of the lumped
components. In comparison, design-II consists of a matched
single-ended loop antenna and avoids lumped elements in the
design. As a result, as shown in Fig. 9(a), the RF energy har-
vester achieves a 1 V sensitivity of −20 dBm for design-I and
−25 dBm for design-II. At a higher power level of −10 dBm,
most of the input power is delivered to the RF-DC converter.
As a result, the insertion loss of the matching network is less
significant; here, the performances of design-I and design-II
are comparable. The PCE versus input power PIN curves in
Fig. 9(b) highlight a much better design-II efficiency than
design-I for a load of 1 M at 868 MHz. Design-I achieves
a peak PCE of 53% at −17 dBm (20 μW), which implies
that roughly 10 μW is harvested at the output. At lower
input power levels of 4 μW, 1 μW is gathered at the output
by design-I. This harvested power is sufficient to power up
an ultra-low-power wake-up receiver [95], temperature sen-
sor [96], and power management circuits [97], [98] of an IoT
device.
244 VOLUME 3, NO. 1, JANUARY 2023

FIGURE 9. Performance of the RF energy harvesters for a 1 Moutput
load: (a) output voltage VOUT versus input power PIN and (b) power
conversion efficiency versus PIN (f =868 MHz).
In comparison, state-of-the-art ultra-low-power RF energy
harvesters have been reviewed and listed in Fig. 10. The
RF energy harvesters have all been designed for sub-1 GHz
frequency industrial, scientific, and medical (ISM) bands.
The RF energy harvesters shown in Fig. 10 can be classi-
fied into three categories: RF-DC converter, RF-DC converter
with a Matching Network (MN), and RF-DC converter with
a matched antenna (Ant.). The works in [85], [88], [91],
and [93] present low-power startup RF-DC converters where
the losses of the matching network have been de-embedded.
As a result, the RF-DC converters have a high peak PCE
between 30%–40%. The inclusion of the matching network
losses has a strong impact on the peak PCE due to the high
insertion losses as seen in Design-I, [86], [88], [90], [92],
and [94]. Including a power-matched antenna to avoid a
matching network greatly benefits the ultra-low-power RF
energy harvesters, as shown in Design-II and [89]. Despite a
low PCE, the work in [90] achieves a good PCE at a low power
level of −21 dBm. Fig. 10 also highlights an interesting trend
in RF energy harvesters which are predominantly designed
in the older CMOS technology nodes like 90 nm, 130 nm,
FIGURE 10. Performance overview of the peak PCE of the various
ultra-low-power sub-1 GHz RF energy harvesters including their
technology nodes (RL=1M).Thelistedworkscanbeclassifiedintothree
categories: RF-DC converter, RF-DC converter and the matching network,
and RF-DC converter and a matched antenna.
FIGURE 11. Power flow in the wireless link of a WPT system for medical
implants [101].
and 180 nm. The older technology nodes offer metal oxide
semiconductor transistors with much lower leakage, which is
highly beneficial for the design of RF energy harvesters.
The results show that for an ultra-low-power design and
batteryless sensor nodes, power-matching of the antenna
becomes more and more critical compared to Ultra-High
Frequency (UHF) RFID tags [99], [100]. It is highly ad-
vantageous to design an RF energy harvester that includes
a conjugate-matched loop antenna for ultra-low-power har-
vester applications.
C. WIRELESS POWER TRANSFER
Modeling an EM-based WPT system using a two-port net-
work is a generic approach for modeling a WPT system since
we can apply it to both near-field and far-field EM operating
regions [101]. Fig. 11 shows a conceptual inductive WPT
scheme where the wireless link is composed of air and bio-
logical tissues. The overall power transfer efficiency (PTE) is
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defined as the delivered power to load of the power harvesting
system Pload over available power by the generator PG.
The PTE can be viewed as a multiplication of wireless link
efficiency ηlink and RF to DC conversion efficiency ηRF-DC.
The power receiving coil/antenna is one of the critical com-
ponents in a wireless power receiver and creates a dilemma
in choosing the operating frequency. It is desired to operate
the system at a higher frequency to utilize millimeter-sized
antennas/coils with acceptable efficiencies. On the other hand,
the propagation path loss is a function of frequency. The link
efficiency can be defined as the ratio of the delivered power to
the load of the two-port network over the generated power by
the RF source. It can be divided into three distinguished terms
(see Fig. 11):
ηlink =PL
PG
=ηm,Tx ×η2port ×ηm,Rx.(1)
The η2port term contains power losses in the coils and the
intervening medium. In contrast, the ηm,Tx and the ηm,Rx
represent the power losses due to impedance mismatch at
the TX and RX sides, respectively. The received RF signal
should be converted into a stable DC voltage to power the
embedded electronics. The RF to DC conversion is usually
done by a voltage rectifier and regulator. Therefore, ηRF-DC
can be considered as multiplication of rectifier efficiency ηrec
and regulator efficiency ηreg. While the operating frequency
is usually determined by the standards, in some applications,
such as medical implants, it can be chosen to optimize the
performance of the link. However, the operating frequency is
not the only controlling factor in the overall PTE. For instance,
voltage rectifiers are known to be non-linear components, and
their conversion efficiency is a string function of the input
power and loading, as shown in the following expression:
ηrec (Pin,RL,f)=PDC
Pin
.(2)
For a given transmitted power, the received power may vary
considerably, depending on the link composition, the orienta-
tion of the transmitter (TX) and the receiver (RX) antennas,
and the load of the rectifier. Therefore, operating frequency
and the matching network should be tuned adaptively to
guarantee maximum PTE [102], [103], [104]. Moreover, the
transmitted power level cannot be increased to compensate
for the additional losses in the link as safety standards and
regulations limit it. Specific absorption rate (SAR) is a perfect
example of these regulations that limits human body exposure
to EM waves [105], [106]. As a result of the link ambiguity
and the limits of the transmission level, the maximum deliver-
able power to a millimeter-sized integrated power harvesting
system is bound to ∼100 μW, and ∼μW for near-field and
far-field systems, respectively [78], [92], [101]. The power
flow into a millimeter-sized fully-integrated IoT device is
insufficient to continuously drive the power-hungry building
blocks, e.g., wireless communication and stimulators. The
remedy to this issue is duty-cycling the power-demanding
building blocks operation to reduce the system’s average
FIGURE 12. Block diagram of a fully integrated millimeter-sized data
transceiver with a wireless power receiver and PMU [107].
FIGURE 13. Illustration of IoT connectivity technologies’ features in data
rate, coverage, and latency [108].
power consumption. Fig. 12 shows an example of a fully
integrated power harvesting system with a power management
unit (PMU) to set the activation time of the data transmitter.
Depending on the available RF power at the RX and the power
consumption of the load, the PMU sets the power delivery
state to continuous or duty-cycled mode, which enables the
system to drive IoT devices with a wide range of power con-
sumption.
IV. WI RELESS CON NECTIVITY FOR IOT DEVICES
Wireless connectivity is the core of IoT technology, en-
abling large-scale digitization by driving a paradigm shift
from point-to-point monitoring to an all-connected-through-
Internet scheme. Various IoT applications can be segmented
into three major verticals: consumer (e.g., smart homes and
wearables), enterprise (e.g., supply chain, asset tracking, and
fleet management), and industrial (e.g., smart manufactur-
ing, smart utilities, and robotic automation). Due to these
applications’ diverse and multifaceted nature, it is impossi-
ble to develop a unique wireless connectivity solution that
fits all of these applications. The existing wireless connectiv-
ity technologies offer different operating ranges, data rates,
246 VOLUME 3, NO. 1, JANUARY 2023

and latency, as shown in Fig. 13 [108]. The existing tech-
nologies have a natural trade-off between latency and power
consumption. For instance, ZigBee and Bluetooth standards
offer low-power consumption in short-range technologies,
while Optical Wireless Communication (OWC) provides low
latency. The same trade-off is observed in the long-range cat-
egory between cellular (LTE/5G) and Low Power Wide Area
networks (LPWANs).
Although the existing technologies have successfully ad-
dressed the needs of many applications so far, the mass scaling
of IoT devices in future applications imposes more demanding
specs on the maximum data rate, latency, and power consump-
tion. Active research trends on low-power communication
have been focused on improving the energy efficiency of the
current ultra-low-power techniques, such as backscattering.
Cellular wireless technology, 5G and beyond, has been a
critical enabler of many modern IoT applications. It is envi-
sioned we will accelerate the progress of wireless connectivity
through the increased network agility, capacity to use secure
devices, and integrated Artificial Intelligence (AI) offered by
wireless technologies beyond 5G. Moreover, 5G and 6G wire-
less technologies operate at mmWave and sub-THz frequency
ranges. Wireless connectivity could be expanded as a sensing
tool, and new joint communication and sensing opportunities
are offered.
The emerging applications of IoT systems instate high
energy efficiency (required energy for successful wireless
transmission per bit) and high data throughput on commu-
nication systems. Moreover, wireless connectivity solutions
should support a high-density user population. In this section,
we have focused on backscattering as one of the most energy-
efficient modulation schemes, [109], and have provided the
latest efforts on increasing the data rate of backscattering
radios by 1 – using higher order modulation and 2 – increasing
the operating frequency to millimeter waves and sub-THz
region. In addition, we review an ultra-wide-band communi-
cation technique as one of the strong candidates for enabling
low-power localization in a user-dense network.
A. QAM BACKSCATTERING
Traditional RFID systems and passive sensors use amplitude
shift keying (ASK) and phase shift keying (PSK) for commu-
nication modulation. UHF RFID systems are a solution for
substituting barcodes, having an increased interest in several
approaches, such as non-line-of-sight communications and
tracking. They are much more robust in harsh environments.
As presented before in [117], recent work [111] shows
that higher-order modulation schemes can be used in RFID
approaches also, this includes, for instance, 4-quadrature
amplitude modulation (4-QAM). These modulation schemes
increase the data rate by transmitting 2 bits as a single symbol,
and thus in the long-range will reduce power consumption
and increase read range. In [111], [118] a 4-QAM backscatter
modulation is presented using a semi-passive system, in that
case, a 3 V coin cell battery is used to power up the micro-
controller. This microcontroller commands a quadrature phase
FIGURE 14. System prototype: The system comprises a 16-QAM modulator
and a rectifier (substrate for the transmission lines is Astra MT77,
thickness =0.762 mm, εr=3.0, tan δ=0.0017) and in [115].
shift keying (QPSK) modulator using 4 different impedances
selected by 4 RF switches. Furthermore, they also expand
their work to a 16-QAM modulator backscatter operating
at UHF, where they claim a modulator power consumption
of 1.49 mW with a data rate of 96 Mbps as can be seen
in [112]. Similarly, this modulator was implemented using
5 switches, and several lumped impedances, being able to
recreate a 16-to-1 multiplexer, that operates in 16 different
levels, creating the 16-QAM states. The approach followed
by [113], was also to implement an I/Q backscatter modulator,
in that case, they used two PIN diodes to implement differ-
ent impedances by controlling the bias currents. The circuit
implemented used a Wilkinson power divider combined with
two different filters and one PIN diode in each branch to im-
plement the modulator. By using this strategy, they achieved
80 mW, assuming mainly the modulator and not considering
any digital counterpart, which clearly is a significant value, if
the proposal is to create a passive TAG. Pozar [119] also uses
PIN diodes in a reflection-type phase shifter configuration,
in that case, two PIN diodes and a quadrature hybrid were
used. This configuration works by commuting the diodes in
an on-and-off stage, which produces a phase change at the
output of the modulator. Nevertheless, the consumption of the
PIN diodes shows that this is not a viable solution for passive
or semi-passive approaches. Kimionis et al. [120], presented
a different approach to developing a binary phase shift keying
(BPSK) modulator. The approach follows a phase shift using
two different switches connected to different delay lines, one
with 0◦and another one with 90◦delays. By commuting
the switches, the delays were changed, and thus the BPSK
phase also changed. Finally, the authors in [114] presented a
330 Mb/s of data rate at 2.9 GHz, using BPSK modulation.
Table 4 compares the modulators’ results from the provided
state-of-the-art references. In [115], the authors have pro-
posed an alternative solution, presented in Fig. 14 divided into
two main blocks, the backscatter modulator and an RF-DC
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TAB L E 4. Performance Summary and Comparison
FIGURE 15. Received signal constellation with EVM and energy per bit
consumption as a function of input power for 960 Mb/s as in [115].
converter. The first block, the backscatter modulator, is com-
posed of a Wilkinson power divider, two matching networks,
and two enhancement-mode high-electron-mobility transis-
tors (E-pHEMTs).
In each branch used, the phases are separated by 45◦phase
shifts, creating a 90◦phase for each of the branch reflected
waves. By selecting a different gate voltage at each transistor,
we can actually change the impedance seen by the drain, and
thus change the reflection coefficient in the Smith chart seen
by the antenna. Creating a 16-QAM constellation or even
more.
The other block is the RF-DC converter, where the power to
energize any microcontroller or sensor can be gathered. This
is done using a five-stage Dickson multiplier that is tuned at
the WPT frequency, which operates at 1.7 GHz, the backscat-
ter block operates at a different frequency (2.45 GHz).
The continuous change of voltage levels at the gate of the
transistor will induce different impedances at the input of
the rectifier, creating some burden on the simultaneous de-
sign of the backscatter and RF-DC converter. The system
followed the approach used in [121] by using two different
frequencies, one for the backscatter communication and the
other for the WPT. When the E-pHEMTs are unbiased, the
RF-DC presents 56% of efficiency when 5 dBm of input
power is considered. The change in voltage to operate the
backscatter block degrades this efficiency, with a worst-case
of 10%. The maximum performance achieved with this circuit
is represented in Fig. 15, where for a data rate of 960 Mb/s,
and an error vector magnitude (EVM) of 8.37% the energy
consumption is only 59 μW. For a load of 21.5 kOhm the
FIGURE 16. DC output voltage and efficiency as a function of input power
at 1.7 GHz with an unbiased gate of each E-pHEMT as in [115].
average DC output voltage and the overall generated effi-
ciency can be seen in Fig. 16 when the input power is varied.
As said above a maximum of 56% efficiency for a 5 dBm
input power at 1.7 GHz was obtained when both transistors
were unbiased. By using different frequencies for WPT and
backscatter, the RF-DC converter can actually behave better
for high impedance changes at 2.45 GHz.
The presented prototype circuit works with two different
frequencies, one for the WPT link and the other to perform
the backscatter communication [115]. This modulator’s en-
ergy consumption per bit can be as low as 61.5 fJ for a data
rate of 960 Mb/s with an EVM of 8.37%. The system has
demonstrated some WPT capabilities with 56% of efficiency
for an input power of 5 dBm. The presented solution is able
to provide high bandwidth solutions for low-power IoT future
developments.
B. MILLIMETER WAVE AND SUB-TERAHERTZ
BACKSCATTERING
Existing wireless networks are limited in the number of
nodes they can concurrently support [122], [123]. Higher
frequencies, i.e., millimeter-wave and sub-terahertz bands
provide unique opportunities for concurrent transmissions:
First, the large spectrum in this regime facilitates dense user
populations to operate concurrently at orthogonal frequency
channels. Second, narrow-beam directional transmission and
reception, which is mandated due to the high path loss, can
achieve network scaling by providing opportunities for space
division multiple access. Finally, the mm-scale wavelength
offers fine-grained localization for future IoT applications.
248 VOLUME 3, NO. 1, JANUARY 2023

These frequencies provide the best of the RF and optical spec-
trum: like RF, they can be phase modulated and experience
lower penetration and reflection losses compared with optical
while still providing a large swath of continuous bandwidth
and laser-shaped beams (just like in optical communication).
Despite these exciting prospects, operation at such a high
frequency is fundamentally power-demanding since the power
consumption of the RF circuitry is proportional to the fre-
quency. This high power consumption has even stalled the
deployment of mobile 28 GHz nodes and will worsen at the
6G and THz regime [124], [125], [126], [127], [128]. Further-
more, directional transmission requires large antenna arrays,
which significantly increase the device’s power consumption
and complexity. This challenge worsens under mobility when
constant beam adaption is needed to maintain the link.
Backscatter technology is introduced for energy-efficient
communication between power-constrained wireless de-
vices [129], [130]. The underlying idea is to allow low-power
nodes to piggyback their data on an ambient signal instead
of generating their own RF signal, which would demand
power-hungry components such as mixers, oscillators, and
amplifiers [131]. Recently, there has been significant work
on extending the communication range [132], [133], [134],
[135] and improving the data rate of backscatter communi-
cation links [136], [137]. In particular, employing low-power
coding techniques such as chirp spread spectrum has shown
promise for decoding backscattering signals below the noise
floor [138]. However, while these techniques can achieve
long-range communications, they often do not scale well with
the number of devices, i.e., they are often limited to very
few (1–2) concurrent links. A recent work [139] allows for
concurrent transmission of 256 backscatter devices over a
bandwidth of 500 kHz. This work relies on the ability of
the low-power nodes to generate cyclically shifted chirps,
which is relatively power-demanding. Further, the number of
concurrent users is inherently bounded to the bandwidth and
the spectral resolution at endpoint devices. Therefore, most
existing low-power backscatter solutions have been limited
to sub-6 GHz bands [140], [142] as the main challenge of
directionality at low power cost remains.
The tags should be retrodirective to close a directional link
between a mmWave/sub-THz reader and a low-power tag.
Retrodirectivity is the capability of a tag to reflect an incident
signal toward the source direction without prior knowledge
of its direction of arrival. In the literature, there are three
methods to achieve retrodirectivity in wireless systems: phase
conjugate arrays, Van Atta arrays, and leaky-wave antennas.
Phase conjugate arrays use heterodyne techniques to conju-
gate the phase of the incoming signal at each antenna element
resulting in a radiated beam back toward the source direction.
However, such a design requires mixing the impinging RF
with a local oscillator [142] at each element, which makes
the array bulky, power-hungry, and therefore unsuitable for
IoT applications. Recently, the structures like Van Atta Arrays
have shown great potential for mmWave backscattering (up to
28 GHz) [137], [143], [144], [145].
FIGURE 17. Van Atta retro-directive array: This passive multi-antenna
architecture reflects any incident wave in reverse, parallel to the direction
of incidence, creating a directional link with a reader at zero power cost.
The idea of Van Atta arrays dates back to 1960 [146].
As shown in Fig. 17, they consist of an array of antennas
connected in symmetrical pairs by transmission lines. Every
antenna in this array serves as receiving and transmitting el-
ements. The signal received by each antenna is transmitted
through the line and re-radiates from the corresponding paired
antennas. To create an emission pattern that points back to the
transmitter, the transmission lines should not contribute other
phase differences to incident waves, i.e., they have an equal
length or their length differences equal to multiples of the
guided wavelength. Further, transmit-receive antenna pairs are
deliberately arranged in a mirror-symmetric manner to cause a
phase reversal for the reflected beam compared to the incident
wavefront.
Unlike phase-conjugated arrays that require active com-
ponents, Van Atta arrays can be designed entirely with
passive components, which makes it well-suited for low-
power backscatter. However, the fundamental limitation is that
Van Atta Arrays are inherently narrow-band as the transmis-
sion lines are optimized at a particular wavelength, which
is fixed (non-configurable) after fabrication. In other words,
communication bandwidth is inherently limited despite carrier
frequencies being in the mmWave regime. The most recent
spectrally-agile retrodirective structure is built on a design
called leaky-wave antenna [148]. Leaky-wave antennas are
waveguides with open slit(s) on one side. Their exciting char-
acteristic is that guided waves can leak out into free space such
that the emission angle is correlated with the frequency of
the signal [148]. These frequency-dependent radiations have
been recently exploited for THz path discovery and local-
ization [149], [150], [152], and have also been demonstrated
in CMOS technology [152]. The key insight is that leaky
waveguides have reciprocal transmission and reception char-
acteristics. When it acts as a receiver, the impinging signals
couple into the waveguide only if their spectral content agrees
with the incident angle (i.e., where the angle of emission
and reception from the waveguide is frequency-dependent).
Hence, by devising two symmetrical slits, one for accept-
ing free-space ambient signals into the waveguide and the
other for leaking those signals back into the air, one can
enable retrodirectivity. As shown in Fig. 18, an active far-
field transceiver emits a THz signal toward the leaky tag.
The impinging signal would then couple into the waveguide,
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FIGURE 18. Illustrating the retrodirective backscatter link between leaky
scatter and a broadband sub-THz transceiver [148].
which is guided toward the second slit and radiates out back
to the free space forming a directional beam that points to
the transceiver’s location, thereby enabling retrodirectivity.
We emphasize that this retrodirective structure is truly wide-
band and spectrally agile as it can operate between 100 GHz
and 500+ GHz. Further, the directionality is achieved with
zero power consumption. However, the active transceiver is
expected to be power-demanding as it should be capable of
generating tunable wideband signals.
C. ULTRA-WIDE-BAND COMMUNICATION
Ultra-wide-band (UWB) communication is one of the best
candidates for IoT devices due to its superior robustness for
radio channel fading and its intrinsic low-energy require-
ments. This section describes some available topologies of
UWB batteryless tags and their localization performance.
Usually, UWB must be coupled with UHF to obtain battery-
less operation due to the UWB mask’s insufficient low-power
constraints to support the energy required for pulse genera-
tion. In [154], [154]. a UHF rectenna is integrated with the
UWB system for energy harvesting purposes [154], [154]. An
energy-autonomous UWB system for localization is presented
in [156], where a tag equipped with UHF and UWB is shown;
Distributed power sources support its operation at UHF, and
anchor nodes at UWB are used for the tag localization. For
a sustainable batteryless UWB operation, an integrated co-
design of the tag and the antenna front-ends is required to
minimize all the possible sources of losses. This includes the
nonlinear/EM co-design of the RF sub-systems and antennas
and the base-band circuitry for power management purposes.
In [156], proofs-of-concept of energy-autonomous UWB tags
are designed and tested. The UWB pulse generator is success-
fully powered by exploiting the WPT sources distributed in
the environment. The activation of the whole system has been
demonstrated at a 10 m distance with a received RF power of
only −13 dB, from cold-start conditions.
We may realize the antenna system by adopting eco-
friendly materials to be deployed for massive object mon-
itoring in IoT-like environments. System compactness and
FIGURE 19. A spiral/dipole integrated antenna for accomplishing UHF
energy harvesting and UWB backscattering communication.
FIGURE 20. Current density distribution over the spiral/dipole antenna at
selected operating frequencies.
lightness goals are reached starting from the antenna’s im-
plementation, covering both UHF and the European UWB
bands [154] with a unique metalization design, using a cus-
tomized spiral antenna. A prototype of this solution is shown
in Fig. 19, where the UHF-UWB operations have been ob-
tained using a modified spiral antenna, acting as a dipole
in the UHF band. Representative current distributions at dif-
ferent operating frequencies are shown in Fig. 20, testifying
to the predicted operation of the multi-band antenna. To
decouple the UHF and UWB operation, a miniaturized du-
plexer in microstrip technologies has been co-designed with
the UWB-UHF antenna to account for the effect of their
near-field interactions when the diplexer is integrated into the
antenna backplane. In [156], the design and integration of a
High Impedance Surface (HIS) into the antenna system allow
for insensitivity to the background of the one-port spiral-
dipole combination while maintaining a low-profile stack-up
structure. This way, the antenna system can be integrated with
different materials without affecting its performance. A 3D
printing realization increases the structure’s robustness and
reliability.
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FIGURE 21. Circuit schematic of a chipless UWB tag consisting of a
rectenna excited by an optimized multi-sine signal with two output paths,
one for collecting DC power and one for backscattering a quasi-UWB pulse
consisting of the intermodulation products resulting from the multi-sine
excitation.
FIGURE 22. Power spectra at the UWB port of the tag of Fig. 21 for
different tones spacings and an average input power of −10 dBm.
A chipless UWB/UHF tag with centimeter-level localiza-
tion has been obtained by a passive generation of a quasi
UWB signal, exploiting the nonlinear intermodulation (IM)
products generated by the multi-sine excitation of a full-wave
rectifier [158]. The rectifier circuit schematic is shown in
Fig. 21 and operates in dual mode since its output section
consists of two decoupled paths: a DC one, which drives
the DC output power into a load (that can be the equivalent
circuit of a PMU), optimized for maximum power conver-
sion efficiency; a UWB one which collects the low-power
higher harmonics generated by the rectifier to be backscat-
tered as a UWB signal, for passive localization purposes. This
architecture has proven to act as a chipless UWB tag (or
harmonic UWB tag, since no pulses generations are needed
on board) with energy harvesting capabilities. The suitable
rectifier/UWB backscatter tag needs to be designed based on
the concurrent signal shape optimization of the multi-sine
excitations and the rectifier components to simultaneously
maximize the harmonic contents of the IM products, flowing
to the UWB output path, and the DC power flowing to the DC
one. Using a novel, accurate, and efficient harmonic balance
simulation set-up, where the multi-tones are represented as the
higher harmonics of their frequency spacing, the optimized
topology and excitations are straightforwardly derived [158].
Fig. 22 represents the spectral contents of one of the UWB
frequency bands, obtained at the UWB output, as a function
of frequency spacing and the number of tones, with a total
RF power as low as −10 dBm. The relationship between the
UWB signal properties, in terms of bandwidth, the number
of tones and tones spacings, and the localization accuracy
can be predicted in a very efficient way. The co-designing of
the rectifier multi-sine excitation and the quasi-UWB pulse
passively generated by exploiting its IM products promises
an innovative and attractive solution for future IoT devices
that need to combine ultra-low power communication, local-
ization, and sensing. We demonstrated a unique and novel
implementation of UWB tags with centimeter-level precision
and no need for an onboard UWB pulse generator and the
related energy requirements.
V. CONCLUSION
This paper discusses eco-friendly manufacturing, sustainable
powering, and wireless connectivity for next-generation IoT
devices to ensure that IoT technology can sustainably grow
to be a part of the future connected world. Sustainable IoT
devices are enabled by addressing environmental concerns
using eco-friendly materials, reducing carbon footprints, and
removing toxic materials from the manufacturing processes.
Sustainable IoT devices are also enabled by exploiting en-
ergy harvesting and wireless power transfer technologies to
eliminate the eco-toxicity of batteries or, if it is impossi-
ble to operate without a battery fully, to reduce the cost of
battery replacement. Another enabler of sustainable IoT de-
vices is novel wireless connectivity solutions compatible with
batteryless operation and energy harvesting schemes as, for
example, retroreflective connectivity in the millimeter wave
bands and beyond, higher-order modulation schemes, and
wideband communication to improve the data rate and user
density in the backscatter networks.
Throughout the article, we present unique design solutions
providing sustainable IoT devices in one or more aspects of
reaching sustainability. For example, we present backscatter
IoT devices that rely on a wireless power transfer from the
interrogator device, provide a batteryless operation, and are
realized on an eco-friendly substrate material. However, there
are many more aspects of sustainability than we have pre-
sented, e.g., sustainability issues of IoT devices on a societal
level regarding the security and privacy of data. Thus, to reach
fully sustainable IoT solutions, RF engineers have to team
up with researchers from other disciplines. We also envision
increasing interdisciplinary research efforts to address the
further-increasing design requirements of IoT devices, e.g.,
by teaming up with computer scientists and exploring tiny
artificial intelligence algorithms to provide reliable wireless
communication in harsh propagation environments.
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