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INTERNET OF BIO‑NANO THINGS: A REVIEW OF APPLICATIONS, ENABLING TECHNOLOGIES
AND KEY CHALLENGES
Murat Kuscu1and Bige Deniz Unluturk2
1Department of Electrical and Electronics Engineering, Koc University, Rumelifeneri Yolu 34450, Sariyer, Istanbul,
Turkey, 2Department of Electrical & Computer Engineering and Biomedical Engineering, 775 Woodlot Dr., East Lansing,
48823, MI, USA
NOTE: Corresponding author: mkuscu@ku.edu.tr
Abstract –Internet of Bio‑Nano Things (IoBNT) is envisioned to be a heterogeneous network of nanoscale and biological
devices, so called Bio‑Nano Things (BNTs), communicating via non‑conventional means, e.g., molecularcommunications (MC),
in non‑conventional environments, e.g., inside human body. The main objective of this emerging networking framework is to
enable direct and seamless interaction with biological systems for accurate sensing and control of their dynamics in real time.
This close interaction between bio and cyber domains with unprecedentedly high spatio‑temporal resolution is expected to
open up vast opportunities to devise novel applications, especially in healthcare area, such as intrabody continuous health
monitoring. There are, however, substantial challenges to be overcome if the enormous potential of the IoBNT is to be realized.
These range from developing feasible nanocommunication and energy harvesting techniques for BNTs to handling the big
data generated by IoBNT. In this survey, we attempt to provide a comprehensive overview of the IoBNT framework along with
its main components and applications. An investigation of key technological challenges is presented together with a detailed
review of the state‑of‑the‑art approaches and a discussion of future research directions.
Keywords – Internet of Bio‑Nano Things, molecular communications, nanonetworks, bio‑cyber interfaces, THz‑band
nanocommunications, nanomachines, nanobiosensors, molecular machines, nanoscale energy harvesting
1. INTRODUCTION
As Internet of Things (IoT) approaches technological ma‑
turity with growing number of applications on the mar‑
ket, new integrative ideas emerge to push the current
boundaries of IoT and extend its application range. One
such approach follows a holistic view and regards the
universe as an interconnected entity which is to be ob‑
served, understood, and manipulated with new informa‑
tion and communication technologies (ICT). At the center
of this approach lies an emerging ICT framework, the In‑
ternet of Bio‑Nano Things (IoBNT), envisioning the
heterogeneous collaborative networks of natural and
artiicial nano‑biological functional devices (e.g.,
engineered bacteria, human cells, nanobiosensors),
seamlessly integrated to the Internet infrastructure [1].
IoBNT is positioned to extend our connectivity and
control over non‑conventional domains (e.g., human
body) with unprecedented spatio‑temporal resolution,
enabling paradigm‑shifting applications, particularly in
the healthcare domain, such as intrabody continuous
health monitoring and theranostic systems with single
molecular precision. The broad application prospects of
IoBNT have attracted signiicant research interest at the
intersection of ICT, bionanotechnology, and medical
sciences, with the great ma‑ jority of studies directed
towards (i) the design and implementation of Bio‑Nano
Things (BNTs) [2, 3], (ii) the understanding of natural
IoBNTs (e.g., nervous nanonet‑ work) [4, 5], (iii) the
development of communication and networking
methods for IoBNT (e.g., molecular communications)
[6, 7, 8], (iv) the design of bio/cyber and nano/macro
interfaces [9], and (v) the development of new IoBNT
applications [10, 11, 12].
Along the aforementioned directions, this survey
presents the most recent advances with respect to the
theoretical foundations and practical implementation
of IoBNT. To this end, we irst attempt to provide a
big picture of the IoBNT framework. Our discussion
starts with the natural IoBNT systems, which inspire
the researchers in designing artiicial IoBNT systems.
These include biological human‑body nanonetworks,
such as nervous nanonetwork, bacterial nanonetworks,
and plant communication networks. Interfacing these
systems with artiicial IoBNT systems that monitor and
control their biochemical states is expected to enable
novel IoBNT applications. We extend our discussion of
the IoBNT framework with the investigation of various
types of BNTs, including engineered‑cell based BNTs and
artiicial molecular and nanomachines, which ultimately
determine the capabilities of IoBNT. This is followed
by a review of potential IoBNT applications. Although
most of them concern healthcare, there are many novel
environmental and industrial applications promised by
IoBNT, such as smart agriculture, food quality control,
monitoring of toxic agents and pollutants, which are
reviewed in this paper.
We also provide a comprehensive review of the key tech‑
nical challenges in realizing the IoBNT applications, and
overview the state‑of‑the‑art solutions and future
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research directions that can target them. Developing new
communication methods for IoBNT is the foremost chal‑
lenge, as the conventional electromagnetic (EM) tech‑
niques are either not feasible for the size‑ and energy‑
constrained BNTs or not performing well in the envi‑
sioned IoBNT application environments, such as intra‑
body. Molecular communications have emerged as the
most promising technique to enable IoBNT, as it is already
utilized by natural BNTs in a ridiculously energy‑eficient
and robust manner. In addition to the detailed review of
MC research, we also look into other emerging communi‑
cation methods proposed for IoBNT, such as those based
on acoustic waves, terahertz (THz)‑band EM waves, and
Fö rster Resonance Energy Transfer (FRET). The emer-
ging idea of using human body as an IoBNT
infrastructure is also discussed through an overview of
thrubody haptic communications, vagus nerve‑based
communication and microbiome‑gut‑brain‑axis‑based
communication proposed to connect BNTs within human
body.
Bio‑cyber interfaces lie at the heart of IoBNT applica‑
tions, which consist in the seamless interconnection of
heterogeneous technologies in diverse application envi‑
ronments. We provide an extensive review of electri‑
cal and optical bio‑cyber interfacing technologies inclu-
ding biosensing‑, redox‑, optogenetics‑ and luores-
cence‑based techniques as well as the newly emerging
magnetic and THz‑based methods. IoBNT applications
with high spatio‑temporal resolutions in control and
monitoring are expected to generate and handle
signiicant amount of heterogeneous data, imposing
critical challenges of big data processing, storage, and
transfer, which are also reviewed in this paper.
Self‑sustaining BNTs are key to the success of IoBNT
applications. Although engineered cell‑based BNTs
might have an inherited metabolism for energy
management, artiicial BNTs such as those based on
nanomaterials should have dedicated mechanisms for en‑
ergy harvesting (EH) and storage for continuous opera‑
tion. We review various EH technologies that are suitable
for the envisioned BNT architectures and IoBNT applica‑
tion environments. Wireless power transfer (WPT) tech‑
niques and energy storage technologies are also reviewed
to provide a broader perspective on the energy challenges
of IoBNT. We also discuss the security, privacy, biocom‑
patibility and co‑existence challenges of IoBNT origina-
ting from the unprecedentedly close interaction with
the complex biological systems, including our own
human body.
Although there are many recent survey articles focused on
particular aspects of IoBNT [7, 13, 3, 6, 14, 15, 9, 16], this
comprehensive review is aimed at providing a broader
snapshot of the state‑of‑the‑art in the entire IoBNT ield
in order to contribute to an holistic understanding of the
current technological challenges and potential research
directions.
2. FRAMEWORK
2.1 Natural IoBNT
In the last several billion years, most basic single cell or‑
ganisms evolved into complex systems of multi‑cellular
organisms composed of living nanoscale building blocks,
i.e., cells, to perform the most intricate tasks in an
optimized fashion. This highly coordinated structure
of multicellular organisms are indeed a result of self‑
organized networks of cells communicating at various
scales. Hence, these networks can be considered as na-
tural IoBNTs and many lessons can be drawn in terms
of effective techniques of communications and
networking at nanoscale by observing the behavior of
these natural IoBNTS. Here, we will describe some of
the most natural IoBNTS, namely, human body
nanonetworks, bacterial nanonetworks, and plant
networks.
2.1.1 Human‑body nanonetworks
Biological systems in the human body are connected to
each other and communicate primarily through molecu‑
lar interactions and action potentials. These commu-
nication pathways enable the coordination of various
types of cells, which are basic building blocks of life,
and organization into tissues, organs, and systems
with different structures and functions. The dense
network of interconnected cells use signaling at
various scales such as juxtracrine (signaling among
cells in contact with each other), paracrine
(signaling among cells in the vicinity of each other,
but not in contact), or endocrine (signaling among
cells distant from each other). The performance and
reliability of this intrabody networks ensures the
health of the human body by preserving the equilibrium
state, i.e., homeostasis, achieved by tight control of
nervous system reacting to molecular and electrical
inputs coming from all parts of the body and
environmental cues coming through ive senses. Any
failure in communication in these networks
will deteriorate the health and lead to diseases [4].
For example, i) problems in electrical signaling of heart
cells cause arrhythmia, i.e., irregular heartbeat,
which can end in heart failure, stroke or sudden
death; ii) communication problems between the
brain and the body arising from the damage to
protective sheath (myelin) that cover nerve ibers
by immune system attacks which is the Multiple
Sclerosis (MS) disease potentially causing paralysis; iii)
irresponsiveness of cells to insulin which is a molecule
carrying information re-gulating metabolism in
endocrine pathways leads to diabetes; iv)
irregular signaling in the microbiome‑gut‑brain
axis, where microbes in gut and brain cells exchange
information through endocrine and nervous
pathways, is shown to affect mood, neuro-
development, and obesity. The most advanced and
complex human‑body network is the nervous system
[5], composed of a very large scale network of neurons
interconnected through neuro‑spike [17] and synapse
[18] communication channels. The nervous
nanonetwork distributed throughout the body
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
transfers information about external stimuli to the brain,
which is a dense network of highly complex neuron cells.
The brain processes all this information and sends
back commands to the body accordingly to control the
vital functions, behavior and physical activities. Other
networks spanning the whole body yet carrying
information on a slower scale than the electrochemical
pulses of nervous nanonetworks, are cardiovascular
system and the endocrine system both composed of
vessels carrying information in molecular form in blood
and lymph, respectively [4].
2.1.2 Bacterial nanonetworks
Besides the IoBNT in multicellular organisms such as hu‑
man body, single cell organisms such as bacteria show
coordination and group behavior enabled by intercellu‑
lar signaling. The irst communication mechanism among
bacteria discovered is quorum sensing (QS), the ability
to detect and respond to cell population density repre‑
sented by the concentration of the signaling molecules
called auto‑inducers [19]. QS controls bioilm forma‑
tion, virulence factor expression, production of secondary
metabolites and stress adaptation mechanisms. Using
this mechanism, unicellular bacteria coordinate their be‑
havior and act as if they are a uniied multicellular orga-
nism. Recently, besides the molecular means of QS,
electrical means of communication among bacteria has
been shown [20]. The bacterial membrane potentials
creating potassium waves through bacterial bioilms
synchronize the behavior of bacteria in bioilms. In
case of nutrient depletion in the center of the bioilm,
this signaling mechanism warns the outer circle of
bacteria in the bioilm to slow down growth
allowing more nutrients to penetrate to the center.
Using the above‑mentioned communication mechanisms,
bacteria form spatio temporally organized community
structures optimizing the growth and itness of the whole
colony which resembles a decentralized decision‑making
system of millions of interconnected nodes. Studies also
show that bacterial colonies engage in social behavior
such as competition, collaboration, and cheating during
the production of public goods [21]. Despite the
limited resources of a single bacterium, tight
coordination in the bacterial populations containing this
sheer number of bacteria can be established. Hence,
bacterial nanonetworks provide lots of clues to IoBNT
researchers that are looking to form networks of large
numbers of BNT devices with limited power and
communication resources [22, 23, 24, 25].
2.1.3 Plant networks
Among the natural IoBNTs, plant networks are the most
counterintuitive since plants seem to be immobile and
solitary. However, the growth and development of plants
are highly dependent on the communication both within
a plant itself, among different plants, and between plants
and micro organisms in soil. Although there is no physical
nervous system in plants, electrical communications have
been observed between the roots and the body of plants
[26], and capillary networks carry molecular information
to the various parts of the plant along with water and nu‑
trients. Furthermore, nearby plants use pheromone com‑
munication to coordinate their behavior to avoid over‑
growth and shadowing each other and to warn each other
against attacks from animals and bugs [27, 28]. Con‑
sidering the many species of plants in a forest, various
weed and grass on top of the soil, ivies and the trees on
which they live symbiotically, plant networks enable a
high level coordination to share the resources and opti‑
mize growth of each plant. Another element helping this
coordination is the presence of rhizobiome, i.e., the root
associated microbiome, which are shaped by the plant
signaling primary and secondary root metabolites [29].
In turn, the rhizobiome consisting of multiple species
of bacteria helps the roots to reach necessary nutrients
from the soil and protects the plant against pathogens.
This rhizobiome‑plant interaction signiicantly affects the
health and growth of the plant.
2.2 Bio‑Nano Things
In IoBNT framework, Bio‑Nano Things are deined as ba‑
sic structural and functional units operating at nanoscale
within the biological environment [1]. BNTs are expected
to have typical functionalities of the embedded compu-
ting devices in IoT, such as sensing, processing,
actuation, and communication.
To build BNTs, one approach is miniaturizing electrical
devices with nanotechnology and encapsulating these de‑
vices for biocompatibility. However, at such a small size,
miniaturized electrical BNTs suffer from lack of space for
batteries to provide suficient power and antenna
generating usable frequencies. Another approach to
build BNTs is utilizing biological units as substrates
such as cells which can be considered standalone devices
that can harvest its energy from the environment.
Another important class of BNTs is molecular and
nanomachines, which are tiny artiicial devices with fea‑
ture sizes between 1 and 100 nm, that can perform a
useful task at nanoscale [30, 31]. Recent years have ob‑
served the design and implementation of molecular and
nanomachines with increasing complexity and sophisti‑
cation, expanding the range of their applications, which
now include molecular factories, self‑propelling cargo
carriers, nanosensors, and molecular computation [32].
At a coarse‑grained level, molecular and nanomachines
can be categorized into three main groups: molecular ma‑
chines, self‑assembled nanomachines, and hybrid inor‑
ganic nanomachines.
Molecular machines are synthetic molecular systems con‑
sisting of single or a few molecules that can undergo a me‑
chanical movement upon stimulation resulting in a use‑
ful task [33]. This class of BNTs can be further divided
into two categories: molecular motors and switches.
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
Molecular motors are molecular devices, typically imple‑
mented with rotaxane‑ or catenane‑type mechanically‑
interlocked molecular architectures, that can perform
work that in turn inluences the system as a function
of trajectory with chemical, light or electrochemical
energy inputs [34, 35]. Molecular motors are
promising for biomimicking applications such as
synthesizing new molecules from individual atoms
and molecules in a programmable manner, just as
their biological counterparts, such as ribosome. On the
other hand, molecular switches reversibly change the
state of the system upon the application of
stimuli by producing no net work. Molecular
switches are being utilized for high‑resolution
molecular sensing applications and promising for
future molecular computer architectures capable of
both digital and analog computing [32].
Self‑assembled nanomachines are nanoscale devices that
are built based on autonomous or programmed organi‑
zation of constituent molecules, and can perform similar
functions to molecular machines, such as switching, logic
gating, active propulsion, typically at larger length scales
[32]. Self‑assembled DNA nanomachines have particu‑
larly attracted research interest due to the high‑level con‑
trol of their assembly through DNA origami techniques,
which enable the selective folding of DNA strands into
particular designs with the use of short staple strands [36,
37]. Selective targeting and versatile functionalization
of DNA nanomachines have expanded their application
areas, which involve bio‑inspired dynamic DNA walkers,
cargo‑carrying DNA boxes with stimuli‑responsive logic
gate‑based opening mechanisms, and stimuli‑responsive
DNA switches [38].
INTERNET
Health-care
provider
Bio-cyber
interface
Interconnected
Body-Area Nanosensor
Networks
Alzheimer & Epilepsy Monitoring
and Brain Stimulation
Nanonetworks
Heart
Monitoring
Networks
Cancer
Monitoring/
Drug Delivery
Networks
Fig. 1 – Conceptual drawing of a continuous health monitoring applica‑
tion of IoBNT.
Hybrid inorganic nanomachines are sub‑100‑nanometer
devices that can be made of metal, metal oxide or
hybrid Nanoparticles (NPs) [32]. In comparison to
self‑assembled nanomachines and molecular machines,
which involve soft biomolecular components, they tend
to be more structurally rigid, however, less biocompa-
tible. Additionally, their interaction with
external stimuli, such as light, magnetic and electric
ields, tend to be much stronger, which makes them
attractive for externally controlled applications
[32]. Janus nanomachines, which are made of Janus
Nanoparticles (JNPs), nanostructures with two
chemically distinct parts, are the most popular
inorganic nanomachines due to their anisotropic
structures that give rise to exceptional propulsion
capabilities [39]. This anisotropy results in a chemical
potential or thermal gradient in JNPs upon
chemical catalysis or external light irradiation,
which in turn, leads to the phoretic low of
surrounding luid around the entire JNP surface. As a
result of this phoretic low, JNPs actively move in the
opposite direction. There are also proposed
architectures of self‑propelled Janus nanomotors wor‑
king based on the decomposition of hydrogen
peroxide into oxygen as a driving force. Moreover,
the use of mesoporous silica nanoparticles (MSNs)
as JNPs has opened up new biomedical opportunities
which involve the targeted delivery and contro-
lled release of therapeutic and diagnostic agents
encapsulated in their porous structure [40]. Although
much has been done to devise exquisite and
complex molecular and nanomachine architectures
that can perform sensing, cargo transport, and
switching operations, the potential of intercon-
necting these tiny machines for a wider range of
biomedical applications has only recently
attracted signiicant attention. Seveeral commu-
nication modalities have already been
considered to enable controlled interaction
and coordination of these devices, such as
diffusion‑mediated communication, which is based on
the exchange of small molecules, e.g., glucose, through
the signaling cascades triggering enzymatic reactions
that fuel the movement of the receiver devices, and cell
or cell‑free genetic circuits that trigger the
expression of a certain kind of protein, e.g.,
green luorescent protein (GFP), in the receiver
BNTs [41, 42, 43, 44]. External energy‑
mediated communications have also been widely
studied to enable the small networks of
molecular and nanomachines. This form of interac‑
tion occurs through several biophysical phenomena,
such as pore formation and modulation of enzyme
cascade re‑ actions, which are triggered by external
stimuli such as light, chemicals, temperature, and
electric and magnetic ields, and provides higher level
of spatiotemporal control compared to the
diffusion‑mediated communication [41]. Non‑covalent
interactions considered for molecular and nano-
machines involve the short‑range electrostatic and
hydrophobic/hydrophilic interactions, as well as
complex formation through reversible ligand‑receptor
binding interactions. Lastly, inducing dynamic collective
behaviors of active nanomachines, such as Janus
nanomachines, through external stimuli, e.g., light,
electric and magnetic ields, has also attracted great
attention due to their emergent out‑of‑equilibrium
properties resembling natural systems [45, 46, 47].
Incorporation of these interacting molecular and
nanomachines into the larger IoBNT framework as
heterogeneous BNTs can enable unpre-
cedented therapeutic and diagnostic applications via
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
exquisite external, distributed, or programmed control
with high spatiotemporal resolution.
2.3 IoBNT Applications
The IoBNT will enable a plethora of applications in many
ields where the connection of biological entities and na-
nodevices to the Internet leads to unprecedented
ways of interfacing with biology due to IoBNT’s
inherent biocompatibility, reduced invasiveness, and
low power consumption. In the rest of this section, we
discuss the potential of IoBNT in biomedical applications,
smart agriculture, and environmental applications.
2.3.1 Biomedical Applications
The most promising applications of IoBNT are envisioned
to be in the biomedical ield where IoBNT would play a
crucial role in healthcare. IoBNT comprising nanonet‑
works of biosensors and actuators operating near, on, or
in the body, will enable real‑time remote monitoring and
control of patients’ health.
A nanosensor network deployed in cardiovascular sys‑
tem monitoring vital signs such as heart rate, blood pres‑
sure, EEG signals, and blood oxygen and carbon dio-
xide levels may reveal abruptly occurring diseases such
as heart attack and automatically alert healthcare
providers. Meanwhile, continuous long‑term monitoring
of these vital signs may be used for management of
chronic diseases as well as data collection to predict
future attacks. Recently, researchers also considered
applying IoBNT concept for detection and mitigation
of infectious diseases [15] where bio‑hybrid BNTs
constantly monitors for biomarkers released by
infectious microorganisms. Other biomarkers that would
be interesting to monitor by IoBNT would be glucose. A
sudden changes in glucose levels can be deadly for
diabetic patients, IoBNT can alert the patient against
low/high glucose levels and can help adjust precise and
timely administration of insulin automatically. Similarly,
IoBNTs can be used for hormonal therapy management
in cancer treatments or hormone replacement
therapies in sex change [48].
Besides monitoring applications, IoBNT can also lead the
realization of next generation smart drug delivery appli‑
cations. To spare the non‑target organs and tissues from
the side effects of drugs, BNTs can deliver medicine to tar‑
geted regions in human body. BNTs encapsulating drug
molecules can either actively search for or be directed ex‑
ternally to target cells and release the drugs only on target
location.
2.3.2 Smart Agriculture
Humans are not the only organisms that can beneit from
remote health monitoring with IoBNT. The health of ani‑
mals such as cattle and poultry can be also interrogated by
IoBNT to ensure the health of the animals and the quality
of their products such as meat, milk, and eggs. Another
beneit of IoBNT to agriculture would be through moni‑
toring of plants by measuring their health through BNTs
deployed on the plants or in the soil. This can be also
supported by BNTs monitoring and controlling smart irri‑
gation systems, actively fertilizing the soil, and deterring
bugs and wildlife damaging crops.
2.3.3 Environmental Applications
Another promising area for IoBNT applications is envi‑
ronmental monitoring. By deploying IoBNT networks in
water supply and distribution systems, it might be possi‑
ble to detect pollutants in the water and use nano‑ilters
to remove harmful substances and toxic agents contained
in it. A similar system can be deployed to combat air pol‑
lution in crowded cities. Another environmental appli‑
cation can be listed as handling the growing problem of
waste management where IoBNTs can be used to sort and
process waste. Nanosensors can sense and tag different
materials and nanoactuators can biodegrade the tagged
materials or alert service providers to remove potentially
toxic waste that might pollute water or soil.
3. CHALLENGES
3.1 Communication Methods for IoBNT
Conventional forms of electromagnetic (EM) communi‑
cations are deemed not suitable for connecting BNTs,
mainly due to the antenna size limitations, biocompati‑
bility concerns, and the severe attenuation of EM sig‑
nals in physiological media relevant for IoBNT applica‑
tions [1]. Because of these challenges, researchers have
started a quest for alternative communication methods
to extend our connectivity to nanoscales. We can clas‑
sify the proposed nanocommunication methods into two
main types: (i) Molecular communications (MC), (ii) THz‑
band EM. Other techniques based on magnetic coupling,
Fö rster Resonance Energy Transfer (FRET), heat trans‑
fer and acoustic energy transfer have also been proposed
for nanonetworks. In the rest of this section, these tech‑
niques will be briely overviewed, with a particular fo‑
cus on MC, which is considered as the most promising
nanocommunication method to enable IoBNT.
3.1.1 Molecular Communications
Molecular communications is a bio‑inspired communica‑
tion technique, that uses molecules to transfer informa‑
tion. More speciically, a physically distinguishable fea‑
ture of molecules, such as their type and concentration, is
used to encode information, and random molecular mo‑
tion in a luidic channel is exploited as a means of sig‑
nal propagation for information transfer. MC is radically
different from conventional communication paradigms,
e.g., EM communications, in various aspects such as the
size and type of network entities, information transmis‑
sion mechanisms, noise sources and fundamental per‑
formance limits including transmission delay, achievable
data rates, coverage and power consumption.
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
Example MC scenarios between pairs of nanomachines
are depicted in Fig. 2, where the messages are encoded
into the concentration of molecules, and then transmit‑
ted to the receiver via molecular propagation in a luidic
channel. The information can also be encoded into the
type, release time, or the electronic state of the molecules
[8]. Different kinds of propagation methods for mole-
cular messages are investigated in the literature, such
as passive diffusion, active transport with molecular
mo‑ tors [49], convection, and transport through gap
junctions [50]. Among these, passive diffusion is the
most promis‑ ing, as it does not require energy
consumption, and thus perfectly suits the energy
limitations of the envisioned nanomachines.
Transmitter MC Channel Receiver
Transmitted
Signal
Received
Signal
Engineered Bacteria-based
Biological MC-Transceivers
Information
Molecules
Electrical Stimuli-responsive
Hydrogel/Graphene MC Transmitter
Graphene Biosensor-based
MC Receiver
Information
Molecules
Fig. 2 – Components of an MC system with biological and nanomaterial‑
based MC transmitter and receiver design approaches.
MC channel has many peculiar characteristics. For
example, the discrete nature of information carriers,
i.e., molecules, results in molecular counting noise, which
is of similar nature with the shot noise occurring in
photonic devices [51]. The stochastic nature of the
ligand‑receptor binding process occurring at the receiver
gives rise to colored noise, also leading to a strong
correlation between molecular propagation process and
reception [52]. The slow nature of diffusion leads to a
substantial amount of channel memory, which in turn,
causes severe inter-symbol interference (ISI), and limits
the achievable data transmission rates [53]. The same
reason also causes a signiicant delay in the
transmission [54].
Deviations from the conventional means of communica‑
tions necessitate radically different ideas for the design
of transmitter and receiver architectures, and communi‑
cation techniques for MC, and new approaches to channel
modeling.
a) Transmitter and Receiver Architectures for MC:
There are mainly two design approaches considered for
artiicial nanomachines that can perform MC and form
MC nanonetworks within the IoBNT framework. The
irst approach is to build the components of nanoma‑
chines using newly discovered nanomaterials, such as
two‑dimensional graphene, and one‑dimensional silicon
nanowire (SiNW) and carbon nanotube (CNT), which all
manifest extraordinary characteristics at the interface of
biology and electronics [55]. The other approach re‑
lies on synthetic biology, and envisions the use of en‑
gineered, i.e., genetically modiied, bacteria as artiicial
nanomachines with communication functionalities wired
into their intracellular signaling networks [24].
The physical nature of the BNTs determines the potential
transmitter and receiver architectures. The MC transmit‑
ter of a BNT should perform the modulation of MC signals,
and the release of molecules into the channel upon a sti-
mulation by an external source, or as a result of an
internal biochemical or electrical process. The receiver
of a BNT is responsible for detecting the incoming
molecular mes‑ sages, transducing them into a
processable signal, and extracting the encoded
information through signal processing. The decoded
information can then be used by the BNT to perform a
prescribed operation, e.g., modulation of gene
expression or translocation. Therefore, the per‑
formance of the transmitter and receiver is critical for the
proper operation of a BNT within an IoBNT application.
Nanomaterial‑based design approaches for MC transmit‑
ter mainly draw on the existing drug delivery technolo‑
gies, such as stimuli‑responsive hydrogels, molecule re‑
lease rate of which is controlled by an electrical or
chemical stimuli. Synthetic biology‑based approaches,
on the other hand, rely on making use of the already
existing molecule release mechanisms of living cells,
and tailoring these functionalities through genetic
modiications to realize the desired MC modulation
schemes. There are also theoretical MC transmitter
designs that exploit stimuli‑responsive ion channels to
trigger the release of molecules in an externally
controllable fashion [56]. Nanomaterial‑based receiver
designs are widely inspired by nanobiosensors, which
share a common objective with MC receivers, that is to
transduce biomolecular signals into a signal form
suitable for processing. Although there are many
nanobiosensor designs differing in their transducing
mechanisms and the resulting signal form at the output,
ield‑effect‑transistor (FET)‑based nanobiosensors
have attracted the most attention for MC receiver
design due to their scalability, simple design similar to
conventional FETs, internal signal ampliication by elec‑
trical ield‑effect, label‑free operation, and the electri‑
cal output signals that allow fast processing of received
signals. More importantly, FET‑based nanobiosensors
provide a wide range of design options. For example,
they can accommodate different types of nanomaterials,
e.g., graphene, SiNW, CNT, as the transducer channel,
the conductivity of which is modulated by the molecu‑
lar concentration in its proximity through the alteration
of the surface potential and electrical ield‑effect. FET‑
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
based nanobiosensors have also a biorecognition layer,
which replaces the gate electrode in conventional FETs,
and consists of receptor molecules selectively binding tar‑
get molecules via afinity‑based ligand‑receptor interac‑
tions. Depending on the transducer channel material, the
biorecongition layer can host a wide range of receptor
molecules, ranging from proteins to DNAs.
Among other options, graphene FET (GFET) biosensors
provide unique advantages for the practical design of MC
receiver. The main advantage of graphene is its high sen‑
sitivity to the charged analytes, e.g., proteins and DNAs,
due to its extremely high carrier mobility and one‑atom
thickness, exposing all its atoms to the environment. The
advent of new types of receptors, e.g., aptamers, has
broadened the target range of nanoscale FET biosensors
from ions to proteins, peptides, and even whole cells.
Aptamers are short functional oligonucleotides (typically
20‑60 nucleotides). Their base sequences for speciic tar‑
gets are identiied from an oligonucleotide library with
an in vitro process called systematic evolution of ligands
by exponential enrichment (SELEX). Their application
in biosensors has gained momentum due to their wide
target range, chemical stability, and ease of production.
Combined with the exceptional properties of graphene
and aptamers, the ability of nanoscale FET biosensors
to provide selective, label‑free and continuous detection
makes GFET aptamer‑based biosensors, i.e., GFET ap‑
tasensors, very promising candidates for the design of MC
receiver.
Biological MC receiver designs are based on the enhance‑
ment of biosensing and biochemical signal processing
functionalities of livings cells with synthetic biology tools
for the receiver operation. This approach consists in the
design of new synthetic receptors that can provide more
sensitivity and selectivity in physiological environments,
for example, through kinetic proof reading mechanisms
[57], and the implementation of new chemical reaction
networks within the cell that can realize the required
computations for decoding the received MC signals. Syn‑
thetic biology is already mature enough to allow perfor-
ming complex digital computations, e.g., with networks
of genetic NAND and NOR gates, as well as analog
computations, such as logarithmically linear addition,
ratiometric and power‑law computations, in synthetic
cells [58]. Synthetic gene networks integrating
computation and memory is also proven feasible [59].
More importantly, the technology enables
implementing BNTs capable of ob‑ serving individual
receptors, as naturally done by living cells. Hence, it
stands as a suitable domain for practi‑ cally
implementing more information‑eficient MC detec‑ tors
based on the binding state history of individual re‑
ceptors.
b) MC Channel Modeling: To design effective and efi‑
cient MC systems addressing the needs of the envisioned
IoBNT applications, it is important to have a theoretical
framework which can be used to optimize the physical
components of the system with ICT performance met‑
rics. Because of this, there has been tremendous inte-
rest in modeling the MC channels to ind the ultimate
performance limits in terms of information theoretical
capacity and data rate. In majority of studies, MC
channel is usually assumed to be unbounded where
information‑carrying molecules propagate through free
diffusion with the underlying phenomenon of
Brownian motion [60, 61]. In a few studies,
diffusion is accompanied by a low which directs the
propagating molecules to a distant receiver [62, 63, 64],
whereas some studies also consider the existence of
reactive molecules within the channel which can
chemically degrade the information carrier molecules
and reduce the intersymbol interference. A few studies
consider bounded MC channels, for example mi‑
croluidic channels where molecules propagate through
convection‑diffusion. In majority of these studies, it is
assumed that the molecules are transmitted from a hy‑
pothetical point source, which is capable of releasing a
known number of molecules to the channel in the form
of an impulse signal at a given time instant. On the other
hand, the receiver is typically assumed to be a transpa-
rent instrument, which is capable of counting every
single molecule in a hypothetically deined space [63],
or an ideal absorbing instrument capable of counting
each molecule that is absorbed [65]. Common to these
studies is the ignorance of the impact of the physical
architectures of the transmitter and receiver on the
communication channel. As such, researchers have been
able to adopt the EM‑inspired simpliications in
modeling, such as linear and time‑invariant (LTI)
channel characteristics with additive white Gaussian
noise, neglecting the effects of interactions and
correlations resulting from transmitter and receiver
architectures and channel geometry. This leads to a
serious discrepancy between theory and practice, as
revealed by the initial MC experiments performed with
‘macroscale’ sensors and dispensers utilized as MC
transmitter and receiver, respectively, showing that the
nonlinearity and time‑variance caused by the operation of
transmitter and receiver invalidate the models built upon
these assumptions [66, 67].
On the other hand, some research groups have studied
MC receivers that rely on ligand‑receptor binding reac‑
tions, the common molecular sensing method in natural
MC [68, 69]. Deterministic models, assuming free diffu‑
sion and point transmitter, have been developed for a vir‑
tual MC receiver with ligand receptors. Although the con‑
sideration of ligand receptors has advanced the accuracy
of the models one step further, the employed assump‑
tions about the transmitter and channel strictly limit the
applicability of these models. Additionally, stochastic
receiver models are developed for FET nanobiosensor‑
based MC receivers [69]. In [62], a model for MC with 2D
biosensor‑based receivers in microluidic channels is
provided. However, these initial models also rely on
unrealistic assumptions, e.g., equilibrium conditions in
ligand‑receptor binding reaction, and ignore the
implications of the receiver geometry.
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
Therefore, there is still a need for a bottom-up physical
modeling approach originating from irst principles, cap‑
turing all interactions in practical transmitter, channel
and receiver architectures, causing nonlinear and
time‑varying behavior and unconventional noise and
interference that may have decisive impacts on the
development of MC techniques for IoBNT.
c) Experimental MC System Testbeds and
Practical Demonstrations: Testbeds are crucial for
validating theoretical models, and practically
evaluating the performance of new communication
techniques. However, research for building expe-
rimental MC systems has just recently gained
momentum. Few studies in MC literature have focused
on ‘macroscale’ implementation of MC systems with
off‑the‑shelf components. For example, in [66, 70], the
isopropyl alcohol (IPA) is used as airborne in‑
formation carriers, and commercially available metal
oxide semiconductor alcohol sensors are used as the
MC receiver. The transmission of molecules is
realized by electrically‑controlled spray nozzles. In
[71], the information is encoded in pH level of the
transmitted luid instead of molecular concentration or
type. The acidic and basic luids are injected into
off‑the‑shelf lexible tubes via peristaltic pumps, and a
macroscale pH meter is used as the MC receiver. In
another testbed [67], magnetic nanoparticles (MNs)
are employed as information carriers, which are
injected into off‑the‑shelf mm‑scale lexible tubes by
low pumps, and propagate through convection and
diffusion. In this study, for the detection of messages
encoded into MN concentration, the authors designed
bulky detector coils placed around the tubes coupled
with capacitors to form a resonator circuit, which
informs about the concentration through a change in in‑
ductance and shift in resonance frequency. In this imple‑
mentation, the designed receiver acts only as an
observer, and does not physically interact with the
information carrier molecules. The focus of the
aforementioned studies is on macroscale MC using
commercially available channels, and off‑the‑shelf
sensors or bulky detectors as receivers that are not
physically relevant for the application domain of MC and
IoBNT.
Recently, the irst micro/nanoscale demonstration of an
MC system is reported in [72]. In this study, the au‑
thors provide the results of MC experiments using a
custom‑made microluidic testbed with a graphene FET
DNA biosensor‑based MC receiver integrated into a mi‑
croluidic channel. A commercially available microluidic
low control system is used to pump single‑stranded
DNA (ssDNA) molecules of different molecular
concentrations into the microluidic channel. Graphene
transducer chan‑ nel of the receiver functionalized with
complementary ss‑ DNAs transduces the real‑time
concentration of the propagating DNA molecules into
electrical signals, which are then used for detection.
The authors of the study report nM‑level sensitivity and
single‑base‑pair‑mismatch selec‑ tivity for the receiver.
However, they also note the very low communication
rates on the order of 1 bit/minute, mainly resulting
from the slow association-dissociation kinetics of DNA
hybridization.
Biological MC testbeds have also been reported by many
research groups. For example, in [73] and [74],
authors implement a microluidic MC testbed with
genetically en‑ gineered Escherichia coli (E. coli)
bacteria acting as receiver nanomachines. The
bacteria in these studies have been engineered to
respond to certain biomolecules, e.g., N‑(3‑Oxyhe-
xanoyl)‑L‑homoserine lactone (C6‑HSL) and N‑Acyl
homoserine lactone (AHL), by expressing green
luorescent proteins (GFP), which can later be detected
via luorescent microscopy upon excitation with light
of certain wavelengths. Both studies report extremely
low communication rates on the order of 1 bit/hour
due to the lengthy process of gene expression required
for each bit transmission. In [75], the authors prefer
a different approach by exploiting the
light‑responsive proton pump gloeorhodopsin (GR)
located in the bacterial membrane to obtain
an optically controlled MC transmitter that can
export protons into the luidic channel upon the
application of external light stimuli. Accordingly,
protons are used as information carriers, which
propagate through structural diffusion in water, and
are detected by a pH sensor acting as the receiver.
Using this testbed, the authors report commu-
nication rates on the order of 1 bit/
minute. Although biological designs have been
demonstrated individually for both MC transmitter
and receiver, there is yet to be any practical
implementation of an entirely biological testbed
for end‑to‑end MC.
d) Development of MC Techniques: The unconven‑
tional characteristics of MC, such as discrete nature of
information carriers and slow nature of propagation
mechanisms, which bear no similarity to conventional
EM communications, lead to various challenges, such as
high channel memory causing severe ISI, non‑Gaussian
noise sources, time‑variance, and very low communica‑
tion rates, as revealed by several theoretical investiga‑
tions [62, 13]. The initial experimental studies performed
on both macro‑ and micro‑scales also demonstrated the
high level of nonlinearity mainly resulting from the cha-
racteristics of sensors utilized as receivers [66, 70,
72]. One can expect that practical MC system
implementations for IoBNT applications may face many
more challenges, such as molecular interference due to
existence of different types of molecules in the channel,
environmental luctuations, such as those in low
velocity and temperature, ionic screening in
physiologically relevant environments preventing the
receiver from detecting the electrical charges of
information molecules, and new noise sources such as
electronic 1/f noise in nanomaterial‑based MC
receivers. Therefore, MC requires new com‑
munication methods that account for these peculiarities,
and overcome their detrimental effects on the communi‑
cation performance. Considering physical limitations of
the envisioned BNTs, these techniques should be also low‑
complexity and low‑energy, i.e., low‑molecule‑use.
We summarize some of the major problems stemming
from the limitations associated with the physical proper‑
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
ties of the MC channel, transmitter and receiver architec‑
tures as follows:
•Intersymbol Interference (ISI): Due to the slow na‑
ture of molecular diffusion in MC channel, severe
ISI occurs in both forward and backward direction,
which is the main factor limiting the communication
rate. The effect of ISI is less pronounced in low‑
based MC channels; however, the slow reaction ki‑
netics at the receiver surface might compound the
ISI, as revealed in [72]. Therefore, MC techniques
should account for ISI, either removing it or redu-
cing its effects.
•Nonlinearity and Time‑variance: The nonlinearity
of the MC system results from the nonlinear trans‑
mission and propagation dynamics, and the reaction‑
based receiver mechanisms. On the receiver side,
in particular, the saturation of the receiver could
have substantial effect on the detection performance.
Therefore, the developed modulation and detection
techniques should account for nonlinearity. Time‑
variance can result from the luctuations in the low
conditions, as well as from the time‑varying molecu‑
lar interference level in the channel.
•Molecular Interference: The existence of other
molecules in the MC channel can originate from an ir‑
relevant biological process, or another MC system co‑
existing in the same channel. The interference
manifests itself on the receiver side, as the
selectivity of receptors against information
molecules is far from ideal in practice, and thus,
many different types of molecules having inite
afinity with the receptors, could also bind the
same receptors, resulting in considerable
interference at the received signal. To overcome this
problem, new detection methods exploiting the
frequency‑domain characteristics of the receiver
reaction and transducing processes can be de‑
veloped to increase the selectivity [57]. Moreover,
the receptor cross‑talk resulting from multiple types
of molecules can be exploited to develop new modu‑
lation techniques to boost the communication rate.
•Noise: In addition to particle counting noise and
ligand‑receptor binding noise, which are well inves‑
tigated in the MC literature, the physical architecture
of the receiver can lead to new noise sources. For
example, in nanomaterial‑based designs, thermal
noise and electronic noise, e.g., 1/f noise, of the
receiver can be expected to severely undermine the
reliability of communication.
•Ionic Screening: One of the main problems parti-
cularly observed at FET biosensor‑based receivers
is the ionic screening in physiologically relevant
luids, which decrease the SNR tremendously. The
ions in the channel luid can cause the screening of
electrical charges of information molecules,
resulting in reduced effective charge per molecule
that can be detected by the receiver via ield‑effect.
The strength of ionic screening depends
exponentially on the distance of bound information
molecules from the surface of the receiver’s
transducer channel. Numerous solutions exist in
the biosensing literature that partially overcome
this widely‑observed problem. For example, using
small‑size receptors, e.g., aptamers, can allow the
bound information molecules to approach the
receiver surface, increasing their effective charge
[76, 77]. Alternatively, high‑frequency AC biasing at
the receiver, exploiting the oscillating dipole
moments of the bound information molecules, can be
employed to overcome the ionic strength in exchange
for increased complexity on the receiver side [78].
•Low Communication Rate: Slow diffusion and re‑
action kinetics of molecules might result in very low‑
communication rates, as shown in some of the recent
practical MC demonstrations. These physical limi‑
tations call for new modulation and detection tech‑
niques that simultaneously exploit multiple proper‑
ties of molecules, e.g., concentration and type, to
boost the communication rate for MC systems.
Modulation techniques in MC fundamentally differ from
that in conventional EM communications, as the mo-
dulated entities, i.e., molecules, are discrete in
nature, and the developed techniques should be robust
against highly time‑varying characteristics of the MC
channel, as well as inherently slow nature of the
propagation mechanisms [8]. Exploiting the observable
characteristics of molecules, researchers have proposed
to encode information into the concentration, type, or
release time of the molecules [13, 79]. The simplest
modulation method proposed for MC is on‑off keying
(OOK) modulation, where a binary symbol is
represented by releasing a number of molecules or
not releasing any [80]. Similarly, using a single type
of molecule, concentration shift keying (CSK), that is
analogous to amplitude shift keying (ASK) in traditional
wireless channels, is introduced in order to increase the
number of transmitted symbols by encoding
information into molecular concentration levels [81].
Molecular information can also be encoded into the type
of molecules, i.e., molecule shift keying (MoSK) [79], or
into both the type and the concentration of molecules to
boost the data rate [82]. Additionally, the release order
of different types of molecules [83], and the release time
of single type of molecules [84] can be modulated to en‑
code information in MC. Finally, in [85], authors propose
the isomer‑based ratio shift keying (IRSK), where the in‑
formation is encoded into the ratio of different types of
isomers in a molecule, i.e., molecule ratio‑keying.
To overcome the noisy and ISI‑susceptible nature of MC
channels, several channel coding techniques which are
adopted from EM communications, e.g., block and con‑
volution codes, or developed speciically for MC, such
as the ISI‑free coding scheme employing distinguishable
molecule types, have been studied. Detection is by far
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
the most studied aspect of MC in the literature.
Several methods varying in complexity have been
proposed to cope with the ISI, noise, and even the
nonlinearity of the channel, such as optimal
Maximum Likelihood (ML)/Maximum A Posteriori
(MAP) detection methods, noncoherent detection,
sequence detectors with Viterbi algorithm [86, 87, 63,
88, 13]. Synchronization problem is addressed by both
developing self‑synchronizing mod‑ ulation techniques
and asynchronous detection methods. However, these
methods are developed based on existing theoretical
models of MC, which largely lack physical
correspondence. Therefore, the performance of the
proposed methods is not validated, which poses a major
problem before practical MC systems and IoBNT applica‑
tions.
3.1.2 Human Body as IoBNT Infrastructure
MC can typically support only very low communication
rates due to the slow diffusion dynamics of molecules.
Moreover, MC is prone to errors because of high level of
noise and molecular interference in crowded physiologi‑
cal media, as well as due to attenuation of molecular sig‑
nals as a result of degradation via various biochemical
processes, making it reliable only at very short ranges [8].
On the other hand, human body has a large‑scale complex
communication network of neurons extending to various
parts of the body and connecting different body parts
with each other through electrical and chemical signaling
modalities [4]. A part of the nervous system also senses
external stimuli via sensory receptors and transmits the
sensed information to the central nervous system, where
a reaction is decided [5]. In that regard, the nervous sys‑
tem provides a ready infrastructure that can potentially
connect nanomachines in distant parts of the body with
each other and with the external devices. In fact, there
are many proposal in this direction that both theoretically
and experimentally investigate the idea of using the ner‑
vous system as an IoBNT backbone inside human body.
In [89], authors consider a thru‑body haptic communi‑
cation system, where the information encoded into tac‑
tile stimulation is transmitted to the brain through the
nervous system, resulting in a discernible brain activity
which is detected by ElectroEncephaloGraphy (EEG) and
used to decode the transmitted information. An analyti‑
cal framework based on the computational neuroscience
models of generation and propagation of somatosensory
stimulation from skin mechanoreceptors is developed for
the analysis of the achievable data rate on this communi‑
cation system. Authors show that the system can support
bit rates of ‑ bit per second (bps) employing an OOK
modulation of tactile stimulation taps at the index inger.
In [90], the authors practically demonstrate a controlled
information transfer through the nervous system of a
common earthworm, which stands as a simple model
system for bilaterian animals including humans. In the
demonstrated setup, authors use external macroscale
electrodes to interface with the earthworm’s nervous
system. Accordingly, the stimulation carrying the en‑
coded information is applied at one end of the nerve
cord, and the resulting nerve spikes are recorded at the
other end. Through the application of different modu‑
lation schemes, e.g., OOK, frequency shift keying (FSK),
the authors demonstrate data rates up to bps with
bit error rate.
In [91], the authors propose to use vagus nerve to deliver
instructions to an implanted drug delivery device near the
brainstem via compound action potentials (CAP) gene-
rated by the application of electrical impulses at the
neck, known in the literature as the vagus nerve
stimulation (VNS). Applying an OOK modulation, the
authors theoretically show that the vagus nerve can
support data rates up to bps and unidirectional
transmission ranges between mm and mm,
which is promising for enabling the communication of
distant BNTs at a rate that is much higher than the
typical MC rates.
A different approach to make use of the natural hu‑
man body networks for IoBNT is investigated in [92],
where authors propose to use Microbiome‑Gut‑Brain‑
Axis (MGBA) to connect distant BNTs. MGBA is a large
scale heterogeneous intrabody communication system
composed of the gut microbial community, the gut tis‑
sues, and the enteric nervous system. In MGBA, a bidirec‑
tional communication between the central nervous sys‑
tem and the enteric nervous system surrounding the gas‑
trointestinal track (GI track) is realized via the transduc‑
tion of electrical signals in the nervous system into mole-
cular signals in the GI track, and vice versa. The axis
has recently attracted signiicant research interest due to
the discoveries underlining the relation of MGBA
signaling with some neurological and gut disorders
such as depression and irritable bowel syndrome
(IBS). In the research roadmap proposed in [92], the
authors envision BNTs as electrical biomedical devices,
e.g., cardiac pacemaker, brain implants, insulin pumps,
and biological devices, e.g., synthetic gut microbes and
artiicial organs, interconnected through the MGBA. They
also investigate the possibility of a link between the
IoBNT and the external environment via molecular
(alimentary canal) and electrical (wireless data transfer
through skin) interfaces.
3.1.3 Other Nanocommunication Modalities for
IoBNT
a) THz‑band Electromagnetic Nanocommunication:
Conventional electromagnetic (EM) communication is
not deemed suitable for IoBNT because the size of BNTs
would demand extremely high operating frequencies
[93]. Fortunately, graphene‑based nanoantennas based
on surface plasmon polariton (SPP) waves have been
shown to support frequencies down to 0.1 THz, much
lower than their metallic counterparts, promising for
the development of high‑bandwidth EM nanonetworks
of nanomaterial‑based BNTs using the unutilized THz‑
band (0.1‑10 THz) [94]. In this direction, several plas‑
monic transceiver antenna designs using graphene and
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
related nanomaterials (e.g., CNT), whose properties can
be tuned by material doping and electric ield, have been
investigated [95, 96]. However, several challenges exist
for the practical implementation of THz‑band nanonet‑
works, such as the very limited communication range re‑
sulting from high propagation losses due to molecular ab‑
sorption, and low transmission power of resource‑limited
nanodevices. These challenges are being addressed
by developing new very‑short‑pulse‑based modulation
schemes to overcome the limitations of THz transceivers
in terms of power [97, 98], and designing directional an‑
tennas and dynamic beamforming antenna arrays to over‑
come the propagation losses [99]. High density of BNTs
in envisioned IoBNT applications also pose challenges re‑
garding the use of the limited spectrum, which are ad‑
dressed by new medium access protocols for dense THz
nanonetworks [100, 101].
b) Acoustic Nanocommunication: Ultrasonic nanocom‑
munication has also been considered for connecting
robotic BNTs inside the luidic environment of human
body due to its well‑known advantages over its RF coun‑
terpart in underwater applications [102, 103, 104]. In
[102], it is shown that the best trade‑off between eficient
acoustic generation and attenuation is realized when the
acoustic frequency is between MHz and MHz for
distances around m. The authors also show that the
power harvested from ambient oxygen and glucose can be
suficient to support communication rates up to bps.
In [105], the authors provide a testbed design for ultra‑
sonic intrabody communications with tissue‑mimicking
materials and as a result of extensive experiments, they
report communication rates up to kbps with a BER
less than .
An alternative approach proposed in [106] suggests the
use of optoacoustic effect for the generation and detection
of ultrasonic waves via a laser and an optical resonator,
respectively. It is shown that optoacoustic transduction
brings multiple advantages for ultrasonic nanocommuni‑
cations, such as higher miniaturization, bandwidth and
sensitivity over traditional piezoelectric/capacitive trans‑
duction methods.
c) FRET‑based Nanocommunication: Single molecular
BNTs are not capable of performing active communica‑
tions, as in the case of MC and THz‑band EM communi‑
cations. On the other hand, external stimuli can supply
the necessary means of information transfer. One such
method is based on Fö rster Resonance Energy Transfer
(FRET), which is a non‑radiative and high‑rate energy
transfer between luorescent molecules, such as luores‑
cent proteins and quantum dots (QDs) [107]. The method
requires an external optical source for the initial excita‑
tion of donor molecules, which then transfer their
energy to ground‑state acceptor molecules in their
close proximity. Encoding information into the excited
state of molecules, short‑range (5‑10 nm) but very
high‑rate (on the order of Mbps) information transfer
can be realized by this method [108]. Additionally,
bioluminescent molecules can be utilized as donors that
are excited upon binding speciic target molecules,
promising for single molecular sensor networks within
an IoBNT application [109, 110]. It is shown that the
limited range of FRET‑based nanocommunication can be
extended to 10s of nanometers by multi‑step energy
transfer processes and multi‑excitation of donor
molecules [111, 112]. Lastly, an experimental study
demonstrated a high rate data transfer (250 kbps with a
BER below ) between luorescent‑dye
nanoantennas in a MIMO coniguration [113].
3.2 Bio‑Cyber and Nano‑Macro Interfaces
Most of the envisioned IoBNT applications require a
bidirectional nano‑macro interface that can seamlessly
connect the intrabody nanonetworks to the external
macroscale networks, and vice versa [114, 115]. Consi-
dering that the MC is the most promising method for
intrabody IoBNT, the interface should be capable of
performing the conversion between biochemical signals
and other signal forms that can be easily processed and
communicated over conventional networks, such as
electromagnetic, electrical, and optical. Several
techniques are considered for enabling such a
nano‑macro interface.
3.2.1 Electrical Interfaces
These are the devices that can transduce molecular sig‑
nals into electrical signals, and vice versa. Electrical
biosensors can readily serve the function of converting
MC signals into electrical signals (see Section 3.1.1 for the
use of electrical biosensors as MC receivers). The litera‑
ture on biosensors is vast, and the irst practical demon‑
stration of graphene bioFET‑based MC receiver shows
promising results in terms of sensitivity, selectivity, and
reliability in electrical detection of MC signals [72]. How‑
ever, challenges posed by physiological conditions should
be overcome before employing biosensors as electrical in‑
terfaces, as detailed in [55, 13]. Conversion from electri‑
cal signals into molecular signals is more challenging due
to the problem of maintaining continuous molecule
generation or supply. Existing electrical
stimuli‑responsive drug delivery systems rely on
limited‑capacity reservoirs or polymer chains, e.g.,
hydrogel, that can store certain types of molecules and
release them upon stimulation with a modulated rate.
However, these systems are typical irreversible, i.e., they
cannot replenish their molecular stock unless they are
replaced or reloaded externally [13]. In [116], a
redox‑based technique is proposed and practically
demonstrated for interfacing biological and electronic
communication modalities, which can be used to
connect a conventional wireless network with en‑
gineered bacterial BNTs communicating via molecu‑
lar signals. The authors introduced the concept of
electronically‑controlled biological local area network
(BioLAN), which includes a biohybrid electrode that
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
transduces information‑encoded electronic input signals
into biologically‑recognized signals in the form of hy‑
drogen peroxide through an oxygen reduction reaction.
These signals are recognized by bacterial cells that are at‑
tached to the biohybrid electrode, and then biologically
propagated across a microbial population with quorum
sensing molecules. The overall electronic‑biology link is
bidirectional such that a microbial subpopulation in the
BioLAN generates speciic molecules that can be detected
by the electrode via an electrochemical oxidation reac‑
tion.
Wearable and epidermal tattoo biosensors and transder‑
mal drug‑delivery systems, which have attracted a sig‑
niicant research interest for various healthcare applica‑
tions, can also be targeted for an macro‑nano interface
that can connect intrabody IoBNT to the external commu‑
nication networks, with the integration of communication
antennas, such as radio‑frequency‑identiication (RFID)‑
tag‑antennas [117, 118, 119, 120]. The challenges lie in
the further miniaturization of these devices as well as
their continuous operation, since biosensors exposed to
physiological luids suffer contamination, and drug de‑
livery systems require periodic replenishment of their
reservoir.
3.2.2 Optical Interfaces
Light represents an alternative modality to interface the
intrabody IoBNT with external networks. In the case that
MC is utilized in IoBNT, such an optical interface can be
realized with the help of light‑sensitive proteins and bio‑
luminescent/luorescent proteins.
Optical control of excitable cells, e.g., neurons and mus‑
cle cells, can be achieved through a well‑known technique
called optogenetics [121]. The method relies on the ge‑
netic modiication of natural cells for enabling them to
express light‑sensitive transmembrane ion channel pro‑
teins, e.g., channelrhodopsin. The resulting light‑sensitive
ion channels open or close depending on the wavelength
of the incident photons. The technique enables speciicity
at the level of single cells in contrast to conventional elec‑
trical interfacing techniques, which generally suffer from
low level of speciicity. It is shown in [122, 123] that
bacteria can also be engineered to express speciic light‑
sensitive proteins, e.g., bacteriorhodopsin, that pump out
protons under illumination, and thus, change the pH of its
close environment.
In [56], the authors propose that optical control of engi‑
neered cells with light‑sensitive ion channels can be ex‑
ploited to enable an optical macro‑to‑nanoscale interface
that can modulate the molecular release of MC transmit‑
ters. The authors in [124], experimentally demonstrate
that synthetic bacteria expressing bacteriorhodopsin can
convert external optical signals to chemical signals in the
form of proton concentration at bit/min conversion
rate. They use the same technique to enable an expe‑
rimental MC testbed in [75]. Similarly, in [125], the
authors propose an implantable bio‑cyber interface
architecture that can enable the in vivo optical
stimulation of brain cells to control neuronal
communications based on external EM signals. Their
device architecture includes a wireless antenna unit that
connects the implanted device to external networks, an
ultrasonic energy harvester, and a micro light emitting
diodes (-LED) for optical stimulation.
Fluorescent molecules, such as luorescent proteins,
quantum dots, and organic dyes, can also be used to rea-
lize a wavelength‑selective optical interface. In [113],
organic dye molecules have been used as
nanotransceiver antennas for FRET‑based molecular
nanonetworks. They act as single molecular optical
interfaces that receive optical control signals from an
external source and non‑radiatively transmit them
into a FRET‑based nanonetwork. They enable an
nano‑to‑macro interface as well, since the excited
luorescent molecules return to their ground state by
releasing a photon at a speciic wave‑length that can
be detected by an external photodetector. Similarly, in
[75, 126], it is suggested that a nano‑to‑ macro interface
can be realized with engineered bacteria receivers
expressing pH‑sensitive green luorescent proteins
(GFPs) that change excitation/emission characte-ristics
depending on the pH of the environment. Biolumi‑
nescent molecules that are excited upon reaction with a
target molecule can also be used for the direct conversion
of MC signals to optical signals to enable a nano‑to‑macro
interface, as proposed in [127, 108].
3.2.3 Other Interfacing Methods
Depending on the communication modality utilized in in‑
trabody IoBNT, there are some other nano‑macro inter‑
facing methods proposed in the literature. For example, in
[128], the authors consider the use of magnetic nanopar‑
ticles (MNs) as information carriers in a MC system. They
propose a wearable magnetic nanoparticle detector in the
form of a ring to connect the intrabody MC to an RF‑based
backhaul. In a follow‑up study [129], they also demon‑
strate the control of MN‑based MC signals in microluidic
channels with external magnetic ields, that could poten‑
tially evolve to a bidirectional interface for IoBNT.
In light of the emerging reports on the EM‑based wireless
control of cellular functions via speciic proteins that are
responsive to electromagnetic ields [130], a wireless link
is proposed to connect THz‑band EM and MC modalities,
that can translate into an EM‑based nano‑macro interface
[131]. The authors in [132], develop an information the‑
oretical model for the mechanotransduction communica‑
tion channel between an implantable THz nanoantenna
acting as the transmitter and a biological protein as the re‑
ceiver undergoing a conformational change upon stimula‑
tion by the THz waves. Although THz‑waves are theore-
tically shown to reliably control the conformational
states of proteins, it remains as a challenge to investigate
the use of the same modality in sensing the protein
states to enable bidirectional wireless interface.
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
3.3 Energy Harvesting, Power Transfer, and
Energy Eficiency
Supply, storage and eficient use of energy is one of the
most crucial challenges towards realizing the envisioned
IoBNT applications. The energy challenge is currently be‑
ing addressed through the development of energy har‑
vesting (EH) and wireless power transfer (WPT) tech‑
niques to continuously power BNTs, the development of
high‑capacity energy storage devices at micro/nanoscale,
and the design of low‑complexity and energy‑eficient
communication methods for IoBNT.
For BNTs based on engineered cells, the challenge of
energy management is relatively straightforward, as
living cells have been evolved over billions of years to
make the most eficient use of biochemical energy for
realizing vital functionalities. Nonetheless, energy
budget requirements of engineered cells may be
extended with the introduction of new computation and
communication functionalities that are demanded by
complex IoBNT applications. On the other hand, there
are only a few studies that consider the overall energy
requirements of MC for only very simple scenarios [133,
134]. The problem is, of course, more challenging for
artiicial BNTs, such as those that are made up of
nanomaterials and missing an inherited metabolism for
energy management.
3.3.1 Energy Harvesting
Leaving aside the continuous efforts to reduce the com‑
plexity of communication methods for IoBNT, such as
modulation and detection techniques [13], in the hope
of increasing energy eficiency, the most promising so‑
lution to enable self‑sustaining IoBNT is the integration
of EH modalities into BNTs. EH has recently received
tremendous research interest partly due to the energy
requirements set by emerging applications of IoT and
IoE. Depending on the application environment and de‑
vice architectures, various natural energy sources have
been considered for harvest by IoT devices [135, 136].
For example, solar energy, vibration sources, electroma-
gnetic sources, e.g., ambient RF EM waves, and
metabolic sources have been deemed feasible for
harvesting [137]. Concerning the intrabody and body
area applications, human body stands as a vast source
of energy in the form of mechanical vibrations resulting
from body movements, respiration, heartbeat, and blood
low in vessels, thermal energy resulting from body heat,
and biochemical energy resulting from metabolic
reactions and physiological processes [138]. Literature
now includes a multitude of successful applications of
human body EH to power miniature biomedical
devices and implants, such as thermoelectric EH from
body heat for wearable devices [139], vibrational EH
from heartbeats [140] and respiratory movements
[141] to power pacemakers, as well as biochemical EH
from human perspiration [142]. These together with
EH from chemical reactions within the body, such as
glucose uptake, lactate release, and pH variations
[138, 143], can be exploited to power the BNTs in an intra‑
body IoBNT. Among the potential EH mechanisms for in‑
trabody IoBNT, mechanical EH has attracted the most in‑
terest. Research in this ield has gained momentum with
the use of lexible piezoelectric nanomaterials, such as
ZnO nanowires and lead zirconate titanate (PZT), in nano‑
generators, enabling energy harvesting from natural and
artiicial vibrations with frequencies ranging from very
low frequencies ( Hz) up to several kHz [144, 145].
3.3.2 Wireless Power Transfer
Another way of powering BNTs and IoBNT applications
can be WPT from external sources. WPT has seen sig‑
niicant advances in recent years due to increasing need
for powering battery‑less IoT devices as well as wea-
rable and implantable devices. Various forms of WPT
have been considered for powering medical implants
[146, 147]. For example, near‑ield resonant inductive
coupling (NRIC)‑based WPT, the oldest WPT technique,
has been in use for widely‑used implants, such as
cochlear implants [148, 149]. Other techniques include
near‑ield capaci‑ tive coupling, midield and far‑ield
EM‑based WPT, and acoustic WPT. Power transfer via
near‑ield capacitive and inductive coupling, however, is
only eficient for dis‑ tances on the order of transmitting
and receiving device sizes, and for the right alignment
of devices, and there‑ fore, might not be suitable for
powering micro/nanoscale BNTs [148]. On the other
hand, radiative mid‑ield and far‑ield EM‑based WPTs
can have looser restrictions depending on the frequency
of EM waves.
Recent research on mm‑wave and THz rectennas suggests
the use of high‑frequency EM WPT techniques to power
BNTs [150]. However, for intrabody applications, the
higher absorption with increasing frequency and power
restrictions should be taken into account. Nonetheless,
simultaneous wireless information and power transfer
techniques (SWIPT) utilizing THz‑band have been inves‑
tigated for EM nanonetworks [151, 152]. Similar SWIPT
applications have been considered for MC, where the re‑
ceiving BNTs use the received molecules for both deco-
ding the information and energy harvesting [153,
154]. There are also applications of acoustic WPT for
biomedical implants using external ultrasonic devices
[155, 156]. Although not implemented yet, ultrasonic
EH has been also considered for powering BNTs with
piezoelectric transducers [157, 158, 125].
An interesting research direction in parallel with the
wider IoE vision is towards hybrid EH systems that can
exploit multiple energy sources. Prototypes have been
implemented for ZnO nanowire‑based hybrid cells for
concurrent harvesting of solar and mechanical energies
[159], and piezoelectric PVDF‑nanoiber NG based hybrid
cells for biomechanical and biochemical EH from bodily
luids [160]. A hybrid EH architecture is also proposed
for IoE comprising modules for EH from light, mechanical,
thermal, and EM sources [161]. The same hybrid archi‑
tectures could be considered for IoBNT as well to main‑
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
tain the continuous operation of BNTs. EH from multiple
resources can reduce the variance at power output with
the addition of alternative complementary procedures in
a modular fashion as investigated in [161].
3.3.3 Energy Storage
Storage of energy is also important when BNTs can‑
not continuously satisfy their power requirements via
EH and WPT techniques. There has been conside-
rable interest in miniaturizing the energy storage
technologies to make them size‑compatible with MEMS
and NEMS devices. Some of the efforts have been
devoted to develop micro‑batteries, miniaturized ver-
sions of conventional thin‑ilm lithiumion batteries,
beneiting from novel nanomaterials [162]. There are
even a few studies focusing on nanoscale versions of
lithium batteries [163, 145]. However, they suffer from
low energy density, short lifetimes, and potential
toxicity in in vivo applications. More promising solution
is micro‑supercapacitors (MSCs), which provide
signiicantly higher energy storage capacity, higher
charge/discharge rates, and more importantly, scalability
and lexibility, which are crucial for their integration
into BNTs [164, 165, 166].
Several types of materials have been considered for the
design of MSC electrode to improve the energy density.
Carbon nanomaterials, such as CNTs and graphene, are
the most widely researched materials due to their abun‑
dance and stability, which is relected to an extended life‑
time [164]. Due to its extremely high surface‑to‑volume
ratio, high mobility and lexibility, graphene has attracted
particular attention [167, 168]. Additionally, conducting
polymers, such as PEDOT/PSS, and graphene/conducting
polymer heterostructures are also considered as lexible
electrodes for MSCs [164]. The research in MSCs is still at
early stages; however, we believe that with the increase
of energy density and further reduction of sizes, they can
be a viable candidate for energy storage units in BNTs.
3.4 Biocompatibility and Co‑existence
Biological processes are complex, and intertwined, often
through intricate relationships that are yet to be unco-
vered. Perturbation of homeostasis maintained by
these relationships may result in serious disorders. Even
more complicated is the fact that the composition of the
physiological environment and the interactome may have
a large variance among different members of the same
species. For example, gut microbiome is known to be
composed of different types of bacteria in different
people [169]. Therefore, the evaluation of in vivo
IoBNT applications in terms of biocompatibility is very
challenging, however, must be considered seriously.
Biocompatibility constraints for IoBNT can be viewed
from two angles [170]. First, an IoBNT application, along
with all the communication methods and devices therein,
should not disrupt the homeostasis of the organism it is
implemented in. Such disruption might occur when the
introduced application has toxic, injurious, or adverse ef‑
fects on the living cells and biochemical processes. Se-
cond, an implanted IoBNT application should be able
to operate without its performance being degraded by
the co‑existing biochemical processes. Performance
degradation usually follows when an IoBNT application
alters the metabolic activities, because such alternation
invokes the immune response that might in turn lead to
the rejection of the deployed application. Rejection can
occur in the form of expulsion of the IoBNT application
from the organism, encapsulation of the BNTs with
biological cells and tissues, or inlammation or death of
the surrounding tissues. In the case of MC, performance
degradation may also happen as a result of cross‑talk
caused by the natural biochemical signaling.
Biocompatibility concerns both materials used in the
physical architecture of BNTs, and the networking, energy
harvesting, power transfer, and interfacing processes of
the IoBNT. In terms of materials, synthetic biology‑based
BNTs can be considered highly biocompatible, as they
adopt living cells and cellular components as the sub‑
strate [24]. Likewise, luorescent protein‑ and DNA‑based
BNTs are also of biological origins, and thus, can be ex‑
pected to offer similar levels of biocompatibility [108].
However, depending on their exact biological origin and
their overall amount in the body, they may still trigger
the immune response. For example, a virus‑based syn‑
thetic BNT can be labeled as foreign agent and attacked
by the immune system, unless it is designed to possess
a kind of stealth proteins that help escape the immune
control [171]. For artiicial BNTs based on nanomateri‑
als, biocompatibility is more challenging. There is still
no consensus on a universal test of biocompatibility for
nanomaterials, leading to conlicting results in the litera‑
ture about almost all materials. Complexity of the biologi‑
cal systems and reproducibility problem for in vivo and in
vitro tests are the main causes of the ongoing ambiguity.
Nonetheless, many polymers (e.g., PMMA, Parylene), gold,
titanium, and some ceramics are widely known to be bio‑
compatible [172, 173, 174]. Carbon‑based materials, e.g.,
CNT and graphene, have been reported as both biocom‑
patible and toxic in different works, preventing a gene-
ralization over these nanomaterials. This is attributed
to large variations in their physicochemical properties,
e.g., size, shape, surface characteristics, adopted in
different works [175, 176]. However, it has been
repeatedly re‑ ported that their biocompatibility can be
modulated with chemical manipulation [175]. For
example, surface functionalization with dextran is
shown to reduce the toxicity of graphene oxide (GO),
hinting at strategies to make carbon‑based
nanomaterials suitable for safe in vivo applications
[177, 176]. Similarly, nanoparticles are shown to be
detoxiied upon the functionalization of their surfaces
with smart/benign ligands [178].
In terms of processes, attention must be paid to the
communication, bio‑cyber interfacing, energy harvesting,
transfer and storage processes. In EM‑based and acous‑
tic communication and power transfer processes, for ex‑
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
ample, the biocompatibility is crucial for preventing the
damage on biochemical structures, e.g., tissue damage by
heating, and closely linked to the frequency and power
of the EM or acoustic waves. For human body applica‑
tions, the exposure limits are regulated by the Food and
Drug Administration (FDA) in US, as 100 W/mm for
RF waves and 7.2 mW/mm for ultrasound waves, [125,
179]. These limits should be taken into account in the de‑
sign of IoBNT technologies.
In the cases that MC is adopted in IoBNT applications,
the concentration and type of molecules used for com‑
munications is very critical for biocompatibility. First,
the information‑carrying molecules should not invoke
the immune response. The degradation of information
molecules by enzymes should also be taken into account
to prevent performance degradation. Also, the MC sig‑
nals should not interfere with the inherent biological sys‑
tems. The type of information molecules must be or‑
thogonal to the molecules involved in biological processes
to prevent interference, or their concentration should
be low enough not to disrupt these processes. This so‑
called co‑existence challenge has recently attracted close
attention of MC researchers, who suggest different solu‑
tion strategies [180, 181, 182]. For example, in [182],
a cognitive radio‑inspired transmission control scheme
is proposed to overcome interference between MC net‑
works and co‑existing biological networks. In [57], vari‑
ous channel sensing methods inspired from the spectrum
sensing techniques in EM cognitive radio are proposed to
estimate the instantaneous composition of the MC chan‑
nel with ligand receptors in terms of molecule types. The
effect of biological cross‑talk on the MC is also investi‑
gated in [183], where the performance of several detec‑
tion methods are investigated in terms of their ability to
ensure reliability under such biological interference.
4. CONCLUSION
In this survey, a comprehensive overview of IoBNT frame‑
work along with its main components and applications
is provided to contribute to an holistic understanding
of the current technological challenges and potential re‑
search directions in this emerging ield. In light of rapid
advances in synthetic biology, nanotechnology, and non‑
conventional communications made possible by inter‑
disciplinary approaches, we believe that the enormous
potential of the IoBNT will soon be realized with high‑
impact medical, environmental and industrial applica‑
tions.
ACKNOWLEDGEMENT
The work of Murat Kuscu was supported in part by the
European Union’s Horizon 2020 Research and Innovation
Programme through the Marie Skłodowska‑Curie Indivi-
dual Fellowship under Grant Agreement 101028935
and by The Scientiic and Technological Research
Council of Turkey (TUBITAK) under Grant #120E301.
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AUTHORS
Murat Kuscu received his PhD
degrees in engineering from
University of Cambridge, UK,
in 2020, and in electrical and
electronics engineering from
Koç University, Turkey, in 2017.
He is currently an Assistant
Professor with the Department
of Electrical and Electronics En‑
gineering, Koç University. His current research interests
include the Internet of Bio‑Nano Things, bio/chemical
information and communication technologies, graphene
and related two‑dimensional nanomaterials, biosensors,
bio‑cyber interfaces, and microluidic sensors. He has
received the Marie Skłodowska‑Curie Actions Individual
Fellowship 2020, University of Cambridge CAPE Acorn
Post‑graduate Research Award 2019, IEEE Turkey Ph.D.
Thesis Award 2018, and Koç University Post‑graduate
Academic Excellence Award 2018.
Bige Deniz Unluturk received
her Ph.D. degree in Electrical
and Computer Engineering from
the Georgia Institute of Techno-
logy, Atlanta, GA, in August
2020. In 2013, she received her
M.Sc. degree from Koc
University, Istanbul, Turkey.
In 2011, she graduated from Electrical and Electronics
Engineering at Middle East Technical University, Ankara,
Turkey. She is currently an assistant professor in the
Departments of Electrical & Computer Engineering and
Biomedical Engineering at Michigan State University.
Her research is in the areas of wireless communication
and networking, more specifically Molecular
Communications and Internet of Bio‑NanoThings, and
their applications to healthcare.
ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3, 13 December 2021
