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Towards 6G: Key Technological Directions
Chamitha de Alwis, Pardeep Kumar, Quoc-Viet Pham, Kapal Dev,
Anshuman Kalla, Madhusanka Liyanage, and Won-Joo Hwang
Abstract—Sixth-generation mobile networks (6G) are expected
to reach extreme communication capabilities to realize emerging
applications demanded by the future society. This paper focuses
on six technological directions towards 6G, namely, intent-
based networking, THz communication, artificial intelligence,
distributed ledger technology/blockchain, smart devices and
gadget-free communication, and quantum communication. These
technologies will enable 6G to be more capable of catering to the
demands of future network services and applications. Each of
these technologies is discussed highlighting recent developments,
applicability in 6G, and deployment challenges. It is envisaged
that this work will facilitate 6G related research and develop-
ments, especially along the six technological directions discussed
in the paper.
Index Terms—6G, Intent-based networking, THz communica-
tion, AI, blockchain, smart devices, gadget-free communication,
quantum communication
I. INTRODUCTION
Sixth-generation mobile networks (6G) are expected to
be deployed by 2030 to facilitate advanced communication
requirements of the future data-centric and hyper-connected
society. 6G networks will reach extreme network capabilities
to facilitate ultra-high-speed connectivity, ultra-low-latency
communication, and highly scalable low-latency machine-type
communication [1], [2]. Fig. 1 portrays the key improvements
envisaged through 6G over fifth-generation mobile networks
(5G), and a high-level 6G architecture, indicating the key tech-
nological components and applications of 6G. These network
capabilities of 6G will enable many new applications and
services, including holographic teleportation, energy internet,
space and deep-sea communication, Connected Autonomous
Vehicles (CAVs), and the next industrial revolution known
Chamitha de Alwis is with University of Bedfordshire, United Kingdom and
University of Sri Jayewardenepura, Sri Lanka (email: chamitha@ieee.org).
Pardeep Kumar is with the Swansea University, United Kingdom (email:
pardeep.kumar@swansea.ac.uk).
Quoc-Viet Pham is with the Korean Southeast Center for the 4th Indus-
trial Revolution Leader Education, Pusan National University, Busan 46241,
Republic of Korea (e-mail: vietpq@pusan.ac.kr).
Kapal Dev is associated with the Munster Technological University, Ireland
(email: kapal.dev@ieee.org).
Anshuman Kalla is with Uka Tarsadia University, India (email: anshu-
man.kalla@ieee.org).
Madhusanka Liyanage is with the University Collage Dublin, Ireland
(email: madhusanka@ucd.ie).
Won-Joo Hwang (corresponding author) is with the Department of Biomed-
ical Convergence Engineering, Pusan National University, Yangsan 50612,
Republic of Korea (e-mail: wjhwang@pusan.ac.kr).
This work was supported in part by the National Research Foundation
of Korea (NRF) Grant funded by the Korean Government (MSIT) under
Grant NRF-2019R1C1C1006143 and Grant NRF-2019R1I1A3A01060518;
in part by BK21 Four, Korean Southeast Center for the 4th Industrial
Revolution Leader Education; and in part by the Institute of Information
& Communications Technology Planning & Evaluation (IITP) Grant funded
by the Korea Government (MSIT) under Grant 2020-0- 01450 (Artificial
Intelligence Convergence Research Center [Pusan National University]).
as Industry 5.0. However, realizing 6G networks and 6G
applications demands significant advancements over existing
technologies. Many research articles on 6G, such as the work
published in [2], [3], provide a broad overview of 6G vision
and developments towards 6G. In contrast, this paper focuses
on six technological directions towards 6G, namely, Intent-
Based networking (IBN), Terahertz (THz) communication,
Artificial Intelligence (AI), Distributed Ledger Technology
(DLT)/Blockchain (BC), Smart Devices and Gadget-free com-
munication (SDG), and Quantum Communication (QC). The
paper elaborates on key technological developments, 6G ap-
plicability, technical challenges, possible solutions available
in the literature, and possible applications of each of the six
technological directions. The impact of these technological
directions for 6G architectural layers is presented in table I,
and 6G applications are tabulated in table II.
The rest of the paper is organized as follows. Section II
explores IBN, whereas Section III focuses on THz communi-
cation. Section IV explains the technological direction of AI.
Section V presents DLT/BC, Section VI portrays smart devices
and gadgets and Section VII identifies quantum communica-
tion as key technological directions towards 6G. Furthermore,
the technological developments under each direction, along
with their potential, existing challenges, and possible solutions,
are presented in table III. Finally, Section VIII concludes the
paper. It is envisaged that this paper would shed light to
facilitate future research and development work along these
technological directions towards realizing 6G.
II. IN TE NT-BASED NETWORKING
IBN automates the deployment of business intent in net-
works by utilizing well-defined policies to support the rapid
adaptation of new 6G services [4]. Due to the inherent support
to realize business intentions, IBN is being adapted in the pro-
duction networks of large enterprises. A typical IBN comprises
three primary functions, namely intent translation, activation
of intents, and assurance. Intent translation translates business
into policies that can be understood by networks, whereas, ac-
tivation of intents performs network-wide deployment of intent
policies by automating the configuration across physical and
virtual networking devices. In addition, assurance monitors
and analyzes the network to verify the desired intent by using
Machine Learning (ML) and AI. Currently, IBN deployments
are built on Software-Defined Networking (SDN) where the
SDN controller acts as a centralized control point to manage
network operations. Thus, both network softwarization tech-
nologies (i.e., SDN/Network Function Virtualization (NFV))
and network intelligent technologies (i.e., AI/ML) are expected
to play a vital role in realizing IBN in future networks.
2
6G Smart
Application Layer
Intelligent
Control Layer
Edge Layer
Wireless
Access Layer
6G Device
Layer
Industry 5.0 Smart Grid 2.0 Holographic
Telepresence
Connected
Autonomous
Vehicles
AI/ML Zero Touch
Management
Blockchain/
DLT
Edge AI
Swarm
Networking
Visible Light
Communication
3D
Networking
Quantum
Communication
Gadget Free
Communication
Smart
Devices
THz
Smart
Surfaces
Space
Communication
UAV Cobots Intelligent
Healthcare
Internet of
Everything
Intent-based
Networking
Fig. 1: 6G improvements, high level 6G architectural layers, 6G technologies, and applications [1].
A. 6G Applicability
IBNs are expected to introduce AI into 6G networks [5]. Ac-
cordingly, IBNs have the capability to solve many of the per-
sisting issues with pre-6G networks, specially in the areas of
flexibility, efficiency, and security. This is performed through
transforming users’ intents into network configurations and
strategies. The use of AI and Big Data with IBN can improve
the robustness, dynamicity, and adaptability in automated
network operation and maintenance. IBN heavily depends on
AI/ML to perform routine tasks, set policies, respond to system
events, and verify achievement of goals and actions of each
intent. Moreover, IBN-enabled 6G networks will support fast
and easy deployment of new services, service prioritization,
and service integration across all 6G Network layers (See
table I). For instance, IBN helps to accurately identify multi-
type end-user service intent in Internet of Things (IoT) applica-
tions and implement multi-dimensional sensing requirements.
Also, the continuous monitoring, gathering of telemetry, and
efficient analysis using AI/ML reduces the risk of malfunction
of services and neutralizes other threats. Furthermore, IBN
helps to optimize and configure the network services to achieve
the goals of corresponding business applications. The intent
translation in IBN allows the desired operational service-level
agreements of users to be efficiently applied across the network
and improve the customer experience. It fuels the use of
6G across many vertical industries. IBN systems can also
intelligently predict possible deviations from the intent, and
proactively take action to streamline with the intent. Thus,
IBN enables self monitoring and self correcting features of
6G. In addition, IBNs can facilitate the massive demand for
intelligent services in 6G, such as adapting to time-varying
radio propagation and network environment banking on real-
time network data [5]. Hence, IBN offers a clear advantages
over regular networking to enable 6G applications, as seen in
Table II.
B. Deployment Challenges and Possible Solutions
The current implementations and developments of IBN is
mainly focused on the network core. Hence, IBN solutions
are required to be optimized for the wireless access network.
The availability of AI resources at the access network segment
with Edge-AI and distributed AI will facilitate the deployment
of IBN in wireless networks. O-RAN Alliance developed
Non Real-Time RAN Intelligent Controller (Non-RT RIC)
concept based on automation and AI/ML to realize Intent-
based wireless RAN management. High degree of network
programmability and intelligent automation of 6G RAN is pos-
sible to realize with Intent-based Non-RT RIC deployment [6].
In addition, considering the IBN integration with 6G from the
very early stages will resolve possible integration challenges
in the future. Use of IBN in 6G could also introduce new
security challenges, such as, information exposure, undesirable
configuration, and abnormal behavior attacks. Thus, network
security solutions such as input validation via mutual au-
thentication between intent producer and consumer, controlled
access via authorization and AI-based proactive monitoring for
abnormality detection, need to be in place before integrating
IBN in 6G architecture. 6G wireless networks have many
configurable parameters to support billions or even trillions
of users and devices. However, the traditional IBNs will not
have an agile operation system to keep up with such a huge
user device ecosystem and the rapidly changing business needs
in 6G networks. This can be addressed through AI/ML based
automation. Furthermore, developments are needed towards a
more flexible and accurate intelligent IBN to facilitate dynamic
business models. In addition, choosing and optimizing AI
algorithms to facilitate the efficient and accurate operation of
IBNs also remain to be thoroughly explored [5].
III. THZCOMMUNICATION
While commercial 5G networks are deployed throughout the
world, the research community is on the verge of speculating
what will be future 6G systems. As discussed in [10], the
key performance factors of 6G include peak data rate of 1
3
TABLE I: Impact of the technological directions for 6G layers [2], [7]–[9]
High Level 6G Architectural Layers
Technology Direction 6G Smart Application Intelligent Control Edge Wireless Access 6G Device
Intent-based Networking
Rapid implementation
of goals, network
customization for
applications
Better troubleshooting,
resolution, analytics,
reconfiguration, self-
healing
Customized service
delivery, automated
and proactive service
migrations, user level
service assurance
Customized coding, in-
tent based spectrum al-
location, AI/ML RAN
managemnet, innovation
for openness
Map intents to device
configurations
THz Communication Provide high data-rate
for indoor applications
Deployment of emerging
services and control poli-
cies
High speed transmission
between edge nodes,
self-backhauling in tiny-
cell networks
Tbps data rates with
channel modelling, ran-
dom access, and MAC
protocols
Impact on the
transceiver, antenna
design, and network
architecture
Artificial Intelligence
Intelligent data analyt-
ics for autonomous deci-
sions
Autonomous control and
operation of sensors and
actuators
Intelligent routing and
placement to optimize
energy efficiency
Intelligent spectrum
sensing, analysis, and
allocation
Intelligent user devices
and algorithms that pro-
cess and analyze data at
the local level.
DLT and Blockchain
Decentralized, secure,
transparent and privacy-
protected applications,
BaaS for 6G applications
Security and privacy for
sharing AI/ML training
data and models for in-
telligent control
Trusted sharing of lo-
cally trained models in
FL and decentralized de-
cision making
Share access networks
and spectrum, secure
SDN-based operations,
transparent radio
management
On demand
computational off-
loading, incentive-based
trading of extra resources
Smart Devices and Gadgets
Enable new interactions,
powerful computing and
strong connectivity
Contribute to edge intel-
ligence capabilities
Harness/ contribute to
edge intelligence capa-
bilities
Support THz communi-
cation, quantum commu-
nication, VLC and LIS
Enable extended
reality, holographic
tele-presence, gadget-
free communication
Quantum Communication
Seamless integration of
smart societies over THz
system with optical in-
frastructure
Faster optimization of
problems and machine
learning techniques in in-
telligent control systems
Realize fast and secure
communication for
serverless edge networks
Reshape wireless net-
work via THz commu-
nication, enhance indoor
and outdoor localization
via fingerprinting
Facilitate quantum en-
abled secure communi-
cation to 6G devices
Tbps, experienced data rate of 10 Gbps, traffic density of 100
Tb/s/km2, a latency of less than 1 ms, reliability of 99.9999%,
centimeter-level positioning, and receiver sensitivity of less
than -130 dBm. Several frequency bands used in the current
network generation, such as millimeter Wave (mmWave) and
Sub-6 GHz do not satisfy the growing demands in 6G. In this
vein, THz communication (0.1 THz to 10 THz corresponding
to the wavelength of 3 mm and 0.03 mm) is regarded as
a promising solution thanks to its distinctive features. In
particular, the THz band can provide up to a hundred GHz
bandwidth, which far exceeds the mmWave band with 10 GHz
bandwidth at most. THz communication is also highly suitable
for massive multi-input multi-output (MIMO) systems with
hundreds of antennas. Moreover, high directionality enabled
by THz signals can be leveraged for interference mitigation
and user satisfaction maximization [11]. Recent advancements
in THz hardware and wireless technologies have shown the
great impact of THz communication on 6G architectural layers
(as shown in table I).
A. 6G Applicability
THz band have been used for traditional applications such
as sensing, imaging, and localization [11]. Recently, THz
communication has found in promising 6G scenarios, sum-
marized in table II. Bandwidth-abundant THz channels are
used for direct wireless transmissions between radio towers
and mobile devices [9]. Furthermore, THz communication
can be leveraged as a key enabler of integrated access and
backhaul networks. In particular, THz communication enables
wireless backhauling between macrocells and small cells. This
THz-enabled wireless backhaul can be used on top of other
frequency bands such as Sub-6 GHz and mmWave, and also
eliminates the need for a licensed bandwidth spectrum. The
implementation of wireless backhaul plays an important role
in ultra-dense heterogeneous networks, where deploying wired
backhaul for a large number of small cells and tiny-cells is an
impractical solution. The existing satellite systems typically
use Ku band, Ka band, and V band for Internet connectivity.
For instance, the OneWeb satellite system has deployed a total
of 110 satellites (December 2020) over the Ku and Ka bands
at an altitude of 1200 km (https://www.oneweb.world). Using
THz communication for high-speed satellite communication
links is also a promising scenario in future networks [9].
B. Deployment Challenges and Possible Solutions
Despite distinctive features and promising applications, sev-
eral challenges should be overcome for THz communication
realization in 6G wireless systems. For instance, large path
losses, and smaller coverage areas, hence requiring more
and ultra-dense base-station deployments with tiny cells, are
evident challenges related to using the THz band. Additional
challenges of using the THz band in 6G are summarized in
table III. THz wireless communication needs small antenna
sizes in order to achieve diversity gain [2]. This requires ultra-
Massive MIMO to facilitate THz wireless communication
in 6G networks. In this regard, Large Intelligent Surfaces
(LIS) can be used with 6G to go beyond massive MIMO
to facilitate THz range frequencies. The directionality fea-
ture of the THz band also raises serious issues for medium
and random access protocols. Non-orthogonal multiple access
(NOMA) and beamforming are promising solutions to combat
highly directional transmissions of THz signals. In particular,
NOMA allows multiple users to share the same THz beam,
thus enabling massive IoT connectivity [12]. Other major
challenges of THz communication include channel modeling,
resource optimization, and health issues.
4
IV. ARTI FIC IA L INTELLIGENCE
Researchers are considering the vision, essential enabling
technologies, and use cases for 6G as the worldwide rollout of
5G continues. The deployment, design, and operating phases
of the 6G layers depicted in Table I are expected to be made
possible by AI [13]–[15]. AI will evolve the conventional
methods to a flexible and programmable-based network that
would help optimize the network management process in
6G [16]. Furthermore, the intelligent agents using AI methods
will help solve complex problems on vast scales that could
result in the provision of concurrent connections and new
sensing technologies [17]. In fact, with the inclusion of AI,
6G systems would become cognitive in a legitimate way. For
instance, communication aspects of 6G, including spectrum
sharing, radio resource management, quality of service, net-
work slicing, and virtualization, will hinge on AI techniques
to solve intricate and domain-specific problems.
A. Application of 6G Technology and AI
With 6G technology, AI will play a key role in reshaping
communication-based services, as well as the other applica-
tions addressed in Table II. For example, self-driving cars in
the auto industry need to know about their constantly changing
environment, location, pedestrians, cyclists, and other cars in
order to find the best route and get through intersections.
Handling, generating, and processing large amounts of data
simultaneously in collaboration is another task that needs AI
(intelligent agents) to solve complex problems in real time on
a larger scale. Moreover, it can be used in all emerging indus-
tries, not merely the auto industry.
In the field of artificial intelligence, potential future appli-
cations of 6G technology include the more traditional uses,
which include diagnostic, prescriptive, and descriptive analyt-
ics [18]. Prescriptive analytics can be used to make judgments
or make predictions relating to edge computing, cache place-
ment, network virtualization, slicing, resource allocation, and
other related topics [19]. With the use of predictive analytics,
one may make educated guesses about the future based on
the data that has been collected in real time and applied to
factors such as the availability of resources, preferences, user
behavior, user locations, and traffic patterns. The purpose of
diagnostic analytics is to identify problems inside a network,
which includes locating network abnormalities, service impair-
ments, network failures, and their underlying causes. This, in
turn, contributes to an improvement in the network’s level
of dependability and security. In order to improve the ser-
vice provider’s and network operator’s situational awareness,
descriptive analytics largely rely on previous data. The apps
cover a wide range of topics, such as user views, channel
conditions, traffic profiles, and network performance, among
others.
B. Challenges in AI Deployment and Potential Solutions
When the aforementioned use cases and applications dis-
cussed in preceding sections are taken into consideration, it
is reasonable to think that AI can be incorporated into 6G
systems on both fronts, i.e. components and applications, in
the appropriate manner [18]. Despite this, these enabling 6G
components are just in their first phases and still need to
solve a number of difficulties, which are outlined in the table
referenced (c.f. Table III). For instance, it is obvious that
the use of AI in 6G needs the mining of massive amounts
of data, which presents questions about the ownership of
data, as well as ethics, privacy, and security, among other
issues. In addition, Unmanned Aerial Vehicles (UAVs) can
also become a part of the edge computing infrastructure of 6G
networks to facilitate AI processing in 6G networks [20]. In
addition, rules and laws need to be drafted in order to preserve
data integrity, privacy, and security during the process of
building the network architectures and protocols in the context
of 6G in order to achieve an appropriate balance between
the potential benefits and potential dangers. In addition, the
difficulties become more varied when dealing with distinct
sets of applications, such as healthcare optimization, financial
market monitoring, smart grids, extended reality, and industry
5.0 [15].
V. DISTRIBUTED LE DG ER TECHNOLOGY AND
BLOCKCHAIN
DLT is touted to have a broader scope to contribute towards
the growth of 6G networks and its applications. DLT enables
secure and distributed storage of a digital ledger at all the
participating nodes in the underlying network using the same
protocol [21]. Thus, all the nodes independently maintain an
identical copy of the digital ledger. One of the prominent types
of DLT is BC which has received all-around attention [21]. BC
follows a specific structure to create and update the distributed
ledger. It comprises immutable blocks (containing set of valid
transactions) that are timestamped and are connected using
a hash-based chain. In other words, in BC, transactions are
validated, clubbed together, and cryptographically sealed in a
unit called a block. The newly created block is appended to
the BC by connecting it with the last block in the ledger using
a cryptographic hash-based chain. This chaining is indeed
established by inserting the hash of the previous block in (the
header of) the newly created block. Some of the well-know
characteristics of BC are immutability, non-repudiation, prove-
nance, enhanced security, pseudonymity, distributed database,
and decentralized operations.
A. 6G Applicability
DLT, and in particular BC technology, has the capability
to address many prevailing issues related to 6G development,
such as, flexibility, autonomous and intelligent operation,
security, privacy, accountability, interoperability, and efficient
resource management. However, this requires the integration
of DLT/blockchain with 6G networks. For instance, BC can
be instrumental in terms of efficient spectrum sharing in 6G
wireless networks. BC, along with smart contracts, can reduce
the administrative costs and issues pertaining to the centralized
management of spectrum [8] and resource sharing [22]. BC
with smart contracts also has the potential to establish dynamic
agreements and effectuate seamless roaming instances and
5
TABLE II: Applicability of the technological directions for 6G applications
6G Application
Technology Di-
rection Industry 5.0 Intelligent
Healthcare
Internet
of Everything Smart Grid 2.0 UAV/Connected Au-
tonomous Vehicles
XR/Holographic
Telepresence
Intent-based
Networking
Eliminate manual
configurations,
improved system
agility, fast network
services deployment
Fast network services
deployment, improved
security and privacy,
reduced complexity
Fast network services
deployment, improved
security and privacy,
reduced complexity
Eliminate manual con-
figurations, improved
security and privacy,
reduced complexity
Improved security and
privacy, reduced com-
plexity, fast network
services deployment
Fast network services
deployment, improved
security and privacy
THz
Communication
Improved wireless se-
curity and control
THz imaging/sensing
in smart healthcare,
THz nano-/in-body
communication
THz tiny-cell for pro-
vide seamless connec-
tivity to everything
Gbps communication
for efficient pricing
control and transmis-
sions among end de-
vices
Ultra-fast and dense
aerial access networks
Tbps transmissions
between end devices
and edge computing
servers
Artificial
Intelligence
Autonomous tasking
for cobots, neural
links for controlling
machines remotely
Automatic analysis of
health records, real-
time monitoring and
recommendations
Heterogeneous
data analysis,
condition based
recommendations,
intelligent services
Intelligent load alloca-
tion and balancing, re-
routing in case of dis-
asters
Energy efficiency
routing protocols, re-
routing, computational
offloading, shortest
path finding
Advanced computer
vision techniques to
recognize environment
and gestures
DLT
and Blockchain
Enhanced security,
privacy protection,
dynamic business
contracts
Secure patient moni-
toring, automated han-
dling of medical insur-
ance
Decentralized compu-
tation, distributed stor-
age, secure communi-
cation, smart contracts
decentralized
automated smart
grids, open market
energy trading
Identity management,
fault tolerance, decen-
tralized security man-
agement
Decentralized content
market places, security
and privacy protection
Smart
Devices
and Gadgets
Digital twin operation,
cobots, automated in-
dustries, supply chain
management
Tele-surgery, tele-
consultation, smart-
wearables
Advanced sensors
with efficient
operation and
communication
Smart energy meters,
sensors, renewable en-
ergy generators
Advanced drones,
smart vehicles,
autonomous vehicles
XR devices, haptics,
holographic displays,
gadget-free communi-
cation
Quantum Com-
munication
Scalable quantum
routing for fast data
transport
Enable quantum tele-
portation in robotic
surgery
Quantum key distribu-
tion in IoE to enable
security features
Intelligent control
systems, secure
communication
between nodes
Multi-degree of Free-
dom, high purity for
Internet of Vehicles
Multipartite entangle-
ments of purification
and holography
tackle roaming frauds [23]. Furthermore, BC can enhance
the applicability of AI/ML techniques for 6G networks and
applications by providing enhanced security and privacy-
protection [7], [24]. Furthermore, BC can ensure the overall
security of 6G networks at different layers as depicted in
table I. Another directions where BC can play a significant role
is to support the new range of 6G applications are presented
in table II). DLT/BC, with its underlying cryptographic mech-
anisms, distributed database, consensus protocols, and smart
contracts, can satisfy the crucial requirements of these appli-
cations such as secure and privacy-protected data exchange,
strict access control, traceability, and identity verification [2],
[25]. Furthermore, DLT/BC is instrumental in establishing an
open market and business model of 6G [26]. Thanks to the
intrinsic capabilities of DLT/BC, different network operators,
third-party vendors, and resource providers can participate
in building complex 6G ecosystems in a trustless yet au-
ditable manner. For instance, European Telecommunications
Standards Institute (ETSI) has initiated Industry Specification
Group on Permissioned Distributed Ledger (ISG PDL) to
explore the applicability of permissioned distributed ledger for
developing an industrial open ecosystem [27].
B. Deployment Challenges and Possible Solutions
The integration of blockchain with 6G demands several
challenges to be addressed. For instance, with the proliferation
of connected IoE devices, data-intensive new applications, and
high-speed communication infrastructure, a large number of
transactions will be pushed to DLT based 6G system. Accord-
ingly, the system will require a very high throughput, i.e., the
ability to process a large number of transactions per unit of
time. The verified transactions need to be stored at all the
nodes independently, which will blow up the storage capacity.
Moreover, the bigger the database (ledger), the higher the time
required to verify a new transaction, which will increase the
latency. Though DLT/BC can enable transactions between un-
trusted stakeholders, it is prone to security attacks like DDoS
attacks or AI-related attacks. Some possible solutions are
sharding or hierarchical BC for throughput, off-chain storage
or sidechain for storage, homomorphic signature, and Trusted
Execution Environment (TEE) for security, and Privacy En-
hancing Technologies (PETs) and Attribute-Based Encryption
(ABE) for privacy. Furthermore, enhancing the interoperability
to facilitate seamsless operation of networks, limited data
replication among nodes to increase the scalability, developing
more energy and time efficient consensus algorithms, and
developing standards for blockchain developments needs to
be overcome in order to realize a tighter integration between
blockchain and emerging 6G networks.
VI. SM ART DEVICES AND GADGET-FRE E
COMMUNICATION
Over 24 billion smart devices, including smartphones, smart
sensors, smart wearables, and smart machinery, are expected
to be connected to 6G networks by 2030 [2]. These devices
will pack advanced technologies, smart screens and sensors
to provide personalized digital services banking on the edge-
intelligence capabilities of future networks. Furthermore, user
interfaces will harness technologies such as Extended Reality
(XR) and Holographic Telepresence (HT) to enable a plethora
of smart services such as intelligent health-care, smart cities
and Industry 5.0 [2]. Gadget-free communication is another
area that is expected to disrupt the way people access dig-
ital services [28]. Gadget-free communication will eliminate
physical devices while providing an omnipotential user en-
vironment through holograms, haptics and digital interfaces.
6
TABLE III: Technological developments, potential, challenges and solutions of the six disruptive technologies towards 6G
Technological Development Potential as an Enabling Technology Existing Challenges Possible Solutions
Intent-based Networking
IBN Controller
Automatic intent translation and conflict
resolution, optimization of network layout,
configuration, and activation strategy
Optimal deployment of the IBN controller
and enabling data processing in 6G Core
Network (CN) and RAN
Hybrid IBN controllers in centralized
cloud and edge, distributed data collection,
processing and resource optimization
Intent-driven Wireless Networks Intelligent and automatic intent translation
into network configuration
Issues related to data collection, data types,
model training, algorithm selection
AI model training infrastructure at the
appropriate network segments, efficient
model training and resource allocation
THz Communication
New Channel Models
Model THz communication in indoor ap-
plications or outdoor scenarios with ideal
conditions
Accurate channel model for all THz com-
munication scenarios not possible due to
very high absorption loss
Tiny cells deployment to address short
communication distance, efficient resource
and interference management schemes
Advanced Transceiver/antenna De-
signs
Transceiver and antenna design plays key
role to enable THz communication
Cost and power consumption of dedicated
RF components for individual antennas,
deployment of THz antennas
Hybrid beamforming solutions, high-gain
and fast-tracking antennas using nano ma-
terials
New MAC and networking Proto-
cols
Settle antenna directionality challenges,
enhance network performance via efficient
medium access schemes, THz line-of-sight
link selection
Issues in MAC and networking protocols
(interference management, adaptive beam-
forming, line-of-sight blockage, deafness)
Cross-layer MAC protocols to consider
user scheduling at the medium access layer
and path selection at the network layer
Artificial Intelligence
Data Sensing Process data acquired from millions of
devices
Large amounts of data processing can
overload the system, Continuous data
transmission decreases power efficiency
Use of AI at the sensor site for local
analysis or summarization to achieve better
energy efficiency
Spectrum sensing
Cognitive radios, spectrum sensing assist
users join network irrespective of their
primary affiliation
Primary users may get affected, power
consumption might increase due to contin-
uous scanning of available spectrum
Co-operative Spectrum Sensing that uses
AI technology can be used for efficient
utilization of frequency spectrum
Data Heterogeneity Connect devices varying in terms of sam-
ple rate, scientific metric, data type
Difficulty in data analysis due to varying
data types
AI allows data to be transformed in la-
tent/feature space for data analysis
DLT/BC
Smart Contracts
Softwarization of the clauses of agreement,
self-execution when predefined conditions
are reached, strict access control to data
No legal framework, difficult to understand
coded agreements, various kind of attacks
(DAO, Parity Multi-Sig Wallet, rubix)
Establish legal frameworks, develop and
use security and privacy preserving tools,
Formal methods to analyze vulnerabilities
Cryptographic Techniques Protect network resources and spectrum,
enhanced security and privacy
Secure key management using lightweight
protocol with minimum overheads, system
collapses if private key is captured
Quantum Key Distribution (QKD) for key
management, homomorphic and Attributed
Based Encryption (ABE) to protect privacy
Consensus Mechanisms Allow decentralized 6G ecosystem, offer
fault tolerance
High convergence time, lightweight smart
consensus algorithm design with high fault
tolerance
Smart consensus algorithm design
using environmental parameters, create
quantum-safe consensus mechanisms
Smart Devices and Gadgets
Further enhanced Mobile Broad-
band (FeMBB) and Mobile Broad-
Band and Low-Latency (MB-BLL)
Provide high data rates, high reliability and
ultra low latency network connectivity
Bandwidth limitations, poor network reli-
ability and availability
More bandwidth, VLC for low latency
communication, QC for ultra reliable com-
munication
Holographic Displays and Projec-
tors
Enable holographic communication,
gadget-free communication through
holograms, virtual tele-presence
Accurate representation of information,
gesture recognition, real-time processing
of large amounts of data
Light-field 3-D displays, 3-D touch-
sensing, edge intelligence for real-time
data processing
Edge Intelligence Provide smart devices with real-time ac-
cess to powerful computational resources
Network latency, data scarcity, data consis-
tency, incentive mechanisms, data security
and privacy
THz spectrum for better connectivity,
AI/swarm intelligence, DLT/BC for decen-
tralized resource management
Quantum Communication
Quantum enabled Communication
Potential to exploit laws of physics, i.e.,
photon states, to make communication
faster
Long-distance transmission of quantum
states
Polarization preserving quantum frequency
between atom and telecom photon to com-
municate over 20km through fiber
Quantum enabled IoT
Integration of computational components
incorporating quantum computers with
neuromorphic chips for fast computation
How to monitor and ensure quality ser-
vices from all devices
Quantum-Temporal Minimization Algo-
rithm to enhance temporal effectiveness,
performance, and quality of service
Quantum enabled Security
Quantum cryptography exploits the quan-
tum theory and its mechanism to enhance
secure end-to-end communications.
Important challenges such as distance, se-
cret key rate, size, and practical security.
Long distance QKD over fiber. In addition,
QKD extends the resulting of higher secret
key rates in wide area networks
User interactions will be detected through multiple sensors
capable of capturing user inputs such as voice, and gestures.
A. 6G Applicability
Smart devices and Gadget free communication is envisaged
to be a key technology direction towards 6G, as highlighted
in table I. SDG plays a key role in enabling futuristic 6G
applications as presented in table II. For instance, in Industry
5.0 applications, various cyber-physical systems are expected
to facilitate autonomous manufacturing in smart factory en-
vironments. These systems can be operated, monitored and
maintained through their digital-twin banking on technologies
such as XR and holographic communication. Furthermore,
healthcare applications connecting heterogeneous Intelligent
Internet of Medical Things (IIoMT) devices generate large
volumes of Big Data that needs to be processed using AI/ML
to facilitate advanced healthcare services. Hospital visits can
also be minimized using gadget free communication to cre-
ate a virtual presence of medical professionals for patients.
In addition, CAVs will self-charge, self-diagnose and self-
maintain connecting to the envisaged Energy Internet (EI) and
edge intelligence based services. UAVs are also expected to
7
be used in many areas including industrial, commercial, com-
munication, military and cinema environments. These UAVs
will be controlled using edge intelligence and Brain Computer
Interfaces (BCI) integrated with future 6G networks.
B. Deployment Challenges and Possible Solutions
SDG will burgeon owing to the advancements of electronics,
computing, smart screens, and more importantly, the envisaged
features through future 6G communication networks, such as,
extremely high data rates, extremely low latency, extremely
high reliability and availability, and edge intelligence [2]. The
SDG technological developments, challenges and solutions
towards 6G are tabulated in table III. Accordingly, multi-
core processors with advanced power management techniques
enable smart devices to drive multiple sensors and high
definition screens. Moreover, research and development work
are progressing towards realizing 360-degree transparent holo-
graphic screen displays. In addition, the network requirements
to facilitate SDG communication are expected to be realized
through developments in technologies such as THz spectrum,
Visible Light Communication (VLC), and Large Intelligent
Surfaces (LIS). Also, connecting an extremely large number
of smart devices, sensors and gadgets in a decentralized
manner to future 6G networks is expected to be a significant
challenge that is envisaged to be realized through DLT/BC and
zero touch network and service management technologies. In
addition, edge intelligence capabilities in future 6G networks
can be harnessed to process large amounts of data obtained
through many devices in real-time to provide advanced digital
services. Furthermore, efficient mechanisms are investigated
to ensure network security and user privacy in future 6G
networks with SDG.
VII. QUAN TU M COMMUNICATION
Quantum computing enabled communications has derived
a lot of research and development interests recently. Slowly
but beyond mere science fiction, QC will be a transformative
reality in the 6G paradigm in the next decade or so [29].
As 6G must meet stringent requirement, such as massive
data rates, fast computing, and strong security, QC will be
a potential enabler. The driving force of QC is that it exploits
traditional concepts of physics i.e., photons are being used to
process the computation to the quantum qubits [30]. These
qubits are then sent from a sender (or emitter) machine to
a receiver machine. Using flying qubits in communications
brings enormous advantages, such as, weak interaction with
an environment, faster computations and communications,
quantum teleportation, communication security, and low trans-
mission losses in communication [31]. These exciting features
will make QC one of key enabling technologies in 6G.
A. 6G Applicability
Researchers have been considering and developing QC-
enabled 6G use-cases that will reshape the future of communi-
cation. For instance, quantum optical network will complement
to achieve almost unlimited capacity of 6G mobile broadband
services. However, this would require advanced algorithms or
methods, such as advanced signal processing, that is capable of
performing the direct transformation of information between
THz and optical domains. Quantum technologies (e.g., based
on plasmonics modulators) would be an enabler in this re-
search direction [30]. One earliest work (i.e., [32]) proposed
an ultra-broadband plasmonic modulator that exploits the
applications of quantum-based technologies in communication
systems and networks. 6G research has ignited more inno-
vative techniques (e.g., quantum access network framework,
quantum switching, and QC-enabled AI) and will continue to
develop to realize QC-enabled 6G services. For instance, in
[33] Granelli et al. proposed a new architecture that would
enable future classical-quantum communication for future
networks. The architecture employs the idea of softwariza-
tion (through software define network, and network function
virtualization). It combines mainly 4G and 5G enabled mobile-
broadband/Internet, and three- dimensional (i.e., data, control
and quantum capabilities) of 6G communication networks via
quantum physical layer. The main benefits of this architecture
would be the representation of quantum and legacy Internet as
a single controlled and independent-integrated entity. Equally,
QC will facilitate the communication requirements of IoE
where millions of devices will be employed to collect data
and demand reliable, unreliable, and low-cost communication
technologies. However, designing, developing, and standard-
izing new security architectures, encryption standards, and
data security mechanisms for quantum computing is yet to
be progressed [34].
B. Deployment Challenges and Possible Solutions
Realization of QC for 6G applications imposes significant
challenges in predicting QC solutions, services and applica-
tions. One fundamental challenge is long-distance transmission
of the quantum states. However, the states of quantum qubits
can play a paramount role due to their robustness to noise
and capacity to carry information is high. The implementation
of quantum states is not easy due to many reasons including
limited resources, and lack of enough practical knowledge.
Some theoretical areas are also yet to be properly explored.
Another challenge is optical quantum memory storage. Many
researches have already proved the capacity to store multidi-
mensional states in quantum memories is possible. However,
very few researchers have shown the adaptability within the
external qubit sources and high-dimensional states stored in
quantum memories. In addition, the data accuracy will be
challenging in 6G enabled IoE. Recent innovations of quantum
computing-inspired optimization (QCiO) have provided new
paths for achieving data accuracy for real-world applications.
In [35], the authors presented an QCiO to acquire IoT sensor
data in the quantum form and achieved high data accuracy
and data temporal efficiency. Yet another interesting challenges
of quantum-based security solutions (e.g., QKD) are whether
they are viable to resource-constrained IoE devices. However,
QKD has its own challenges such as secret key rate (few
Mbps), distance (few 100s Km), and practical and formal
security verification. Therefore, new insights are needed to
8
be explored on quantum-based security solutions and their
viability in resource-constrained environments.
VIII. CONCLUSION
This paper focuses on six technological directions towards
realizing 6G, the next generation of mobile networks. These
technological directions are IBN, THz communication, AI,
DLT/BC, smart devices and gadget-free communication, and
quantum communication. It is evident that that the six tech-
nological directions elaborated in this paper are expected to
play a major role towards the realization of 6G. The paper
presents technological developments, 6G applicability, exist-
ing challenges and possible solutions under each technology
direction. Accordingly, the proposed solutions can be explored
towards overcoming some of the existing challenges towards
developing 6G mobile networks. It is also envisaged that
the paper will pave the path to focus future research and
development work towards the six technological directions
discussed in this paper to realize 6G in the coming decade.
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Chamitha de Alwis is a Lecturer in University of Bedfordshire, United
Kingdom and a Senior Lecturer in University of Sri Jayewardenepura, Sri
Lanka. He also works as a Consultant in the areas of telecommunication,
and network security. His research interests include 5G, 6G, blockchain, and
network security.
9
Pardeep Kumar is working with Swansea University, United Kingdom.
His research interests are security and privacy in Internet of things, smart
environment, edge computing, blockchain and network security.
Quoc-Viet Pham [M’18] (vietpq@pusan.ac.kr) is working at Pusan National
University, Korea. He received the best PhD thesis award in Engineering from
Inje University in 2017. His research interests include network optimization,
edge computing, resource allocation, and wireless AI.
Kapal Dev is senior research associate at University of Johannesburg, South
Africa. He is AE in Springer WINE, Elsevier PhyCom, IET Quantum
Communication, IET Networks &MDPI Network. He is GE in Q1 journals;
IEEE TNSE, TII, TGCN, Elsevier COMCOM &COMNET. He served(ing)
as Lead chair in MobiCom, Globecom, PIMRC, &CCNC 2021 workshops.
Anshuman Kalla is Professor at CGPIT, Uka Tarsadia University, India.
His research interests are blockchain, next generation networks - 5G/6G, and
network security.
Madhusanka Liyanage (S07, M16, SM20) is a lecturer/assistant professor at
University College Dublin, Ireland. His research interests are network security,
softwarized networks, edge computing, 5G/6G, and blockchain.
Won-Joo Hwang [SM’17] (wjhwang@pusan.ac.kr) received the Ph.D. degree
from Osaka University, Japan, in 2002. Currently, he is with the Department of
Biomedical Convergence Engineering, Pusan National University, Korea. His
research interests include optimization theory, game theory, machine learning
and data science for wireless communications and networking.
