A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems

02/26/2019 ∙ by Walid Saad, et al. ∙ University of Oulu Virginia Polytechnic Institute and State University 0

The ongoing deployment of 5G cellular systems is continuously exposing the inherent limitations of this system, compared to its original premise as an enabler for Internet of Everything applications. These 5G drawbacks are currently spurring worldwide activities focused on defining the next-generation 6G wireless system that can truly integrate far-reaching applications ranging from autonomous systems to extended reality and haptics. Despite recent 6G initiatives1, the fundamental architectural and performance components of the system remain largely undefined. In this paper, we present a holistic, forward-looking vision that defines the tenets of a 6G system. We opine that 6G will not be a mere exploration of more spectrum at high-frequency bands, but it will rather be a convergence of upcoming technological trends driven by exciting, underlying services. In this regard, we first identify the primary drivers of 6G systems, in terms of applications and accompanying technological trends. Then, we propose a new set of service classes and expose their target 6G performance requirements. We then identify the enabling technologies for the introduced 6G services and outline a comprehensive research agenda that leverages those technologies. We conclude by providing concrete recommendations for the roadmap toward 6G. Ultimately, the intent of this article is to serve as a basis for stimulating more out-of-the-box research around 6G.

READ FULL TEXT VIEW PDF
POST COMMENT

Comments

There are no comments yet.

Authors

page 2

page 6

page 7

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.

I Introduction

To date, the wireless network evolution was primarily driven by an incessant need for higher data rates, which mandated a continuous 1000x increase in the network capacity. While this demand for wireless capacity will continue to grow, the emergence of the Internet of Everything (IoE) system, connecting millions of people and billions of machines, is yielding a radical paradigm shift from the rate-centric enhanced mobile broadband (eMBB) services of yesteryears towards ultra-reliable, low latency communications (URLLC).

Although the fifth generation (5G) cellular system [2] was marketed as the key IoE enabler, through concerted 5G standardization efforts that led to the first 5G new radio (5G NR) milestone (for non-standalone 5G) and subsequent 3GPP releases, the initial premise of 5G – as a true carrier of IoE services – is yet to be realized. One can argue that the evolutionary part of 5G (i.e., supporting rate-hungry eMBB services) has gained significant momentum, however, the promised revolutionary outlook of 5G – a system operating almost exclusively at millimeter wave (mmWave) frequencies and enabling heterogeneous IoE services – has thus far remained a mirage. Although the 5G systems that are currently being marketed will readily support basic IoE and URLLC services (e.g., factory automation), it is debatable whether they can deliver the tomorrow’s smart city IoE applications. Moreover, even though 5G will eventually support fixed-access at mmWave frequencies, it is more likely that early 5G roll-outs will be centered around sub-6 GHz, especially for supporting mobility.

Meanwhile, an unprecedented proliferation of new IoE services is ongoing. Examples range from eXtended reality (XR) services (encompassing augmented, mixed, and virtual reality (AR/MR/VR)) to telemedicine, haptics, flying vehicles, brain-computer interfaces, and connected autonomous systems. These applications will disrupt the original 5G goal of supporting short-packet, sensing-based URLLC services. To successfully operate IoE services such as XR and connected autonomous systems, a wireless system must simultaneously deliver high reliability, low latency, and high data rates, for heterogeneous devices, across uplink and downlink. Emerging IoE services will also require an end-to-end co-design of communication, control, and computing functionalities, which to date has been largely overlooked. To cater for this new breed of services, unique challenges must be addressed ranging from characterizing the fundamental rate-reliability-latency tradeoffs governing their performance to exploiting frequencies beyond sub-6 GHz and transforming wireless systems into a self-sustaining, intelligent network fabric which flexibly provisions and orchestrates communication-computing-control-localization-sensing resources tailored to the requisite IoE scenario.

To overcome these challenges and catalyze the deployment of new IoE services, a disruptive sixth generation (6G)

wireless system, whose design is inherently tailored to the performance requirements of the aforementioned IoE applications and their accompanying technological trends, is needed. The drivers of 6G will be a confluence of past trends (e.g., densification, higher rates, and massive antennas) and of emerging trends that include new services and the recent revolution in wireless devices (e.g., smart wearables, implants, XR devices, etc.), artificial intelligence (AI), computing, sensing, and 3D environmental mapping.

Fig. 1: 6G Vision: Applications, Trends, and Technologies.

The main contribution of this article is a bold, forward-looking vision of 6G systems (see Fig. 1) that identifies the applications, trends, performance metrics, and disruptive technologies, that will drive the 6G revolution. The proposed vision will then delineate new 6G services and provide a concrete research roadmap and recommendations to facilitate the leap from current 5G systems towards 6G.

Ii 6G Driving Applications, Metrics, and New Service Classes

Every new cellular system generation is driven by innovative applications. 6G is no exception: It will be borne out of an unparalleled emergence of exciting new applications and technological trends that will shape its performance targets while radically redefining standard 5G services. In this section, we first introduce the main applications that motivate 6G deployment and, then, discuss ensuing technological trends, target performance metrics, and new service requirements.

Ii-a Driving Applications behind 6G and their Requirements

While traditional applications, such as live multimedia streaming, will remain central to 6G, the key determinants of the system performance will be four new application domains:

Ii-A1 Multisensory XR Applications

XR will yield many killer applications for 6G across the AR/MR/VR spectrum. Upcoming 5G systems still fall short of providing a full immersive XR experience capturing all sensory inputs due to their inability to deliver very low latencies for data-rate intensive XR applications. A truly immersive AR/MR/VR experience requires a joint design integrating not only engineering (wireless, computing, storage) requirements but also perceptual requirements stemming from human senses, cognition, and physiology. Minimal and maximal perceptual requirements and limits must be factored into the engineering process (computing, processing, etc.). To do so, a new concept of quality-of-physical-experience (QoPE) measure is needed to merge physical factors from the human user itself with classical QoS (e.g., latency and rate) and QoE (e.g., mean-opinion score) inputs. Some factors that affect QoPE include brain cognition, body physiology, and gestures. As an example, in [9], we have shown that the human brain may not be able to distinguish between different latency measures, when operating in the URLLC regime. Meanwhile, in [11], we showed that visual and haptic perceptions are key for maximizing wireless resource utilization. Concisely, the requirements of XR services are a blend of traditional URLLC and eMBB with incorporated perceptual factors that 6G must support.

Ii-A2 Connected Robotics and Autonomous Systems (CRAS)

A primary driver behind 6G systems is the imminent deployment of CRAS including drone-delivery systems, autonomous cars, autonomous drone swarms, vehicle platoons, and autonomous robotics. The introduction of CRAS over the cellular domain is not a simple case of “yet another short packet uplink IoE service”. Instead, CRAS mandate control system-driven latency requirements as well as the potential need for eMBB transmissions of high definition (HD) maps. The notion of QoPE applies once again for CRAS; however, the physical environment is now a control system, potentially augmented with AI. CRAS are perhaps a prime use case that requires stringent requirements across the rate-reliability-latency spectrum; a balance that is not yet available in 5G.

Ii-A3 Wireless Brain-Computer Interactions (BCI)

Beyond XR, tailoring wireless systems to their human user is mandatory to support services with direct BCI. Traditionally, BCI applications were limited to healthcare scenarios in which humans can control prosthetic limbs or neighboring computing devices using brain implants. However, the recent advent of wireless brain-computer interfaces and implants will revolutionize this field and introduce new use-case scenarios that require 6G connectivity. Such scenarios range from enabling brain-controlled movie input to fully-fledged multi-brain-controlled cinema [15]. Using wireless BCI technologies, instead of smartphones, people will interact with their environment and other people using discrete devices, some worn, some implanted, and some embedded in the world around them. This will allow individuals to control their environments through gestures and communicate with loved ones through haptic messages. Such empathic and haptic communications, coupled with related ideas such as affective computing in which emotion-driven devices can match their functions to their user’s mood, will constitute important 6G use cases. Wireless BCI services will require fundamentally different performance metrics compared to what 5G delivers. Similar to XR, wireless BCI services need high rates, ultra low latency, and high reliability. However, they are much more sensitive than XR to physical perceptions and will necessitate QoPE guarantees.

Ii-A4 Blockchain and Distributed Ledger Technologies (DLT)

Blockchains and DLT will be one of the most disruptive IoE technologies. Blockchain and DLT applications can be viewed as the next-generation of distributed sensing services whose need for connectivity will require a synergistic mix of URLLC and massive machine type communications (mMTC) to guarantee low-latency, reliable connectivity, and scalability.

Ii-B 6G: Driving Trends and Performance Metrics

The applications of Section II-A lead to new system-wide trends that will set the goals for 6G:

  • Trend 1 – More Bits, More spectrum, More Reliability: Most of the driving applications of 6G require higher bit rates than 5G. To cater for applications such as XR and BCI, 6G must deliver yet another 1000x increase in data rates yielding a target of around 1 Terabit/second. This motivates a need for more spectrum resources, hence motivating further exploration of frequencies beyond sub-6 GHz. Meanwhile, the need for higher reliability will be pervasive across most 6G applications and will be more challenging to meet at high frequencies.

  • Trend 2 – From Spatial to Volumetric Spectral and Energy Efficiency: 6G must deal with ground and aerial users, encompassing smartphones and XR/BCI devices along with flying vehicles. This 3D nature of 6G requires an evolution towards a volumetric rather than spatial bandwidth definition. We envision that 6G systems must deliver high spectral and energy efficiency (SEE) requirements measured in bps/Hz/m/Joules. This is a natural evolution that started from 2G (bps) to 3G (bps/Hz), then 4G (bps/Hz/m) to 5G (bps/Hz/m/Joules).

  • Trend 3 – Emergence of Smart Surfaces and Environments: Current and past cellular systems used base stations (of different sizes and forms) for transmission. We are currently witnessing a revolution in electromagnetically active surfaces (e.g., using metamaterials) that include man-made structures such as walls, roads, and even entire buildings, as exemplified by the Berkeley ewallpaper project222See https://bwrc.eecs.berkeley.edu/projects/5605/ewallpaper.. The use of such smart large intelligent surfaces and environments for wireless communications will drive the 6G architectural evolution.

  • Trend 4 – Massive Availability of Small Data:

    The data revolution will continue in the near future and shift from centralized, big data, towards massive, distributed “small” data. 6G systems must harness both big and small datasets across their infrastructure to enhance network functions and provide new services. This trend motivates new machine learning and data analytics techniques that go beyond classical big data.

  • Trend 5 – From Self-Organizing Networks (SON) to Self-Sustaining Networks: SON has only been scarcely integrated into 4G/5G networks due to a lack of real-world need. However, CRAS and DLT technologies motivate an immediate need for intelligent SON to manage network operations, resources, and optimization. 6G will require a paradigm shift from classical SON, whereby the network merely adapts its functions to specific environment states, into a self-sustaining network (SSN) that can maintain its key performance indicators (KPIs), in perpetuity, under highly dynamic and complex environments stemming from the rich 6G application domains. SSNs must be able to not only adapt their functions but to also sustain their resource usage and management (e.g., by harvesting energy and exploiting spectrum) to autonomously maintain high, long-term KPIs. SSN functions must leverage the recent revolution in AI technologies to create AI-powered 6G SSNs.

  • Trend 6 – Convergence of Communications, Computing, Control, Localization, and Sensing (3CLS): The past five generations of cellular systems had one exclusive function: wireless communications. However, the convergence of various technologies requires 6G to disrupt this premise by providing multiple functions that include communications, computing, control, localization, and sensing. We envision 6G as a multi-purpose system that can deliver multiple 3CLS services which are particularly appealing and even necessary for applications such as XR, CRAS, and DLT where tracking, control, localization, and computing are an inherent feature. Moreover, sensing services will enable 6G systems to provide users with a 3D mapping of the radio environment across different frequencies. Hence, 6G systems must tightly integrate and manage 3CLS functions.

  • Trend 7 – End of the Smartphone Era: Smartphones were central to 4G and 5G. However, recent years witnessed an increase in wearable devices whose functionalities are gradually replacing those of smartphones. This trend is further fueled by applications such as XR and BCI. The devices associated with those applications range from smart wearables to integrated headsets and smart body implants that can take direct sensory inputs from human senses; bringing an end to smartphones and potentially driving a majority of 6G use cases.

As shown in Table I, collectively, these trends impose new performance targets and requirements on next-generation wireless systems that will be met in two stages: a) A major beyond 5G evolution and b) A revolutionary step towards 6G.

5G Beyond 5G 6G
Application Types eMBB. Reliable eMBB. New applications (see Section II-C):
URLLC. URLLC. MBRLLC.
mMTC. mMTC. mURLLC.
Hybrid (URLLC + eMBB). HCS.
MPS.
Device Types Smartphones. Smartphones. Sensors and DLT devices.
Sensors. Sensors. CRAS.
Drones. Drones. XR and BCI equipment.
XR equipment. Smart implants.
Spectral and Energy Efficiency Gains with Respect to Today’s Networks 10x in bps/Hz/m 100x in bps/Hz/m 1000x in bps/Hz/m (volumetric)
Rate Requirements 1 Gbps 100 Gbps 1 Tbps
End-to-End Delay Requirements 5 ms 1 ms < 1 ms
Radio-Only Delay Requirements 100 ns 100 ns 10 ns
Processing Delay 100 ns 50 ns 10 ns
End-to-End Reliability Requirements Five 9s Six 9s Seven 9s
Frequency Bands Sub-6 GHz. Sub-6 GHz. Sub-6 GHz.
MmWave for fixed access. MmWave for fixed access at 26 GHz and 28GHz. MmWave for mobile access.
Exploration of THz bands (above 140 GHz).
Non-RF (e.g., optical, VLC, etc.).
Architecture Dense sub-6 GHz small base stations with umbrella macro base stations. Denser sub-6 GHz small cells with umbrella macro base stations. Cell-free smart surfaces at high frequency supported by mmWave tiny cells for mobile and fixed access.
< 100 m tiny and dense mmWave cells.
MmWave small cells of about 100 m (for fixed access). Temporary hotspots served by drone-carried base stations or tethered balloons.
Trials of tiny THz cells.
TABLE I: Requirements of 5G vs. Beyond 5G vs. 6G.

Ii-C New 6G Service Classes

Beyond imposing new performance metrics, the new technological trends will redefine 5G application types by morphing classical URLLC, eMBB, and mMTC and introducing new services (summarized in Table II), as follows:

Ii-C1 Mobile Broadband Reliable Low Latency Communication

As evident from Section II-B, the distinction between eMBB and URLLC will no longer be sustainable to support applications such as XR, wireless BCI, or CRAS. This is because these applications require, not only high reliability and low latency but also high 5G-eMBB-level data rates. Hence, we propose a new service class called mobile broadband reliable low latency communication (MBRLLC) that allows 6G systems to deliver any required performance within the rate-reliability-latency space. As seen in Fig. 2, MBRLLC generalizes classical URLLC and eMBB services. Energy efficiency is central for MBRLLC, not only because of its impact on reliability and rate, but also because 6G devices will continue to shrink in size and increase in functionality.

Fig. 2: MBRLLC services and several special cases (including classical eMBB and URLLC) within the rate-reliability-latency space. Other involved, associated metrics that are not shown include energy and network scale.

Ii-C2 Massive URLLC

5G URLLC meant meeting reliability and latency of very specific uplink IoE applications such as smart factories,, for which prior work [6] provided the needed fundamentals. However, 6G must scale classical URLLC across the device dimension thereby leading to a new massive URLLC (mURLLC) service that merges 5G URLLC with legacy mMTC. mURLLC brings forth a reliability-latency-scalability tradeoff which mandates a major departure from average-based network designs (e.g., average throughput/delay). Instead, a principled and scalable framework which accounts for delay, reliability, packet size, network architecture, topology (across access, edge, and core) and decision-making under uncertainty is necessary [1].

Ii-C3 Human-Centric Services

We propose a new class of 6G services, dubbed human-centric services (HCS), that primarily require QoPE targets (tightly coupled with their human users, as explained in Section II-A) rather than raw rate-reliability-latency metrics. Wireless BCI are a prime example of HCS in which network performance is determined by the physiology of the human users and their actions. For such services, a whole new set of QoPE metrics must be defined and offered as function of raw QoS and QoE metrics.

Ii-C4 Multi-Purpose 3CLS and Energy Services

6G systems must jointly deliver 3CLS services and their derivatives. They can also potentially offer energy to small devices via wireless energy transfer. Such multi-purpose 3CLS and energy services (MPS) will be particularly important for applications such as CRAS. MPS require joint uplink-downlink designs and must meet target performance for the control (e.g., stability), computing (e.g., computing latency), energy (e.g., target energy to transfer), localization (e.g., localization precision), as well as sensing and mapping functions (e.g., accuracy of a mapped radio environment).

Service Performance Indicators Example Applications
MBRLLC Stringent rate-reliability-latency requirements. XR/AR/VR.
Energy efficiency. Autonomous vehicular systems.
Rate-reliability-latency in mobile environments. Autonomous drones.
Legacy eMBB and URLLC.
mURLLC Ultra high reliability. Classical Internet of Things.
Massive connectivity. User tracking.
Massive reliability. Blockchain and DLT.
Scalable URLLC. Massive sensing.
Autonomous robotics.
HCS QoPE capturing raw wireless metrics as well as human and physical factors. BCI.
Haptics.
Empathic communication.
Affective communication.
MPS Control stability. CRAS.
Computing latency. Telemedicine.
Localization accuracy. Environmental mapping and imaging.
Sensing and mapping accuracy. Some special cases of XR services.
Latency and reliability for communications.
Energy.
TABLE II: Summary of 6G service classes, their performance indicators, and example applications.

Iii 6G: Enabling Technologies

To enable the aforementioned services and guarantee their performance, a cohort of new, disruptive technologies must be integrated into 6G.

Iii-1 Above 6 GHz for 6G – from Small Cells to Tiny Cells

As per Trends 1 and 2, the need for higher data rates and SEE anywhere, anytime in 6G motivates exploring higher frequency bands beyond sub-6 GHz. As a first step, this includes further developing mmWave technologies to make mobile mmWave a reality in early 6G systems. As 6G progresses, exploiting frequencies beyond mmWave, at the terahertz (THz) band, will become necessary [14]. To exploit higher mmWave and THz frequencies, the size of the 6G cells must shrink from small cells to “tiny cells” whose radius is only a few tens meters. This motivates new architectural designs that need much denser deployments of tiny cells and new high-frequency mobility management techniques.

Iii-2 Transceivers with Integrated Frequency Bands

On their own, dense high-frequency tiny cells may not be able to provide the seamless connectivity required for mobile 6G services. Instead, an integrated system that can leverage multiple frequencies across the microwave/mmWave/THz spectra (e.g., using multi-mode base stations) is needed to provide seamless connectivity at both wide and local area levels.

Iii-3 Communication with Large Intelligent Surfaces

Massive MIMO will be integral to both 5G and 6G due to the need for better SEE, higher data rates, and higher frequencies (Trend 1). However, for 6G systems, as per Trend 3, we envision an initial leap from traditional massive MIMO towards large intelligent surfaces (LISs) and smart environments [7] that can provide massive surfaces for wireless communications and for heterogeneous devices (Trend 7). LISs enable innovative ways for communication such as by using holographic radio frequency (RF) and holographic MIMO. LISs will likely play a basic role in early 6G roll-outs and become more central as 6G matures.

Iii-4 Edge AI

AI is witnessing an unprecedented interest from the wireless community [4]

driven by recent breakthroughs in deep learning, the increase in available data (Trend 4), and the rise of smart devices (Trend 7). Imminent 6G use cases for AI (particularly for reinforcement learning) revolve around creating SSNs (Trend 5) that can autonomously sustain high KPIs and manage resources, functions, and network control. AI will also enable 6G to automatically provide MPS to its users and to send and create 3D radio environment maps (Trend 6). These short-term AI-enabled 6G functions will be complemented by a so-called “collective network intelligence” in which network intelligence is pushed at the edge, running AI algorithms and machine learning on edge devices (Trend 7) to provide distributed autonomy. This new edge AI leap will create a 6G system that can integrate the services of Section

II, realize 3CLS, and potentially replace classical frame structures.

Iii-5 Integrated Terrestrial, Airborne, and Satellite Networks

Beyond their inevitable role as users of 6G systems, drones can be leveraged to complement ground, terrestrial networks by providing connectivity to hotspots and to areas in which infrastructure is scarce. Meanwhile, both drones and terrestrial base stations may require satellite connectivity with low orbit satellites (LEO) and CubeSats to provide backhaul support and additional wide area coverage. Integrating terrestrial, airborne, and satellite networks [10] and [3] into a single wireless system will be essential for 6G.

Iii-6 Energy Transfer and Harvesting

6G could be the first generation of cellular systems that can provide energy, along with 3CLS (Trend 6). As wireless energy transfer is maturing, it is plausible to foresee 6G base stations providing basic power transfer for devices, particularly implants and sensors (Trend 7). Adjunct energy-centric ideas, such as energy harvesting (from RF or renewable sources) and backscatter will also be a component of 6G.

Iii-7 Beyond 6G

A handful of technologies will mature along the same time of 6G and, hence, potentially play a role towards the end of the 6G standardization and research process. One prominent example is quantum computing and communications that can provide security and long-distance networking. Currently, major research efforts are focused on the quantum realm and we expect them to intersect with 6G. Other similar beyond 6G technologies include integration of RF and non-RF links (including optical, neural, molecular, and other channels).

Iv 6G: Research Agenda and Open Problems

Fig. 3: Necessary foundations and associated analytical tools for 6G.

Building on the identified trends in Section II and the enabling technologies in Section III, we now put forward a research agenda for 6G along with selected open problems (summarized in Table III).

Iv-1 3D Rate-Reliability-Latency Fundamentals

Fundamental 3D performance of 6G systems, in terms of rate-reliability-latency tradeoffs and SEE is needed. Such analysis must quantify the spectrum, energy, and communication requirements that 6G needs to support the identified driving applications. Recent works in [1] and [8] provide a first step in this direction.

Iv-2 Exploring Integrated, Heterogeneous High-Frequency Bands

Exploiting mmWave and THz in 6G brings forth several new open problems from hardware to system design. For mmWave, supporting high mobility at mmWave frequencies will be a central open problem. Meanwhile, for THz, new transceiver architectures are needed along with new THz propagation models [14]. High power, high sensitivity, and low noise figure are key transceiver features needed to overcome the very high path-loss at THz frequencies. Once these physical layer aspects are well-understood, developing new multiple access and networking paradigms under the highly varying and mobile mmWave and THz environments is necessary. Another important research direction is to study the co-existence of THz, mmWave, and microwave cells across all layers, building on early works such as [13].

Iv-3 3D Networking

Due to the integration of ground and airborne networks, as outlined in Section III, 6G must support communications in 3D space, including serving users in 3D and deploying 3D base stations (e.g., tethered balloons or temporary drones). This, in turn, requires concerted research on various fronts. First, measurement and (data-driven) modeling of the 3D propagation environment is needed. Second, new approaches for 3D frequency and network planning (e.g., where to deploy base stations, tethered balloons, or even drone-base stations) must be developed. Our work in [10]

already showed that such 3D planning is substantially different from conventional 2D networks due to the new altitude dimension and the associated degrees of freedom. Finally, new network optimizations for mobility management, multiple access, routing, and resource management in 3D are needed.

Iv-4 Communication with LIS

As per Trend 3, 6G will provide wireless connectivity via smart LIS environments that include active frequency selective surfaces, metallic passive reflectors, passive/active reflect arrays, as well as nonreconfigurable and reconfigurable metasurfaces. Open research problems here range from the optimized deployment of passive reflectors and metasurfaces to AI-powered operation of reconfigurable LIS. Fundamental analysis to understand the performance of LIS and smart surfaces, in terms of rate, latency, reliability, and coverage is needed, building on the early works in [7]. Another important research direction is to investigate the potential of using LIS-based reflective surfaces to enhance the range and coverage of tiny cells and to dynamically modify the propagation environment. Using LIS for wireless energy transfer is also an interesting direction.

Iv-5 AI for Wireless

AI brings forward many major research directions for 6G. Beyond the need for massive, small data analytics as well as using machine learning (ML) and AI-based SSNs (realized using reinforcement learning and game theory), there is also a need to operate ML algorithms reliably over 6G to deliver the applications of Section

II. To perform these critical application tasks, low-latency, high-reliability and scalable AI is needed, along with a reliable infrastructure [4] and [12]. This joint design of ML and wireless networks is an important area of research for 6G.

Iv-6 QoPE Metrics

The design of QoPE metrics that integrate physical factors from human physiology (for HCS services) or from a control system (for CRAS) is an important 6G research area, especially in light of new, emerging devices (Trend 7). This requires both real-world psychophysics experiments as well as new, rigorous mathematical expressions for QoPE that combine QoS, QoE, and human perceptions. Theoretical development of QoPE can be achieved using techniques from other disciplines such as operations research (e.g., multi-attribute utility theory (see [5])) and machine learning (see [9]). 6G will be the first generation to enable a new breed of applications (wireless BCI) leveraging multiple human cognitive senses.

Iv-7 Joint Communication and Control

6G needs to pervasively support CRAS. The performance of CRAS is governed by real-world control systems whose operation requires data input from wireless 6G links. Therefore, operating CRAS over 6G systems requires a communication and control co-design, whereby the performance of the 6G wireless links is optimized to cater for the stability of the control system and vice versa. Due to the traditional radio-centric focus (3GPP and IEEE fora), such a co-design has been overlooked in 5G. Meanwhile, prior works on networked control abstract the specifics of the wireless network and cannot apply to cellular communications. This makes the communication-control co-design a key research topic in 6G.

Iv-8 3cls

The idea of joint communication and control must be extended to the joint design of the entire 3CLS functions. The interdependence between computing, communication, control, localization, sensing, energy, and mapping has not yet been fully explored in an end-to-end manner. Key questions range from how to jointly meet the performance of all 3CLS services to multi-modal sensor fusion for reconstructing 3D images and navigating in unknown environments for navigating robots, autonomous driving, etc. 3CLS is needed for various applications including CRAS, XR, and DLT.

Iv-9 RF and non-RF Link Integration

6G will witness a convergence of RF and non-RF links that encompass optical, visible light communication (VLC), molecular communication, and neuro-communication, among others. Design of such joint RF/non-RF systems is an open research area.

Iv-10 Holographic Radio

RF holography (including holographic MIMO) and spatial spectral holography can be made possible with 6G due to the use of LIS and similar structures. Holographic RF allows for control of the entire physical space and the full closed loop of the electromagnetic field through spatial spectral holography and spatial wave field synthesis. This greatly improves spectrum efficiency and network capacity, and helps the integration of imaging and wireless communication. How to realize holographic radio is a widely open area.

An overview on the necessary analytical tools and fundamentals related to these open research problems is shown in Fig. 3.

Research Area Challenges Open Problems
3D Rate-Reliability-Latency Fundamentals Fundamental communication limits. 3D performance analysis of rate-reliability-latency region.
3D nature of 6G systems. Characterization of achievable rate-reliability-latency targets.
3D SEE characterization.
Characterization of energy and spectrum needs for rate-reliability-latency targets.
Exploring Integrated, Heterogeneous High-Frequency Bands Challenges of operation in highly mobile systems. Effective mobility management for mmWave and THz systems.
Susceptibility to blockage. Cross-band physical, link, and network layer optimization.
Short range. Coverage and range improvement.
Lack of propagation models. Design of mmWave and THz tiny cells.
Need for high fidelity hardware. Design of new high fidelity hardware for THz.
Co-existence of frequency bands. Propagation measurements and modeling across mmWave and THz bands.
3D Networking Presence of users and base stations in 3D. 3D propagation modeling.
High mobility. 3D performance metrics.
3D mobility management and network optimization.
Communication with LIS Complex nature of LIS surfaces. Optimal deployment and location of LIS surfaces.
Lack of existing performance models. LIS reflectors vs. LIS base stations.
Lack of propagation models. LIS for energy transfer.
Heterogeneity of 6G devices and services. AI-enabled LIS.
Ability of LIS to provide different functions (reflectors, base stations, etc.). LIS across 6G services.
Fundamental performance analysis of LIS transmitters and reflectors at various frequencies.
AI for Wireless Design of low-complexity AI solutions. Reinforcement learning for SON.
Massive, small data. Big and small data analytics.
AI-powered network management.
Edge AI over wireless systems.
New QoPE Metrics Incorporate raw metrics with human perceptions. Theoretical development of QoPE metrics.
Accurate modeling of human perceptions and physiology. Empirical QoPE characterization.
Real psychophysics experiments.
Definition of realistic QoPE targets and measures.
Joint Communication and Control Integration of control and communication metrics. Communication and control systems co-design.
Handling dynamics and multiple time scales. Control-enabled wireless metrics.
Wireless-enabled control metrics.
Joint optimization for CRAS.
3CLS Integration of multiple functions. Design of 3CLS metrics.
Lack of prior models. Joint 3CLS optimization.
AI-enabled 3CLS.
Energy efficient 3CLS.
RF and non-RF Link Integration Different physical nature of RF/non-RF interfaces. Design of joint RF/non-RF hardware.
System-level analysis of joint RF/non-RF systems.
Use of RF/non-RF systems for various 6G services.
Holographic Radio Lack of existing models. Design of holographic MIMO using LIS.
Hardware and physical layer challenges. Performance analysis of holographic RF.
3CLS over holographic radio.
Network optimization with holographic radio.
TABLE III: Summary of Research Areas

V Conclusion and Recommendations

This article laid out a bold new vision for 6G systems that outlines the trends, challenges and associated research. While many topics will come as a natural 5G evolution, new avenues of research such as LIS-communication, 3CLS, holographic radio, and others will create an exciting research agenda for the next decade. To conclude, several recommendations are in order:

  • Recommendation 1: A first step towards 6G is to enable MBRLLC and mobility management at high-frequency mmWave bands and beyond (i.e., THz).

  • Recommendation 2: 6G requires a move from radio-centric system design (à-la-3GPP) towards an end-to-end co-design 3CLS under the orchestration of an AI-driven intelligence substrate.

  • Recommendation 3: The 6G vision will not be a simple case of exploring additional, high-frequency spectrum bands to provide more capacity. Instead, it will be driven by a diverse portfolio of applications, technologies, and techniques (see Figs. 1 and 3).

  • Recommendation 4: 6G will transition from the smartphone-base station paradigm into a new era of smart surfaces communicating with human-embedded implants.

  • Recommendation 5: Performance analysis and optimization of 6G requires operating in 3D space and moving away from simple averaging towards fine-grained analysis that deals with tails, distributions, and QoPE.

References

  • [1] M. Bennis, M. Debbah, and H. V. Poor (2018-10) Ultrareliable and low-latency wireless communication: Tail, risk, and scale. Proceedings of the IEEE 106 (10), pp. 1834–1853. Cited by: §II-C2, §IV-1.
  • [2] F. Boccardi, R. W. Heath, A. Lozano, T. L. Marzetta, and P. Popovski (2014-02) Five disruptive technology directions for 5G. IEEE Communications Magazine 52 (2), pp. 74–80. Cited by: §I.
  • [3] X. Cao, S. Kim, K. Obraczka, C. Wang, D. O. Wu, and H. Yanikomeroglu (2018-Sep.) Guest editorial airborne communication networks. IEEE Journal on Selected Areas in Communications 36 (9), pp. 1903–1906. Cited by: §III-5.
  • [4] M. Chen, U. Challita, W. Saad, C. Yin, and M. Debbah (2017-Oct.)

    Machine learning for wireless networks with artificial intelligence: a tutorial on neural networks

    .
    available online: arxiv.org/abs/1710.02913. Cited by: §III-4, §IV-5.
  • [5] M. Chen, W. Saad, and C. Yin (2018-11) Virtual reality over wireless networks: quality-of-service model and learning-based resource management. IEEE Transactions on Communications 66 (11), pp. 5621–5635. External Links: ISSN 0090-6778 Cited by: §IV-6.
  • [6] G. Durisi, T. Koch, and P. Popovski (2016-Sep.) Toward massive, ultrareliable, and low-latency wireless communication with short packets. Proceedings of the IEEE 104 (9), pp. 1711–1726. Cited by: §II-C2.
  • [7] S. Hu, F. Rusek, and O. Edfors (2018-05) Beyond massive MIMO: The potential of data transmission with large intelligent surfaces. IEEE Transactions on Signal Processing 66 (10), pp. 2746–2758. Cited by: §III-3, §IV-4.
  • [8] A. T. Z. Kasgari and W. Saad (2019-05) Model-free ultra reliable low latency communication (URLLC): A deep reinforcement learning framework. In Proc. of the IEEE International Conference on Communications (ICC), Shanghai, China. Cited by: §IV-1.
  • [9] A. T. Z. Kasgari, W. Saad, and M. Debbah (2018-03) Human-in-the-loop wireless communications: Machine learning and brain-aware resource management. arXiv preprint arXiv:1804.00209. Cited by: §II-A1, §IV-6.
  • [10] M. Mozaffari, A. Taleb Zadeh Kasgari, W. Saad, M. Bennis, and M. Debbah (2019-01) Beyond 5G with UAVs: Foundations of a 3D wireless cellular network. IEEE Transactions on Wireless Communications 18 (1), pp. 357–372. Cited by: §III-5, §IV-3.
  • [11] J. Park and M. Bennis (2018-Dec.) Propagation measurement system and approach at 140 GHz–moving to 6G and above 100 GHz. In Proc. of the IEEE Global Communications Conference (GLOBECOM), Abu-Dhabi, UAE. Cited by: §II-A1.
  • [12] J. Park, S. Samarakoon, M. Bennis, and M. Debbah (2018-Dec.) Wireless network intelligence at the edge. arXiv preprint arXiv:1812.02858. Cited by: §IV-5.
  • [13] O. Semiari, W. Saad, M. Bennis, and M. Debbah (to appear, 2019) Integrated millimeter wave and Sub-6 GHz wireless networks: A roadmap for joint mobile broadband and ultra-reliable low-latency communications. IEEE Wireless Communications. Cited by: §IV-2.
  • [14] Y. Xing and T. S. Rappaport (2018) Propagation measurement system and approach at 140 GHz-moving to 6G and above 100 GHz. arXiv preprint arXiv:1808.07594. Cited by: §III-1, §IV-2.
  • [15] P. Zioga, F. Pollick, M. Ma, P. Chapman, and K. Stefanov (2018-04) Enheduanna a manifesto of falling live brain computer cinema performance: Performer and audience participation, cognition and emotional engagement using multi brain BCI interaction. Frontiers in neuroscience 12, pp. 191. Cited by: §II-A3.