"6G技术发展及其演变：IEEE经典文章概览"

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"6G技术发展及其演变IEEE经典文章-1；6G技术发展及其演变IEEE经典文章;Received June 23, 2020, accepted July 6, 2020, date of publication July 21, 2020, date of current version July 31, 2020.Digital Object Identifier 10.1109/ACCESS.2020.30108966G and Beyond: The Future of WirelessCommunications SystemsIAN F. AKYILDIZ, (Fellow, IEEE), AHAN KAK, AND SHUAI NIEBroadband Wireless Networking Laboratory, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USACorresponding author: Ahan Kak (ahan@ece.gatech.edu)This work was su;" 6G技术发展及其演变随着4G和5G技术的迅猛发展，人们对未来通信系统的期望和需求越来越高。为了满足未来通信的需求，学术界和产业界一直在探索下一代无线通信技术，即6G技术。本文回顾了6G技术的发展和演变，并展望了未来的无线通信系统。本文的作者来自佐治亚理工学院电气与计算机工程学院的宽带无线网络实验室，包括IAN F. AKYILDIZ（IEEE会士）、AHAN KAK和SHUAI NIE。作者指出，随着人们对更快速、更可靠的通信需求的增加，6G技术将成为未来通信领域的重要研究方向。本文探讨了6G技术的几个关键特点和技术挑战。首先，6G技术将以更高的频率和更大的带宽来提供更高的通信速度和容量。其次，6G技术将引入更多的天线和更复杂的天线设计，以提高信号的覆盖范围和系统的鲁棒性。此外，6G技术还将应用更高级的信号处理技术和智能算法，以提高系统的性能和效率。本文还介绍了6G技术在不同应用领域的潜在应用和挑战。例如，在智能交通领域，6G技术可以实现车辆之间的高速通信和实时感知，从而提高交通效率和安全性。在工业自动化领域，6G技术可以支持大规模机器到机器通信和智能控制，推动工业生产的智能化和自动化。在医疗领域，6G技术可以实现远程医疗和健康监测，提高医疗资源的利用效率和病人的生活质量。然而，6G技术的发展还面临着一些挑战。首先，由于更高频率的使用，6G技术将面临更严峻的信号传输和衰减问题。其次，6G技术需要支持更多的设备和用户，因此需要更高的容量和系统吞吐量。此外，6G技术的实现还需要解决安全和隐私保护等重要问题。为了应对这些挑战，本文提出了一些6G技术发展的方向和建议。首先，需要加强基础理论研究，特别是在高频率传输和天线设计方面。其次，需要提高6G技术的硬件和软件支持能力，以满足更高的容量和系统需求。此外，还需要加强与其他领域的跨学科合作，共同解决6G技术发展中的共性问题。总之，6G技术作为下一代无线通信技术，具有重要的研究意义和广阔的应用前景。本文回顾了6G技术的发展和演变，展望了未来的无线通信系统。随着技术的不断进步和需求的不断增长，相信6G技术将在未来的通信领域发挥重要的作用。

I. F. Akyildiz et al.: 6G and Beyond: The Future of Wireless Communications Systems

Besides these classical approaches for THz band device

development, new materials, including graphene, carbon nan-

otubes, and graphene nanoribbons, are gaining more attention

due to their extremely high electron mobility in the order of

8, 000 − 10, 000 cm

/(V · s) at room temperature, as com-

pared to 1, 400 cm

/(V · s) of silicon, and 8, 500 cm

/(V · s)

of GaAs, which means that the link throughput can be poten-

tially up to ten times higher than is currently achievable

with most semiconductors [28]. The graphene-based devices,

offering outstanding mechanical, electrical, and optical prop-

erties, have been utilized in the development of power detec-

tors at 600 GHz [29] and 200 GHz [30], as well as plasmonic

antenna arrays and transceivers [31], [32]. Graphene-based

devices have the potential to break new ground in reaching

the desired level of performance at much higher frequencies

above 1 THz.

C. PHYSICAL LAYER MODELING AT TH E THz BAND

The realization of wireless communications at THz frequen-

cies requires the development of accurate channel models to

capture the impact of both channel peculiarities including the

high atmospheric attenuation and molecular absorption rates

at various transmission windows, as well as the propagation

effects including reﬂection, scattering, and diffraction, with

respect to different materials. Current research has reported

several efforts to provide fundamental understanding of such

channels. For example, an early work in [33] demonstrates

the remarkable capacity the THz band channel can support

for short transmission distances. The model provides a detail

analysis on the effect of attenuation caused by the molecular

absorption and spreading loss, on which the performance

of channel throughput is heavily dependent. One step fur-

ther, in order to extend the transmission distance at THz

bands, an idea dubbed as the ultra-massive multiple-input

multiple-output (UM MIMO) communications, enabled by

an element array size of 1024 × 1024 with plasmonic nano-

antennas, can drastically boost the signal strength by steering

and focusing the transmitted beams in both space and fre-

quency [34]. Correspondingly, a UM MIMO channel model

has been developed in [35] which takes into account the role

of such arrays.

Additionally, a stochastic channel model for indoor THz

band communications at 300 GHz has been reported in [36]

which characterizes both spatial and temporal domain chan-

nel information. More recently, based on the aforemen-

tioned applicable scenarios in the THz band, a stochastic

channel model for kiosk applications has been reported

in [37] which ranges from 200 − 340 GHz. The main take-

away from current models validated using either mea-

surements or the ray-tracing technique is that the direct

path between the transmitter and the receiver and the

single-bounce reﬂected paths dominate the received power,

while other channel effects, including diffraction and scatter-

ing, attenuate power signiﬁcantly along propagation.

On the basis of the ultra-wideband channel character-

ization, THz band communications faces a critical and

challenging task of synchronization in the receiver design.

Existing pulse-based modulation schemes permit the use

of low-complexity non-coherent analogue detectors, e.g.,

energy detector and auto-correlation receiver, which involve

the multiplication of the received signal with itself, followed

by an integrator. However, a more advanced non-coherent

receiver architecture in [38] based on a continuous time

moving average symbol detection scheme demonstrates bet-

ter performance compared to previous detection schemes

for pulse-based modulations in terms of the symbol error

rate. In addition, robust frequency and timing synchroniza-

tion for multi-carrier communication in the THz band is

desirable to decode multiple incoming signal streams. The

work presented in [39] realizes both a low-rate sampling

scheme for channels with high SNR values and a maximum

likelihood-based algorithm for low SNR channels with sat-

isfying bit-error-rate performance. More recently, a synchro-

nization scheme based on medium access control protocols

is reported in [40], which shows good performance in both a

macro-scale scenario to overcome the distance limitation at

the THz band and a nano-scale scenario for nano-devices for

energy harvesting.

Similarly, given the peculiar ultra-wideband nature and

frequency selectivity of THz band communications, equal-

ization solutions pose another relevant challenge [15], [41].

In [42], three equalization solutions, including the Tomlinson-

Harashima precoding, a waveform with interference manage-

ment for time-reversal systems, and an iterative algorithm

with adaptive soft feedback, are reviewed and compared for

an indoor channel. Results show that the iterative algorithm

with adaptive soft feedback yields the most promising BER

performance [42].

D. MEDIUM ACCESS CONTROL I N THz BAND

COMMUNICATIONS

On top of physical layer channel models, the medium access

control (MAC) schemes in THz band communications should

adopt certain spatial and spectral features in order to pro-

vide solutions in resolving issues such as the deafness prob-

lem and LoS blockage, among others [43], [44]. Different

from commonly used MAC solutions in RF systems that

utilize omnidirectional antennas, such as carrier sense mul-

tiple access with collision avoidance (CSMA/CA), the MAC

protocols designed for THz band rely on handshakes between

transceivers with highly directional beams. These razor-sharp

beams can provide higher power radiation gain and prolong

the transmission distance, but when misalignment happens,

the deafness problem arises. As such, the deafness avoidance

approach is required in MAC scheme design. Existing solu-

tions utilized in IEEE 802.15.3c [45] and others employ a

beam-training phase to estimate and steer beams towards des-

tined devices. Recent works also propose methods based on

angular division multiplexing [46] and a priori aided channel

tracking schemes [47]. The results in such proposed solutions

suggest that with good beam alignment strategies the channel

throughput can be improved signiﬁcantly.

VOLUME 8, 2020 134001

I. F. Akyildiz et al.: 6G and Beyond: The Future of Wireless Communications Systems

Moreover, the MAC protocols can also resolve the issue

of LoS blockage where the received power of a user device

may undergo deep fading due to the device being held in

a manner that blocks the LoS path. Studies have shown

that such attenuation by the human body can be as high as

20 dB at 60 GHz and up [49], [50]. To mitigate the blockage

problem, researchers have proposed a multi-hop scheme at

the mmWave and THz bands to form alternative routes [51],

[52]. A careful link-level scheduling and neighbor discovery

process is necessary to achieve high throughput while main-

taining low interference.

E. OPEN PROBLEMS IN THz BAND COMMUNICATIONS

Currently, the fabrication and testing of THz band antenna

arrays remains a relevant challenge. Some techniques based

on photolithography, electro-beam lithography, among oth-

ers, are able to produce the front-end with hundreds of plas-

monic antenna elements. The utilization of large antenna

arrays can extend the signal coverage by forming array radi-

ation patterns with main lobes of high directivity, thus focus-

ing energy towards desired directions. However, such highly

directional beams limit coverage in the angular domain, caus-

ing low energy efﬁciency at the transmitter to serve each user.

A recent solution named ‘‘THzPrism’’ has been proposed

to form multiple beams with slight frequency shifts towards

different directions while maintaining good distance cover-

age [53] in addition to other proposed solutions discussed

in Section III-C to solve the transmission distance problem.

This design employs true time delays for RF chains before

phase-shifters to obtain a prism-like effect, which spreads the

original beam into several beams, each with a slight frequency

shift with respect to the center frequency.

In parallel to the quest for more novel solutions in antenna

design, other remaining challenges reside in the control

and signal processing schemes associated with transceiver

designs in the THz band. On the one hand, real-time con-

trol algorithms are needed. On the other hand, communi-

cation protocols for coordination between the transmitter,

receiver, and reﬂectarrays are needed. Among others, in [54],

researchers reported a smart reﬂectarray-assisted mmWave

system compatible with IEEE 802.11ad. Besides the design

of the reﬂectarray and a study on deployment strategies,

a three-way beam-searching protocol is developed, in which

the reﬂectarray coordinates with the transmitter through a

2.4 GHz control channel in order to discover the best joint

transmit and reﬂect sectors for which the signal at the receiver

is maximized. However, this work does not capture the

extended functionalities of plasmonic reﬂectarrays. Further-

more, when highly directional beams are utilized at mobile

transceivers, a relevant challenge arises from the limited

ﬁeld-of-view of antenna arrays for each transceiver to locate

the next hop to forward its data; thus, new routing solutions

are necessary for THz band communications to efﬁciently

discover and establish links. A study in [55] reports a solution

in link discovery at THz band using a leaky-wave antenna to

sense the angular information of a user.

IV. INTELLIGENT COMMUNICATION ENVIRONMENTS

Along with the rapid growth in the number of wireless

devices, services, and applications, a corresponding demand

for higher speed wireless communications has burgeoned in

recent years. Nevertheless, the major challenge at mmWave

and THz-band frequencies is the limited communication dis-

tance because of the remarkably high path loss inherent to

small wavelengths and the limited transmission power of

mmWave and THz-band transceivers [56]. Current solutions

primarily focus on the advancement of wireless transceiver

hardware and software, as well as network optimization

strategies. However, the wireless propagation medium has

been largely neglected. The wireless communication environ-

ments, for both indoor and outdoor scenarios, can be actively

utilized in order to become controllable for signal propaga-

tion. To control signal propagation in environments is essen-

tially to control how electromagnetic waves interact with

scatterers, which include indoor furniture and outdoor build-

ings as well as other infrastructure. Typically, the control-

lable behaviors of electromagnetic waves include controlled

reﬂection, absorption, wave collimation, signal waveguiding,

and polarization tuning, as illustrated in Figure 4. The notion

of ‘‘Intelligent Communication Environments’’ resides in the

control algorithms where deep learning and reinforcement

learning are to be exploited to dynamically conﬁgure the

environments. In the following subsections, we elaborate on

these controllable wave behaviors, current research efforts,

as well as corresponding open issues.

A. BASICS OF INTELLIGENT COM MUNICATION

ENVIRONMENTS

The intelligent environments can be seen as a three-

dimensional structure with several layers, each with differ-

ent functionalities. Recent research under the EU Research

Project ‘‘VisorSurf’’ has demonstrated a structure with ﬁve

main layers, which are (from top to bottom) the EM behavior

layer, the actuation and sensing layer, the shielding layer,

the computing layer, and the communication layer, respec-

tively [57]. Speciﬁcally, the EM behavior layer is composed

of metasurfaces, a two-dimensional representation of meta-

materials, and has a tunable impedance to control direc-

tions of reﬂection of the EM waves. Some other works use

reﬂectarray antennas as the top surface [58], [59]. The actu-

ation and sensing layer consists of circuits for phase shift-

ing and sensors for impinging signal sensing. Some options

for actuation include PIN diodes with controllable biasing

voltage as switches in reﬂectarray antennas, and complemen-

tary metal-oxide semiconductors (CMOS) transistors as well

as micro-electro-mechanical (MEMS) switches for metasur-

faces. The shielding layer isolates the upper and lower parts of

the layered structure so as to minimize the possible interfer-

ence. The computing layer serves to control the phase shifts

and process sensed impinging waves. To this end, another

reported solution makes use of ﬁeld-programmable gated

arrays (FPGAs) to fulﬁll such functions on metasurfaces [60].

Finally, the communication layer connects all upper layers

134002 VOLUME 8, 2020

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