Page 148 - ITU Journal, Future and evolving technologies - Volume 1 (2020), Issue 1, Inaugural issue

ITU Journal on Future and Evolving Technologies, Volume 1 (2020), Issue 1

INTEGRATED SENSING AND
COMMUNICATIONS

Drone
cameras ULTRA-FLEXIBLE Camera
HETEROGENOUS NETWORKS systems

Space Aerial
networks
networks
Radar ULTRA-FLEXIBLE (zeppelins)
sensing PHY & MAC
Smart
Flexible
Eavesdropper wearables
waveforms
Aerial
networks MIMO and
(balloons) PHY Aerial
security Beam-space networks
Vehicle (UAVs)
sensors
Body
sensors
Aerial
CoMP
networks systems Terrestrial
(drones) Intelligent networks
surfaces
Automated
vehicles Undersea Sensors
networks
Fig. 5 – The integration of many different sensor hardware with the heterogeneous communications networks under 6G systems.

Sensing and Communications (ISAC) has been studied granular REM information.
in different domains in the past. Cognitive Radio (CR)
applications triggered the ISAC research on the last two The complete information and awareness of the environ-
decades. Spectrum sensing and awareness is one of ment comes at the cost of a high volume of data, variety
the irst application areas in the ISAC research [115]. of sources and signi icant processing [80,82]. This neces-
Location awareness is exploited to improve the wire- sitates the use of big-data processing techniques [122]. A
less communications system design in [116]. Satellite signi icant challenge, however, in this regard is the over-
and drone images can be used to predict channel pa- head of data exchange between the sensing and process-
rameters [117]. Context-awareness is used to optimize ing nodes. A centralized solution might not be suitable
network architectures in wireless communications [118]. in such scenarios, rendering the use of edge-computing
ISAC systems are studied for radar sensing [91, 119] and imperative, particularly for low-latency use cases. More-
Wi-Fi network coexistence [120] in the literature. How- over, the usage of Arti icial Intelligence (AI) solutions can
ever, the complete list of sensing information that can be be helpful while processing big-data at the edge nodes.
useful for the next generation cellular communications
systems from the ISAC perspective has not yet been 3.5 Intelligent Communications
comprehensively studied [114].
The usage of AI in the communications society has
A Radio Environment Map (REM) is a realization of increased in recent years. Several survey and tutorial
the ISAC concept [121]. It is mainly used to obtain papers are published on the usage of Machine Learning
environmental information in the literature, however, (ML) for wireless communications [34, 123–129]. AI-
for the next generation systems the REM concept will be aided design and optimization has even been leveraged
generalized from environmental-awareness to complete- for the lexible implementation options provided in
awareness. REM may include all sensing information in 5G [25]. In many of the studies, AI is put at the cen-
a multi-dimensional manner for wireless communica- ter of 6G visions [6, 8, 24, 28, 32, 44, 67, 75, 76, 83] to
tions networks. To exemplify, REM can be a specialized complement the classical methods. Indeed, the use of
database for the ISAC. Therefore, the lexibility level of AI is inevitable to incorporate intelligence in the future
the ISAC systems can be determined by the dimensions in networks [130–132]. AI-aided methods can propose fast
REMs. Each dimension in a REM increase the awareness, and ef icient solutions in case enough data is available.
allowing better resource utilization. Moreover, control
of the con igurable options and parameters in different AI and ML also ind a range of applications in ISAC and
communications layers of 6G can be enhanced by more REM paradigms to extract information regarding the en-

128 © International Telecommunication Union, 2020