Instrumentation & Measurement Magazine 23-9 - 58

IEEE 802.15.22.3 Spectrum
Characterization and Occupancy
Sensing Application Testbed
Gianni Cerro, Gianfranco Miele, Roger Hislop, Oliver Holland, and Apurva Mody

D

ynamic Spectrum Access (DSA) is becoming a key
enabler for wireless communication technologies.
Many DSA concepts-such as the Citizens Broadband Radio Service and TV White Space-rely on spectrum
databases to identify available radio channels. However,
propagation models and other assumptions used by these
databases are usually poor for the given scenario, typically
leading to over-conservative calculations in terms of permitted secondary spectrum access, geographical bounds or
transmit powers in order to mitigate perceived interference
risk. Spectrum sensing allows better understanding of the
actual propagation and actual channel impulse response, allowing spectrum databases to tune their propagation models
to increase the availability of spectrum for secondary access
as assessed by such spectrum databases, or to increase the
availability of local access licenses as assessed by the telecommunications regulator. A critical limitation on the uptake of
ubiquitous sensing is that measurement systems are either
proprietary or do not have commercial use-cases; hence little
economy of scale exists to drive deployment. For this reason,
the IEEE 802.15.22.3 Task Group was formed to standardize a
Spectrum Characterization and Occupancy Sensing (SCOS)
system capable of addressing a wide range of sensing tasks
and be easily and flexibly deployed across a variety of hardware options. This paper provides a high-level description of
this system and a first testbed implementing the standard in a
laboratory-controlled environment. Preliminary performance
assessments are also reported, where it is shown that the system is able to detect users with a power level down to -80 dBm
with a probability of detection equal to 1 and controlled false
alarm rates.

Optimizing Spectrum Usage
The scientific community has been working on the development of new spectrum management techniques to address
the accelerating demand for more bandwidth by wireless telecommunication operators against the backdrop of spectrum
scarcity [1]-[3]. These include TV White Space and Citizens
Band Radio Service in the 700 MHz band and 3.5 GHz band,
58	

respectively, and a range of other spectrum sharing mechanisms are coming to the forefront, such as shared spectrum
licenses and local licenses to optimize spectrum utilization.
As one example of this, one of the key enablers of 5G communication systems is the vast bandwidths opened at higher
frequencies, particularly mm-wave. Such frequencies propagate extremely poorly, however, meaning that these systems
will most likely only be deployed in dense urban areas-leaving these bands under-utilized in peri-urban and rural areas.
To enable wider access to 5G technologies that can use the
kinds of bandwidths closer to those provided at mm-wave,
much of the lower-frequency spectrum with desirable propagation characteristics as possible must be unlocked. To meet
the need for access to more of this lower-frequency spectrum,
underlying mechanisms that would underpin implementation of a Dynamic Spectrum Access (DSA) policy have been
widely investigated.
Several radio frequency measurement and characterization
methods have been proposed, as well as a new architecture for
wireless transmitters and receivers [4], [5] to distribute this
data for the greatest benefit. One of the most important requirements to enable Dynamic Spectrum Sharing techniques,
such as Opportunistic Spectrum Access (OSA), is to ensure
that the Opportunistic Users (or Secondary Users) of spectrum
cause no interference to the incumbents or the Primary Users
(typically a licence holder for those bands). To that end, it is of
paramount importance that by using some improved mechanism one can optimize the Exclusion Zones and the Protection
Zones to increase utilization efficiency. To do this, a passive
spectrum database (a list of known transmitters feeding into
a propagation model) alone may not be enough. One needs to
adopt other new, active techniques to derive more information
about the global and local spectrum usage. These include Spectrum Sensing and Beaconing.
Recently, the IEEE 802.22 Working Group completed a
standard for Cognitive Radio Wireless Regional Area Networks (WRANs) which specifies the Medium Access Control
(MAC), Physical Layer (PHY), and policies and procedures
for operation in the bands that allow spectrum sharing [6]. A

IEEE Instrumentation & Measurement Magazine	
1094-6969/20/$25.00©2020IEEE

December 2020



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