Subject: [NEXTEL-1] Adaptive Spectrum Access: Using the Full Spectrum Space

From: Marcelrf <[email-masked]>
Date: Mon, 01 Mar 2004 23:42:03 -0500

Adaptive Spectrum Access: Using the Full Spectrum Space
William D. Horne*
The MITRE Corporation

McLean, VA
703-883-6198; [email-masked]
Abstract

Trends in technology are enhancing the future capability of devices to
access the electromagnetic
spectrum using the full range of dimensions associated with the
spectrum. This increased capability to
access the full spectrum “hyperspace” not only improves the ability of
systems to use the spectrum but
can also reduce interference and the adverse impact to system
performance. This paper presents technical
research into advanced adaptive techniques and identifies those
parameters or characteristics where
regulation and policy need to be reviewed. Fundamental to these new
adaptive techniques is a behaviorbased
approach to design and, possibly, policy. Consequently, this paper also
presents a technical case study of one behavior-based approach, Dynamic
Frequency Selection, that provides insight into the benefits and
possible limitations of such approaches to cognitive radio design and
policy.

1. Introduction

The Federal Communications Commission’s (FCC) Spectrum Policy Task Force
(SPTF) report [1]
defined three regulatory mechanisms, exclusive use, commons, and
command-and-control, for assigning
spectrum usage rights; however, each model depends upon recent
technological advances to promote
access and efficiency, common goals for any spectrum access model. For
example, the commons model,
even in its most basic form of existing unlicensed bands, essentially
requires use of techniques that sense
and adapt to the radio environment. In addition, these same adaptive
techniques are necessary for the
exclusive use model to improve spectrum access through the use of
methods such as secondary markets.
Consequently, regardless of regulatory model, if flexibility and
efficiency are to be promoted, regulation must enhance or at least allow
the use of adaptive techniques.

Many organizations, such as the MITRE Corporation [2-3], are researching
and developing the techniques
and technology necessary to enable devices with adaptive spectrum access
capability, including the use of
software defined radios (SDRs) [4-5]. This research focuses not only
traditional methods to enhance
access, such as frequency division multiplexing, but is also exploring
ways to adaptively access all
dimensions associated with the electromagnetic spectrum. This spectrum
“hyperspace” includes not only
the fundamental parameter, frequency, but also others as well including
time, space (both location and
signal directionality), and signal space, which involves power,
polarization, coding, and other signal
features. Although it is difficult to define the dimensions of the
spectrum space [6], the flexibility to
access spectrum across many of these dimensions provides systems an
ability to react and adapt to its
environment either in an exploitive, non-cooperative mode or through a
coordinated, central control
method associated with a networked system. Adaptation is one of the, if
not the, fundamental attribute for
intelligent wireless systems, that is, systems demonstrating an
awareness of its environment and an ability
to automatically react. Recently, such systems are referred to as
“cognitive radios” [7-8].
* The views and opinions of the author expressed herein do not
necessarily state or reflect those of The MITRE
Corporation or its clients and sponsors.

This paper presents research into advances in adaptive spectrum access
technology and identifies those
parameters or characteristics requiring regulation or policy
consideration. The paper first discusses the various dimensions of
spectrum, including the difficulty in actually defining such a spectrum
space.
Next, the paper reviews the concept and general definition of adaptive
spectrum radio along with
advances in technologies enabling this adaptive concept. In addition,
demonstrations of technologies and
systems, the subject of the next section of the paper, are important not
only for showing the feasibility of
adaptive systems but also for identifying policy considerations.
Fundamental to adaptive techniques is a
notion of behavior—how does a system react given the conditions of its
environment. Consequently, the
paper presents a technical case study of one behavior-based approach,
Dynamic Frequency Selection
(DFS), to provide insight into the benefits and possible limitations of
such approaches to cognitive radio
design and policy. Finally, drawing from these reviews and case study,
the paper concludes with a review
of policy topics requiring consideration from regulators and other
interested parties.

2. The Spectrum Space

When considering adaptive techniques for accessing the spectrum, system
designers and policy makers
need to define the parameters over which a system can alter its
transmissions. However, identifying the
dimensions of spectrum is not clear whether for design purposes or for
regulation as one does not want to
over-constrain the situation by limiting adaptation to too few
parameters while at the same time not excessively increasing the
complexity by defining too many parameters.

One of the concepts discussed in the FCC SPTF Report was expanding
regulation beyond the traditional
realm of frequency and location (space), as epitomized by the
International Telecommunication Union (ITU) and US Table of Frequency
Allocations that define permitted services according to blocks of
frequencies. This limited view of spectrum, as noted by the SPTF Report,
prevents the full use of the spectrum and, in many cases, limits the
possibilities of technology to improve access to the spectrum.

The SPTF Report states:

“The Task Force also analyzed the benefits of parceling out spectrum
using variations in frequency, space, power, and time to maximize the
use of spectrum. In the past, the Commission has recognized and licensed
spectrum primarily by defining spectrum rights in terms of the first
three dimensions. The Task Force found that new technological
developments are changing the way in which each of these spectrum
dimensions is used. In addition, new technology now permit the
Commission to increasingly consider the use of time, in combination with
frequency, power, and space, as an added dimension that could permit
more dynamic allocation and assignment of spectrum usage rights.”

Such definition of the spectrum space is important as it guides the
development of regulation but also,
more fundamentally, the rights and responsibilities for accessing
spectrum, regardless of the allocation
model (exclusive use, commons, or command-and-control). While many
economists, notably Ronald
Coase [9], have noted the importance of defining a bundle of rights,
they have not explicitly offered a
definition of rights based on the dimensions of the spectrum space. This
definition is important for
regulators whether licensing primary users or enabling secondary markets
and “underlays” (e.g., lowpower
operations on non-interference basis). Such a definition remains
elusive.  Underlying this difficulty in defining economic or regulatory
dimensions is the difficulty in actually defining the spectrum space.
Several researchers [6] have proposed definitions of the spectrum space.

Typically, when defining an n-space, the dimensions are orthogonal, that
is, the values uniquely define a
point in the space. However, several of the possible parameters (e.g.,
coding/modulation), do not
necessarily define an orthogonal parameter but they can still be used to
distinguish signals, albeit with a
statistical likelihood.

Without stating the definitive dimensions of the spectrum space, Table 1
lists the dimensions proposed by
researchers. It should be noted that this set, in its entirety, is not
necessarily orthogonal. However, it does
provide an organized set of parameters from which to draw a bundle of
rights or to define regulatory parameters. The current international and
national system do, in fact, draw from these parameters.  The purpose
here is not to definitively define the complete set of dimensions of the
spectrum space; rather, the intent is to indicated that regardless what
the minimum set is required for defining rights or regulation, emerging
adaptive spectrum systems can adjust its own interaction with the
spectrum space using all of these parameters. Advances in technology
from digital signal processing to antennas are enabling systems to adapt
its access across the entire spectrum space.

3. Adaptive Spectrum Radio: A Notional Definition

Forms of adaptive spectrum access have been implemented in a number of
systems in the past including
current and next generation mobile phone standards, but the key
difference in the emerging adaptive
spectrum radios is the increased flexibility, both in speed and variety
of parameters, to alter transmissions
and reception. This section provides a notional definition for adaptive
behavior based on two conditions:
(1) an opportunistic, non-cooperative situation and (2) a situation in
which information is shared in a cooperative fashion. This notional
definition may also serve to define, in part, the meaning of cognitive
radios.
The key benefits for adaptive spectrum access, regardless of the
situation, include:
??Improved spectrum access and utilization;

??Maintenance of quality of service in a changing environment; and,
??Capability to adjust emissions to reduce or maintain levels of
interference to other systems.

Table 1: Possible Dimensions of the Spectrum Space
General Class Parameter Units Notes
Power
Power (or field
strength)
W (or V/m)
Often viewed as the
independent variable of the
spectrum space
Frequency Frequency Hz
Time Time sec
Location latitude, longitude, elevation
3 dimensions (can be
generalized to other
reference systems besides
geocentric)
Space
Signal direction
(transmission
direction, angle of
arrival)
azimuth, elevation
2 dimensions (note:
perspective is important
whether from transmitter or
receiver)
Polarization
vertical/horizontal
(clockwise/counter-clockwise)

Signal Coding/modulation (variable) not necessarily orthogonal
Rudimentary forms of adaptive spectrum access have been implemented for
years in systems operating in
unlicensed bands (e.g., cordless phones operating around 45 MHz must use
an automatic channel selection mechanism that prevents establishment of
a link in an occupied channel). More advanced implementations of
adaptability include the various methods for changing data rate, code
rate, and modulation order implemented by second (2G) and third
generation (3G) mobile standards [6-7]. For example, Enhanced Data Rates
for GSM Evolution (EDGE) adapts the transmission parameters modulation
(GMSK or 8-PSK) and coding rate. This type of adaptability is well
suited for packet data and in situations with slow variations in fading
and distance loss over the cell coverage area.

Recent advances in technology, specifically sensing and networking,
enable two forms of adaptive
spectrum access. The first form, often referred to as opportunistic,
responds to a changing radiofrequency
environment by automatically adapting its transmissions to zones where
no other systems are operating.
As shown in Figure 1, the basic approach first senses the spectrum to
determine where other systems are
operating and where idle spectrum (“white space”) exists and then
synthesizes a waveform to exploit the
“white space.” Thus, an adaptive system enables operation with other
radio systems in non-cooperative
fashion and potentially increases the utilization of the spectrum. Such
a system can also share knowledge
of the spectrum environment with other similar devices to ensure other
users are not affected by the adaptive system. Besides the
inter-operation with other systems in underutilized spectrum, adaptive
spectrum systems may also increase spectrum utilization since they do
not rely upon static frequency assignments which, if not required, would
remain fallow.
Underlying this form of opportunistic adaptive access is the assumption
that spectrum is not always used
across the dimensions of the spectrum space, especially frequency and
time. Depending upon the frequencies that the adaptive system can
access, the amount of available spectrum may vary. Several efforts
underway [10] indicate that the spectrum is not fully used across all
its dimensions. One key program, discussed later in this paper, is
DARPA’s next Generation (XG) program that is explicitly exploiting this
known “white space” in an opportunistic approach.  Another form of
adaptive spectrum access exploits shared information or operations to
cooperatively determine access to the spectrum. Such an operation is
inherent, albeit in a limited manner, in existing systems like trunked
radio systems that share channels between users and cellular systems
that assign channels to users (either time slots or CDMA codes). In a
more expansive fashion, emerging mesh networking systems exhibit
adaptive and dynamic behavior. Unlike opportunistic approaches, sharing
information can greatly improve spectrum access utilization by
coordinating access across the various spectrum dimensions. Several
methods may be employed to distribute the spectrum knowledge and control
whether through beacons or control channels or by sharing databases of
existing users.

Future systems may employ either or both forms of adaptive spectrum
access, so they should not be
viewed as mutually exclusive. In addition, other taxonomies for adaptive
systems are possible including
centralized versus distributed control of adaptation. The key
characteristics or behaviors of adaptive
spectrum systems are their ability to exploit knowledge of the
electromagnetic environment to adapt its
operations and access to the spectrum. The knowledge may be gained
through measuring or sensing the
spectrum or through sharing information between systems. Key challenges
remain for technology developers including the need to demonstrate the
feasibility of adaptive techniques across the various dimensions of
spectrum. This will require working with the policy and regulatory
community to develop appropriate policies and procedures.

Figure 1: Adaptive Spectrum Access (Opportunistic)

4. Technology Advances and Demonstration Projects Enabling Adaptability
Enabling this automated, cognitive behavior is a wide-range of advances
in technology along with a
variety of targeted government and industrial research and development
projects. Digital signal
processing-based radios, typically referred to as Software Defined
Radios (SDR), provide the platform for
these dynamic radio systems. However, a variety of technologies
contribute to the increasing capability
to access the spectrum across all of its dimensions. In addition to a
variety of activities advancing SDRs
and underlying technologies, several targeted projects are investigating
adaptive techniques for spectrum
access.

Technology Advances

While there are different ways to categorize technology, Table 2
provides a general overview of
technologies fundamental to adaptive access of the spectrum. The intent
of Table 2 is only to highlight
underlying technology advances and not meant as an exhaustive review.
For those desiring additional
details, technical publications of the Institute of Electronic and
Electrical Engineers (IEEE) provide
detailed overviews of various technologies while academic papers, such
as [11], provide good generalaudience
overviews of the technologies and policies.

Create waveform(s) to use
idle spectrum
Determine which channels
are busy
Repeat steps 1 & 2 to monitor spectrum
and adapt when environment changes
Radio Frequency (MHz)
Radio Frequency (MHz)
Waveform adaptable to
variable, non-contiguous
spectrum
Time (sec)
Time (sec)
Step 1
Step 2
Step 3
Occupancy information
may be shared with
other radio node

Table 2: Technology Developments Enabling Adaptability
Technology
Categories
Elements Trends Limitations
Analog-to-Digital and Digitalto-
Analog Converters
Increasing sampling rate
and resolution
Advances not
commensurate to
advances in processing
elements
Application-Specific
Integrated Circuit (ASIC)
Lower power, greater
processing
Non-programmability
Field Programmable Gate
Array (FPGA)
Processing speed not as
great as ASICs
Digital Signal Processor
(DSP)
Processing speed not as
great as ASICs/FPGAs
Digital Signal
Processing
Micro-processors
Lower power, greater
processing with
programmability
Power consumption
higher than other
processing devices
Antennas
Adaptive techniques
using arrays of elements
provide
- Dynamic beam steering
- Interference cancellation
- Multiple antenna/
channel techniques
Power Amplifiers, Low Noise
Amplifiers
Increasing bandwidth but
limited advances
Radiofrequency
Devices
Filters, etc. Increasing bandwidth but
limited advances
Performance bandwidth
limits broadband
capabilities
Data representation
(Extensible Markup
Language (XML), Resource
Description Framework
(RDF), etc.)
Standardization enabling
greater sharing of data
Data/Knowledge
Tools
Knowledge (semantic tools,
Web Ontology Language,
etc.)
Standardization and
object-oriented
approaches allowing
“knowledge-based”
operations
Early stages of
standardization and
limited experience in
radiocommunication
systems

The general categories denoted in Table 2 should not be viewed as
stand-alone technologies in isolation
of the others. The convergence and simultaneous development in several
areas can combine to create
powerful new applications or techniques. For example, the increased
signal processing capabilities of
integrated circuits in conjunction with developments in antenna design
combine to form powerful
applications like adaptive arrays that can dynamically steer the antenna
beam or cancel unwanted signals.
In addition, this conjunction also enables new techniques like
multiple-input multiple-output (MIMO) systems that exploit multiple
signal paths to increase the capacity that a channel can carry.

The principal area enabling adaptability is advances in digital signal
processing. These advances include
increased capabilities of microprocessors and other programmable,
processing components as listed Table
2. System architectures (i.e., SDRs) using these programmable devices
need to consider the trade-off
between flexibility and performance. Flexible signal processing,
favoring an architecture centered on
programmable devices (DSP, FPGA), enables a system to evolve and be
changed even after deployment.
Alternatively, the need for processing wideband signals generally
requires application specific solutions.

As an example SDR architecture, Figure 2 depicts an architecture that
blends the speed of ASICs with the flexibility of DSPs. The benefits of
SDRs using these processing elements include increased flexibility
(upgradeability, customization, faster-time-to-market, and adaptability)
and lower costs (economies of scale and increased modularity).
The next major category includes a variety of elements including
antennas, amplifiers, filters, and other
related electronic components. The key advances and limitations for
these elements are primarily
associated with the bandwidth over which the elements perform. For
example, the performance of
antennas is typically limited to a defined frequency band with
significant decreasing performance as
bandwidth increases. These limitations inhibit adaptive systems to
adjust its transmission across the
fundamental dimension of frequency. In addition, as noted previously,
advances in processing along with
new antenna concepts like adaptive arrays are enabling greater
capability to adapt.

A new emerging area of technology enabling adaptability includes data
and knowledge tools that provide
for standardized approaches to defining, sharing, and interpreting data.
By standardizing data, adaptive
systems can readily define operations based on shared information. For
example, significant programs
developing SDR-based systems, such as the Joint Tactical Radio System
(JTRS), have specified
Extensible Markup Language (XML) for use in defining shared data. XML
and related standards such as
Resource Description Framework (RDF), are cross-platform, software and
hardware independent tools for
structuring, storing, and transmitting data. Future advances will not
only define data but also allow
inferences and operations to be extracted using automated tools. Such
emerging “knowledge” tools (e.g.,
the World Wide Web Consortium’s Web Ontology Language (OWL)) will
exploit defined relationships between objects, sometimes referred to as
“ontologies,” in a manner that allows a machine to make inferences and
determine actions.
Research & Development Projects

In addition to developing the underlying technologies, system research
and development projects are
required to demonstrate the technical principles for dynamic spectrum
access. Recent recommendations
for testbeds for wireless system development [12] further promote the
need for technology developers to
demonstrate capabilities and limitations in order to assist both
end-users and the policy community to gain confidence in new adaptive
wireless approaches and applications.
r(t) s(t)
FPGAs
DSPs
FPGAs
ASICs
ASICs

Balancing Performance versus Flexibility
- Highest Performance
- Lowest Flexibility
- Lowest Performance
- Highest Flexibility

A/D
DAC
Figure 2: Example Software Defined Radio Architecture

Principal objectives for demonstrations include:
??Feasibility;
??Identification of system operations concepts;
??Definition of architectural approaches; and,
??Exploration of policy considerations.

Demonstrations are not intended as final indicators of future
applications or design, but they do provide a
means to explore operations concepts and policy options. Two example
research projects provide illustrations of adaptive spectrum access
systems.

The MITRE Corporation has developed a testbed, referred to as the
Adaptive Spectrum Radio (ASR), to
demonstrate feasibility of the adaptive spectrum radio concept with the
intention of providing four basic
capabilities: (1) periodic estimation of a channel’s occupancy state;
(2) periodic adaptation of a timelimited
waveform in response to occupancy state estimates; (3) periodic "joint
occupancy vector” negotiation (see Figure 3) with subsequent burst data
transfer; and (4) measurement of impairments to primary users. The
testbed uses Commercial-Off-The-Shelf (COTS) products with a processing
architecture similar to that shown in Figure 2 and a functional
architecture as shown in Figure 4. The testbed consists of two chassis
that operate as two independent radios along with signal generators for
simulating the radiofrequency environment. To date, the MITRE testbed
has been used to demonstrate the essential feasibility of adaptive
spectrum access and to identify design and policy considerations.  The
most significant project exploring adaptive spectrum access is DARPA’s
next Generation (XG)

project that is developing a prototype adaptive spectrum system and is
defining a set of abstract behaviors
and associated protocols to guide the operations according to spectrum
management policy [13]. This ambitious project plans to demonstrate both
the feasibility and operations in realistic radiofrequency environments.
Most notably, the XG project is defining a set of behaviors and
protocols that will translate spectrum management policy into clearly
defined operations of the radio. These concepts and other associated
approaches are discussed in Section 6.

Spectrum @ Ts
Frequency
ASR 1
Spectrum @ Ts
ASR 2
Frequency
Negotiate Common Passband
Negotiate Common Passband
Frequency
Disjoint Passband
Adaptive Waveform @Ts
Figure 3: MITRE Testbed Frequency Occupancy Negotiation

Figure 4: MITRE Testbed Functional Architecture

Other projects exploring adaptive spectrum access techniques include a
variety of projects developing ad
hoc and mesh networking systems. These projects include both government,
primarily DoD projects like
the JTRS Wideband Networking Waveform, and industry projects, such as
IEEE 802 standards work exploring possible ad hoc networking
enhancements to the baseline wireless networking standards.  Although
the primary work in these projects focuses on cooperative networking
approaches, extensions may be developed that allow additional adaptive
techniques for opportunistic operations as well.

5. Case Study: 5 GHz Sharing and Dynamic Frequency Selection (DFS)
While the previous sections have defined the spectrum space and the
increasing capability to dynamically
access the spectrum across this multi-dimensional space, the actual
benefits and implementations of
“cognitive” behavior needs to be understood both for future development
of systems and the need for
policy to define appropriate boundaries. One way to attempt an
understanding is through the case study
of an emerging technology that is being implemented in future radio
local area networks (RLAN).
Background

During the late 1990s, wireless local area networks , notably the IEEE
802.11 family of standards, known
as WiFi, and the European HIPERLAN system, became popular as broadband
wireless systems enabling
Internet connections in office, commercial, and home situations. Based
on projected needs for additional
spectrum beyond the previously defined bands in the 2.4 GHz band and
several bands near 5 GHz (see
Table 3), proponents requested additional spectrum in the 5 GHz region.
However, opening this spectrum
to RLANs would require sharing with other systems, notably government
radar systems.
Spectrum
Analyzer
Test Signal
Source
Optional
Single Freq
Tx
Spectrum
Estimator
Adaptive
System
Controller
Transmitter /
Modulator
Receive
Subsystem
Tx/Rx Chassis
Assy
Combined Rx
spectrum
environment
Control
software
& Policy
agent

Table 3: 5 GHz ITU Allocations & Selected Country Allocations
Allocation to services
(specific allocations in selected regions/countries)
Frequency (MHz)
Region 1
(Europe/Africa) Region 2 (Americas) Region 3 (Asia)
MOBILE** except aeronautical mobile (selected footnotes: 5.BD02)
5150-5250* Licensed Exempt
(Europe) (HIPERLAN)
(200 mW e.i.r.p. limit)
U-NII*** (United States)
(50 mW tx power. limit)
Hi-speed wireless access (Japan)
RADIOLOCATION****
MOBILE** except aeronautical mobile (selected footnotes: 5.BD02 5.BD04)
5250-5350*

Licensed Exempt
(Europe) (HIPERLAN)
(200 mW e.i.r.p. limit)
U-NII*** (United States)
(250 mW tx power limit)
5350-5470 No mobile (e.g., WiFi, HIPERLAN) systems RADIOLOCATION****
MOBILE** except aeronautical mobile (selected footnotes: 5.BD02 5.BD07)
5470-5725*

Licensed Exempt
(Europe) (HIPERLAN)
(200 mW e.i.r.p. limit)
Proposed U-NII*** (United
States)
(1 W tx power limit)
RADIOLOCATION
5725-5825* U-NII*** (United States)
(1 W tx power limit)
ITU Footnotes
5.BD02 The use of the bands 5150-5350 MHz and 5470-5725 MHz by the
stations in the mobile service shall be in
accordance with Resolution [COM5/16] (WRC-03). (WRC-03)

5.BD04 In the band 5250-5350 MHz, stations in the mobile service shall
not claim protection from the radiolocation
service, the Earth exploration-satellite service (active) and the space
research service (active). These services shall not impose
on the mobile service more stringent protection criteria, based on
system characteristics and interference criteria, than those stated in
Recommendations ITU-R M.1638 and ITU-R SA.1632. (WRC-03)

5.BD07In the band 5470-5725 MHz, stations in the mobile service shall
not claim protection from radiodetermination services.
Radiodetermination services shall not impose on the mobile service more
stringent protection criteria, based on system characteristics and
interference criteria, than those stated in Recommendation ITU-R M.1638.
(WRC-03)
Resolution [COM5/16] (WRC-03)
Resolution requires, inter alia, the following:
- Dynamic Frequency Selection (DFS) required for 5250-5 350 MHz and
5470-5725 MHz bands
- Indoor use only with maximum 200 mW e.i.r.p. in 5150-5250 MHz band
- In 5250-5350 MHz, limited e.i.r.p. (250 mW/1 W with other constraints)
and indoor use should be promoted

Footnotes

* Other services allocated in several sub-bands including EARTH
EXPLORATION-SATELLITE
** Mobile service includes WiFi, HIPERLAN, and other similar Radio Local
Area Networks (RLANs)
*** Unlicensed National Information Infrastructure (U-NII)
**** Radiolocation service includes radar systems

Consequently, the ITU initiated a series of studies to explore the
possibility for sharing and to define, if
possible, technical restrictions necessary to allow sharing. During the
resulting studies in the ITU
Radiocommunication Sector (ITU-R) study groups, several recommendations
were prepared that define
the operations of RLANs and the general characteristic of radar systems.
In addition, based on extensive
simulations of projected deployments of RLANs and radar system
operations, the ITU-R prepared a
recommendation [14] that defines the necessary conditions for RLANs to
share with radar systems. This
recommendation was spurred by a US Government and industry agreement
that formally defined several
key parameters. At the 2003 ITU World Radiocommunication Conference in
Geneva, the member administrations of the ITU agreed to allow the
sharing of the 5 GHz bands as it provided a primary allocation to both
the radiolocation (e.g., radar systems) and the mobile services (e.g.,
WiFi systems).

The new allocations are shown in Table 3. In the United States, the FCC
has initiated proceedings [15] to
upgrade to the allocations and to proscribe DFS for RLAN systems. In
addition, an ongoing informal effort of US government and industry
representatives, led by the National Telecommunications and Information
Administration (NTIA), plan to test DFS-enabled systems to verify
operations.

Dynamic Frequency Selection (DFS)
Unlike most technical restrictions of the ITU or regulatory agencies
like the FCC that define simple
power limits or similar constraints, the recommendation defined a
behavior-based mechanism, DFS. This
mechanism requires a rudimentary “cognitive” ability to understand the
radiofrequency environment and to adapt its operations.
The operations achieve the required protection of radar systems by
avoiding the use of, or vacating, a
channel identified as being occupied by radar equipment based on
detection of radar signals. The
parameters indicated in Table 4 define the performance of a set of
proscribed DFS behaviors (illustrated
in Figure 5):

Channel Availability Check. Before initiating transmissions on a
channel, a RLAN must monitor for a defined period (Channel availability
check time) the radio channel to determine whether a radar or other
signal is present based on a set threshold (DFS detection threshold) and
averaging period (1 µs).  ??In-Service Monitoring. The RLAN must
continually monitor the channel by searching for radar signals
in-between normal transmissions. This requires “quiet” periods between
bursts of data.  ??Channel Abdication. Upon detection of a signal above
the threshold (DFS detection threshold), the RLAN must cease all
transmission within a defined period (Channel move time). Normal data
transmissions may occur for a maximum of 200 ms with all control
signaling ending by the defined period (Channel move time).

??Channel Non-Occupancy. Once a channel has been determined to contain a
radar or other system signal, the RLAN must not utilize the channel for
a defined period of time (Non-occupancy time).  Essentially, the RLAN
implementation of DFS provides a “listen-before-talk” operation and
allows radar or other systems to essentially shut down the operations of
nearby RLANs through its own nominal or systematic transmissions. The
DFS mechanism requirements, however, do not specify the actual
methodology for channel reassignment or the technique used to detect
radar or other signals—these remain the province of the system designer.

Table 4: DFS Performance Requirements
Parameter Value
DFS detection threshold
(normalized to the output of a 0 dBi antenna)
–62 dBm for devices with a maximum e.i.r.p.
of < 200 mW and
–64 dBm for devices with a maximum e.i.r.p.
of 200 mW to 1 W averaged over 1 µs
Channel availability check time 60 s
Non-occupancy period 30 min
Channel move time ??10 s
Figure 5: Dynamic Frequency Selection (DFS) Operations
Design and Policy Implications

Although DFS-enabled RLANs provide only a rudimentary level of adaptive
spectrum capabilities, it does set precedence for “cognitive” systems. A
preliminary review reveals several key observations concerning the
process leading to the agreements and the specification of the DFS:

The ITU agreements define a set of behaviors required for a system and
specifically defines the associated functional and performance
requirements;

The required parameters were determined through models of existing
systems and statistical simulations of projected deployments;

Channel Availability
Check (60 sec)
Radar pulses
Non-occupancy period
(30 min)
Radar Signal (channel x)
RLAN
Transmissions (channel x)

Case 1) RLAN Detects Radar Signal on Channel x Prior to Operations
Channel Availability
Check (60 sec)
Radar pulse
Non-occupancy
period (30 min)
Radar Signal (channel x)
RLAN
Transmissions (channel x)
Case 2) RLAN Detects Radar Signal on Channel x After Operations
Initiated
Data bursts
Radar pulse detected
Channel move time (10 sec)

The agreement essentially defines a primary service (radiolocation) and
a subordinate user (mobile),
even though both services are nominal given “primary” allocation status;
and, ??Certification or other verification testing requires a test
program to not only measure specific parameters, as is classically
performed for certification, but also to certify behavior in a specified
radiofrequency environment--expanding the normal testing required for
regulatory certification.
Although the DFS mechanism is only proscribed for a limited set of
systems (RLANs operating in
specific 5 GHz bands), it does serve as a case study for cognitive
behavior that can be used to raise policy
questions including:

When defining a set of behaviors and associated parameters, should they
be defined based on existing
systems or should another means be used to consider possible future
systems that may promote innovation and introduction of new systems?
Can more extensive behaviors, such as interactive mechanisms requiring
negotiations (e.g., secondary
markets) or identification of specific systems, be defined rather than
purely reactive mechanisms?
Can behaviors be defined that do not necessitate primary and subordinate
systems?  ??Can a set of well-defined, high-level behaviors be defined
that can be used for defining appropriate “cognitive” functions?
Can a regularized set of test procedures be defined for any
behavior-based regulation?
The following section will explore these and other considerations.

6. Design and Policy Considerations

The increased capability of emerging adaptive spectrum radios to access
the spectrum across all its dimensions, on a cursory level, appears to
challenge notions of fixed frequency assignments and rigid
certification–pillars of the current spectrum regime. However, the
introduction of behavior-based regulation may provide a means to define
rights within the existing regulatory framework and regulatory models.
As noted earlier, adaptive capabilities are essentially fundamental to
improving spectrum utilization regardless of the underlying model
(command & control, commons, or exclusive use).
Development of the prototype adaptive systems along with the DFS case
study reveal several possible
mechanisms and parameters for adaptability that can be employed by
system designers and, possibly, for
policy. Behaviors may be either internal self-directed or external,
observable operations, with the
external behaviors of most interest for regulation. Table 5 provides a
high-level set of behaviors that can
define operations for adaptive systems. These high-level categories,
however, do not specify the sets of
parameters or details that may be necessary to enable sharing or other
desired outcomes. As an example,
the DFS mechanism is essentially a non-cooperative, casual behavior with
specific parameters (i.e.,
threshold detection levels, etc.) defined based on existing systems and
simulations to enable sharing
between dissimilar systems (radars and RLANs). Another possible casual
mechanism, “interference
temperature,” was identified by the FCC Spectrum Policy Task Force
report. This mechanism allows the
system to transmit as long as certain defined thresholds (“interference
temperature”) are not exceeded within a given region as defined by the
dimensions of the spectrum space. Of course, notions like “interference
temperature” may require additional knowledge of other systems within
the defined space so it may require an interactive approach.

Table 5: High-Level Adaptive Behaviors
High-Level Behavior (external) Mechanism/Parameter Considerations
Prohibited
Limit access through defined
spectrum space regions
(frequency band, time, location,
directionality, etc.)
May be used to protect existing
systems during introduction of
adaptive systems or for
protecting critical systems
Given location in the spectrum
space (e.g., physical location and
frequency), access may be
permitted with specific
constraints
May require mandated existence
and availability of databases
Given measured environment,
access may be permitted with
specific constraints
- Requires system to measure
environment and react
accordingly (e.g., DFS)
- May also include limits based
on the overall environment (e.g.,
“interference temperature”)
Casual (if-then)
Given signal identification,
access may be permitted with
specific constraints
Use of both databases and
measured environment to
determine actions
Interactive (negotiated or shared
control)
Negotiated access using
spectrum space dimensions
(e.g., request access to x band
during y timeframe in location z)
- Such behavior enables
regulatory constructs like
secondary markets
- Less interactive mechanisms,
such as beacons, can also be
used to define access
Dynamic
Rather than pre-defined actions,
systems can automatically
determine what criteria and
actions are needed based on
measurements, shared
information, and requirements
(e.g., interference levels)
Enables innovative concepts
based on dynamic system needs
and conditions

Such attempts for defining high-level behaviors and parameters, however,
may neglect the need to determine the highest level of spectrum access
principles. Rather than specifying detailed sets of behaviors and
parameters regulators and system designers may wish to consider ways to
define the overarching principles for achieving the goals of spectrum
management, centered on spectrum access.

Fundamental to any high-level principle is a set of clearly defined
access rights based on the full multidimensional
spectrum space. If achievable, such principles may allow systems to
adapt behavior based on the rights rather than highly defined mechanisms
like DFS.

Finally, these issues will be further explored as part of FCC
proceedings on cognitive radios and other topics resulting from the
Spectrum Policy Task Force report, including likely Notice of Inquiries
(NOIs) in the Fall of 2003. Another opportunity for involvement is the
DARPA XG program’s open “Request for Comment (RFC)” process soliciting
comments on its proposed vision and protocols [13]. This “RFC” effort
plans an extensive review of possible adaptive behaviors, protocols, and
policy.

7. Conclusion

Enabled by advances in technology and targeted research and development
programs, emerging systems
can adaptively access the spectrum across a wide-range of dimensions.
This increased capability raises a
number of questions for system designers and policy makers. As a first
step to defining future adaptive
spectrum access, this paper has identified, through the use of existing
demonstration efforts and a case
study, key considerations and questions for system designers and
regulators to consider, including
possible high-level sets of behaviors. Although no definitive proposals
are recommended, this study also
identified several opportunities in which researcher may wish to engage
to further explore and define the
future of adaptive spectrum access.

References

[1] Spectrum Policy Task Force Report, FCC, ET Docket No. 02- 135, Nov
2002
[2] D. Schaefer, “Wide Area Adaptive Spectrum Applications,” MILCOM
2001, Vienna, VA, Oct 2001
[3] W. Horne, P. Weed, & D. Schaefer, “Adaptive Spectrum Radio: A
Feasibility Platform On The Path
To Dynamic Spectrum Access,” International Symposium On Advanced Radio
Technologies, Boulder,
CO, 4-7 March 2003
[4] R. Berezdivin, R.Breinig, & R. Topp, “Next Generation Wireless
Concepts, Communications and
Technologies,” IEEE Commun. Mag., Mar 2002
[5] S. Nanda, K. Balachandran, & S. Kumar, “Adaptation Techniques in
Wireless Packet Data Services,”
IEEE Commun. Mag., Jan 2000
[6] R. J. Matheson, “The Electrospace Model as a Frequency Management
Tool,” International
Symposium On Advanced Radio Technologies, Boulder, CO, 4-7 March 2003
[7] FCC, Workshop on Cognitive Radio Technologies, 19 May 2003 (see TBD
web site for presentations)
[8] J. Mitola, Cognitive Radio: An Integrated Agent Architecture for
Software Defined Radio,
Dissertation, KTH, June 2000
[9] R. Coase, “The Federal Communications Commission,” 2 J. L. & ECON.
(1959), 1
[10] P. Marshall, “Spectrum Management Protocols in the DARPA Next
Generation Communications
Program,” SDR’02 Tech Conf, San Diego, Nov 2002
[11] W. Lehr, F. Merino, S. Eisner Gillett, “Software Radio:
Implications for Wireless Services, Industry
Structure, and Public Policy,” 2002 Telecommunications Policy Research
Conference, Alexandria, VA,
Sep 2002
[12] Defense Science Board, “Wideband Radio Frequency Modulation:
Dynamic Access to Mobile Information Networks,” Office of the Under
Secretary of Defense for Acquisition, Technology, and Logistics,
Washington, DC, July 2003 [13] DARPA XG Program web site:
http://www.darpa.mil/ato/programs/XG/ [14] Recommendation ITU-R M.1652,
“Dynamic frequency selection (DFS) in wireless access systems including
radio local area networks for the purpose of protecting the
radiodetermination service in the 5 GHz band,” (2003)
[15] FCC, Notice of Proposed Rulemaking, “Revision of Parts 2 and 15 of
the Commission’s Rules to
Permit Unlicensed National Information Infrastructure (U NII) devices in
the 5 GHz band,” ET Docket
No. 03 122, 2003

http://intel.si.umich.edu/tprc/papers/2003/225/Adaptive_Spectrum_Horne.pdf

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