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6 CRA V: Building the CRA on SDR Architectures

6 CRA V: Building the CRA on SDR Architectures

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Chapter 14



Radio Interface



N-/RT = Near Real Time and Real Time

Base Station

Offline Software



Online Software



N-/RT Software



Services

Development

Workstation(s)



Programmable

Processor(s)



Programmable

Processor(s)



Wideband

A/D–D/A



RF Conversion



Real-Time Stream

Modular, Open Architecture Host Hardware



To/From Public Switched Telephone Network (PSTN)



Figure 14.14: SWR principle applied to cellular-base station (© 1992 Dr. Joseph Mitola III,

used with permission).



conversion and intermediate frequency (IF) conversion. Given narrowband RF, the

hardware-defined radio might employ baseband (e.g., voice frequency) ADC,

DAC, and digital signal processing. The programmable digital radios (PDRs) of

the 1980s and 1990s used this approach. Historically, this approach has not been

as expensive as wideband RF (i.e., the cost of antennas, conversion), ADCs, and

DACs. Handsets are less amenable to SWR principles than the base station

(Figure 14.15). Base stations access the power grid. Thus, the fact that wideband

ADCs, DACs, and DSP (digital signal processor) consume many watts of power is

not a major design driver. Conservation of battery life, however, is a major design

driver in the handset.

Mobile Unit

Microphone

Video

Fax

Subscriber



Data Unit



Narrow band

A/D–D/A

(Optional Integral

Source Coding)



N-/RT Software

Programmable

Processor(s)



Wideband

A/D–D/A?



RF

Conversion



Highly Integrated Host Hardware



Radio Interface



Figure 14.15: SWR principle: “ADC and DAC at the antenna” may not apply (© 1992

Dr. Joseph Mitola III, used with permission).



Thus, insertion of SWR technology into handsets has been relatively slow.

Instead, the major handset manufacturers include multiple single-band RF chip

sets into a given handset. This has been called the “Velcro” radio or “slice” radio.

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Cognitive Radio Architecture

The ideal SWR is not readily approached in many cases, so the SDR has comprised a sequence of practical steps from the baseband DSP of the 1990s toward

the ideal SWR. As the economics of Moore’s law and of increasingly wideband

RF and IF devices allow, implementations move upward and to the right in the

SDR design space (Figure 14.16).

Digital Access Bandwidth



10 GHz



Digital RF

X



1 GHz



RF



SWR

100 MHz

V



Digital IF

D



ch



1 MHz



Te



SDR



100 kHz



B



10 kHz



IF



no

log

y



C

C



10 MHz



Digital Baseband



Baseband

A



Digital Radio

1 kHz

ASIC



FPGA



DSP



Function

per cm2



Function

per cm2



Function

per cm2



Dedicated

Silicon



Silicon

(Variable)



ISA +

Memory



General

Purpose

CISC

RISC

Function

per cm2

Memory



A – HF STR-2000

B – COTS Handset

C – SWR Cell Site

D – SPEAKeasy II

V – MIT Virtual Radio

[177, 178]

X – Ideal Software Radio



CISC : complex instruction set computer

ISA : instruction set architecture

RISC : reduced instruction set computer



Figure 14.16: SDR design space. This figure shows how designs approach the ideal SWR

(© 1996–2003 Dr. Joseph Mitola III, used with permission).



This space consists of the combination of digital access bandwidth and programmability. Access bandwidth consists of ADC/DAC sampling rates converted

by the Nyquist criterion13 and practice into effective bandwidth. Programmability



13



The Nyquist criterion is that a signal must be sampled at more than twice the highest-frequency

component that is present in the signal. Failure to do so will result in an alias, in which interference will be shifted from out of band to in the processing band. This is generally a distortion that

most systems cannot tolerate. In other words, the Nyquist frequency is half the sample rate of the

analog-to-digital (A/D) or digital-to-analog (D/A) converters.



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Chapter 14

of the digital subsystems is defined by the ease with which logic and interconnect

may be changed after deployment. Application-specific integrated circuits (ASICs)

cannot be changed at all, so the functions are “dedicated” in silicon. Field-programmable gate arrays (FPGAs) can be changed in the field, but if the new function

exceeds some performance parameter of the chip, which is not uncommon, then one

must upgrade the hardware to change the function, just like with ASICs. DSPs are

typically easier or less expensive to program and are more efficient in power use

than FPGAs. Memory limits and instruction set architecture (ISA) complexity can

drive up costs of reprogramming the DSP. Finally, general-purpose processors,

particularly reduced instruction set computers (RISCs), are most cost-effective to

change in the field. To characterize a multiprocessor, such as a cell phone with a

CDMA-ASIC, DSP speech codec, and RISC microcontroller, weight the point in

the design space by equivalent-processing capacity.

Where should one place an SDR design within this space? The quick answer

along a migration path of radio technology from the lower left toward the upper

right, benefiting from lessons learned in the early migration projects captured

in SRA [1].



14.6.2 Radio Architecture

The discussion of the SWR design space contains the first elements of radio architecture. It defines a mix of critical components for the radio. For SWR, the critical

hardware components are the ADC, DAC, and processor suite. The critical software components are the user interface; the networking software; the information

security (INFOSEC) capability (hardware and/or software); the RF media access

software, including the physical (PHY) layer modulator and demodulator (modem)

and media access control (MAC); and any antenna-related software, such as

antenna selection, beamforming, pointing, and the like. INFOSEC consists of

transmission security, such as the frequency-hopping spreading code selection,

plus communications security encryption.

The SDR Forum defined a very simple, helpful model of radio in 1997, which

is shown in Figure 14.17. This model highlights the relationships among radio

functions at a tutorial level. The CR has to “know” about these functions, so this

model is a good start because it shows both the relationships among the functions

and the typical flow of signal transformations from analog RF to analog or (with

SDR) digital modems, and on to other digital processing, including system control

of which the user interface is a part.

486



Cognitive Radio Architecture



Information Transfer Thread

Control



RF Modem



Transec



Message Processing and I/O



Com- Bridging Vocoding

Sec

Signaling



Routing



Management



Information

Security



Front-End

Processing



I/O



Control



Figure 14.17: SDR Forum (formerly MMITS) information transfer thread architecture

(© 1997 SDR Forum, used with permission).



This model, the techniques for implementing an SWR, and the various degrees

of SDR capability are addressed in depth in the various texts on SDR [22–25].

14.6.3 The SCA

The US DoD developed the SCA for its Joint Tactical Radio System (JTRS) family of radios. The SCA identifies the components and interfaces shown in Figure

14.18. The APIs define access to the PHY layer, to the MAC layer, to the logical

Physical



Non-CORBA

Physical

Component



MAC



LLC



Non-CORBA

MAC

Component



I/O



Non-CORBA

Security

Component



Non-CORBA

I/O

Component



RF

Physical Physical

MAC

MAC

Component Adapter Component Adapter

Physical

API



Link, Network

Components



MAC

API



Security

Security

Security

Adapter Components Adapter



LLC

API

Core Framework IDL



CORBA ORB and

Services (Middleware)



CF Services and

Applications



Link, Network

Components



Security

API



I/O

I/O

Adapter Components



LLC

API



I/O

API



(“Logical Software Bus” via CORBA)



CORBA ORB and

Services (Middleware)



CF Services and

Applications



Operating system



Operating system



Network Stacks and Serial Interface Services



Network Stacks and Serial Interface Services



Board Support Package (Bus Layer)



Board Support Package (Bus Layer)



Black (Secure) Hardware Bus



Red (Non secure) Hardware Bus



Figure 14.18: JTRS SCA Version 1.0 (© 2004 SDR Forum, used with permission).



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Chapter 14

link control (LLC) layer, to security features, and to the input/output of the physical radio device. The physical components consist of antennas and RF conversion

hardware that are mostly analog and that typically lack the ability to declare or

describe themselves to the system. Most other SCA-compliant components are

capable of describing themselves to the system to enable and facilitate plug-andplay among hardware and software components. In addition, the SCA embraces

the portable operating system interface (POSIX) and CORBA.

The model evolved through several stages of work in the SDR Forum and

OMG into a UML-based object-oriented model of SDR (Figure 14.19).

Waveforms are collections of load modules that provide wireless services, so from

a radio designer’s perspective, the waveform is the key application in a radio.

From a user’s perspective of a wireless PDA (WPDA), the radio waveform is just

a means to an end, and the user doesn’t want to know or to have to care about

waveforms. Today, the cellular service providers hide this detail to some degree,

but consumers sometimes know the difference between CDMA and GSM, for

example, because first generation CDMA works in the United States, but not in

Europe. With the deployment of the 3G of cellular technology, the amount of

technical jargon consumers will need to know is increasing. So the CRA insulates

the user from those details, unless the user really wants to know.



SDR Domain Architecture

Components Logical Model



Waveform/Application



Waveform/Applications



User Services’ resources

User Services’ resources

User Services’ resources

User Services’ resources

User Services’ resources

User Services’ resources

User Services’ resources

User Services’ resources

User Services’ resources

User Services’ resources



Applications/waveforms

and platform APIs



Anterna



Amp



RF



Interference

Management



Modem



Black

Processing



INFOSEC



Red

Processing



Network



I/O



Managed



Services Architecture



Managed

Managed



Managed



Managed Managed Managed Managed Managed

Managed



Managed



Figure 14.19: SDR Forum UML model of radio services (© 2004 SDR Forum, used with

permission).



In the UML model shown in Figure 14.19, Amp refers to amplification services, RF refers to RF conversion, interference management refers to both avoiding

interference and filtering it out of one’s band of operation. In addition, the jargon

488



Cognitive Radio Architecture

for US military radios is that the “red” side contains the user’s secret information,

but when it is encrypted it becomes “black,” or protected, so it can be transmitted.

Black processing occurs between the antenna and the decryption process. Notice

also that Figure 14.19 has no user interface. The UML model contains a sophisticated set of management facilities, illustrated further in Figure 14.20, to which the

human–machine interface (HMI) or user interface is closely related.



Managed



Local or

Remote



Managed



Managed



Managed Managed Managed Managed



Managed

Managed



Managed

Services Inherit Framework

Services from System Control

which Inherits from Framework



HMI

Initiates management



System

Control



Managed



Uses framework services



Provides Physical

Interconnects



Managed



Fault

Management



Management

Architecture



Configuration

Management



Framework

global



Security

Management



Virtual Channel

Management



Performance

Management

Networld

Management



System

Fabrio

Computational

Architecture



Figure 14.20: SDR Forum UML management and computational architectures (© 2004 SDR

Forum, used with permission).



Systems control is based on a framework that includes very generic functions

such as event logging, organized into a computational architecture, heavily influenced by CORBA. The management features are needed to control radios of the

complexity of 3G and of the current generation of military radios. Although civil

sector radios for police, fire, and aircraft lag these two sectors in complexity and

are more cost-sensitive, baseband SDRs are beginning to insert themselves even

into these historically less technology-driven markets.

Fault management features are needed to deal with the loss of a radio’s processors, memory, or antenna channels. CR therefore interacts with fault management

to determine what facilities may be available to the radio given recovery from hardware and/or software faults (e.g., error in a download). Security management is

increasingly important in the protection of the user’s data by the CR; balancing

convenience and security can be very tedious and time consuming. The CR will

direct virtual channel management (VCM) and will learn from the VCM function

489



Chapter 14

what radio resources are available, such as what bands the radio can listen to and

transmit on and how many bands it can use at once. Network management does for

the digital paths what VCM does for the radio paths. Finally, SDR performance

depends on the availability of analog and digital resources, such as linearity in the

antenna, millions of instructions per second (MIPS) in a processor, and the like.

14.6.4 Functions-Transforms Model of Radio

The CRA uses a self-referential model of a wireless device, the functions-transforms

model, to define the RKRL and to train the CRA. In this model, illustrated in Figure

14.21, the radio knows about sources, source coding, networks, INFOSEC, and the

collection of front-end services needed to access RF channels. Its knowledge also

extends to the idea of multiple channels and their characteristics (the channel set),

and the radio part may have many alternative personalities at a given point in time.

Through evolution support, those alternatives change over time.

External Environment

Source

Set



Source

Coding

and

Decoding

Radio Node



Evolution

Support



Service

and

Network

Support



INFOSEC



Modem



IF

Processing



Channel

Set



RF/

Channel

Access



Channel Coding and Decoding



Joint Control

Multiple Personalities



Figure 14.21: Functions-transforms model of a wireless node (© 1996 Dr. Joseph Mitola III,

used with permission).



CR reasons about all of its internal resources via a computational model of

analog and digital performance parameters, and how they are related to features

it can measure or control. MIPS, for example, may be controlled by setting the

clock speed. A high clock speed generally uses more total power than a lower

clock speed, and this tends to reduce battery life. The same is true for the brightness of a display. The CR only “knows” this to the degree that it has a data structure that captures this information and algorithms, preprogrammed and/or learned,

that deal with these relationships to the benefit of the user. Constraint languages

may be used to express interdependencies, such as how many channels of a given

490



Cognitive Radio Architecture

personality are supported by a given hardware suite, particularly in failure modes.

CR algorithms may employ this kind of structured reasoning as a specialized KS

when using case-based learning to extend its ability to cope with internal changes.

The ontological structure of the above may be formalized as shown by the

equation in Figure 14.22.



















Figure 14.22: Equation that defines SDR subsystem components.



Although this text does not offer a comprehensive computational ontology of

SDR, semantically based dialogs among AACRs about internal issues such as

downloads may be mediated by RXML with the necessary ontological structures.

14.6.5 Architecture Migration: From SDR to AACR

Given the CRA and contemporary SDR architecture, one must address the transition of SDR through a phase of AACRs, toward the iCR. As the complexities of

handheld, wearable, and vehicular wireless systems increase, the likelihood that

the user or network will have the skill necessary to do the optimal thing in any

given circumstance is reduced. Today’s cellular networks manage the complexity

of individual wireless protocols for the user, but the emergence of multiband

multimode AACR moves the burden for complexity management toward the

PDA. Likewise, the optimization of the choice of wireless service between the

“free” home WLAN and the “for-sale” cellular equivalent moves the burden of

radio-resource management from the network to the WPDA.

14.6.6 Cognitive Electronics

The increasing complexity of the PDA–user interface also accelerates the trend

toward increasing the computational intelligence of personal electronics. AACR is

in some sense just an example of a computationally intelligent personal electronics system. For example, using a laptop computer in the bright display mode uses

up the battery power faster than when the display is set to minimum brightness.

491



Chapter 14

A cognitive laptop could offer to further the brightness level when reduce only

half charged in battery-powered mode. It would be even nicer if it would recognize operation aboard a commercial aircraft and know that the user’s preference is

to set the brightness low on an aircraft to conserve the battery, and automatically

do so. A cognitive laptop shouldn’t make a big deal over that, and it should let the

user turn up the brightness without complaining. If it had an ambient light sensor

or ambient light algorithm for an embedded camera, it also could tell that a window shade was open and that the user has to deal with the brightness. By sensing

the brightness of the on-board aircraft scene and associating the user’s control of

the brightness of the display with the brightness of the environment, a hypothetical cognitive laptop could learn advice the user to do the right thing in the right

situation (pull down the shade).

How does this relate to the CRA? For one thing, the CRA could be used as-is

to increase the computational intelligence of the laptop. In this case, the self is the

laptop and the PDA knows about itself as a laptop, not as a WPDA. It knows about

its sensors suite, which includes at least a light-level sensor if not a camera through

the data structures that define the . It knows about the user by observing

keystrokes and mouse action as well as by interpreting the images on the camera; it

verifies that the user is still the owner because that is important to building userspecific models. It might build a space–time behavior model of any user or it might

be a one-user laptop. Its actions include the setting of the display intensity level. In

short, the CRA accommodates the cognitive laptop with suitable laptop knowledge

and functions implemented in the CRA map sets.

14.6.7 When Should a Radio Transition toward Cognition?

If a wireless device accesses only a single-RF band and mode, then it is not a very

good starting point for CR—it’s just too simple. Even as complexity increases, as

long as the user’s needs are met by wireless devices managed by the network(s),

then embedding computational intelligence in the device has limited benefits. In

1999, Mitsubishi and AT&T announced the first “four-mode handset.” The T250

operated in Time Division Multiple Access (TDMA) mode on 850 or 1900 MHz,

in first-generation Advanced Mobile Phone System (AMPS) mode on 850 MHz,

and in Cellular Digital Packet Data (CDPD) mode on 1900 MHz. This illustrates

the early development of multiband, multimode, multimedia (M3) wireless. These

radios enhanced the service provider’s ability to offer national roaming, but the

complexity was not apparent to the user because the network managed the radio

resources of the handset.

492



Cognitive Radio Architecture

Even as device complexity increases in ways that the network does not manage, there may be no need for cognition. There are several examples of capabilities embedded in electronics typically are not heavily used. For example, how

many people use their laptop’s speech recognition system? What about its Infrared

Data Association (IrDA) port? The typical users in 2004 didn’t use either capability of their Windows XP laptop all that much. So complexity can increase without

putting a burden on the user to manage that complexity if the capability isn’t central to the way in which the user employs the system.

For radio, as the number of bands and modes increases, the SDR becomes a better candidate for the insertion of cognition technology. But it is not until the radio or

the wireless part of the PDA has the capacity to access multiple RF bands that cognition technology begins to pay off. With the liberalization of RF spectrum use

rules, the early evolution of AACR may be driven by RF spectrum-use etiquette for

ad hoc bands such as the FCC use case. In the not-too-distant future, SDR PDAs

could access satellite mobile services, cordless telephone, WLAN, GSM, and 3G

bands. An ideal SDR device with these capabilities might affordably access three

octave bands, from 0.4 to 0.96 GHz (skipping the air navigation and GPS band from

0.96 to 1.2 GHz), from 1.3 to 2.5 GHz, and from 2.5 to 5.9 GHz (Figure 14.23). Not

counting satellite mobile and radio navigation bands, such radios would have access



HF



LV HF



2 MHz 28



VHF-UHF

88



Cellular



PCS



Indoor and RF LAN



400 960 MHz 1.39 GHz 2.5



VHDR



5.9 6 34 GHz



Antenna-Sensitive

(Notional)

Fixed Terrestrial

(Notional)

Cellular Mobile

(Notional)

Public Safety

(Notional)

Land Mobile

(Notional)



Local Multipoint

Distribution (LMDS)



Other*

(Notional)

Cognitive

Radio Pools



Very Low Band



Low



Mid Band



High Band



*Includes broadcast, TV, telemetry, amateur, ISM (Industrial, scientific, medical);

VHDR: Very High Data Rate; VHF: very high frequency; UHF: ultra high frequency.



Figure 14.23: Fixed spectrum allocations versus pooling with CR (© 1997 Dr. Joseph Mitola

III, used with permission).



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Chapter 14

to more than 30 mobile subbands in 1463 MHz of potentially sharable outdoor

mobile spectrum. The upper band provides another 1.07 GHz of sharable indoor and

RF-LAN spectrum. This wideband radio technology will be affordable first for military applications, next for base station infrastructure, then for mobile vehicular

radios, and later for handsets and PDAs. When a radio device accesses more RF

bands than the host network controls, it is time for CR technology to mediate the

dynamic sharing of spectrum. It is the well-heeled conformance to the radio etiquettes afforded by CR that makes such sharing practical.

14.6.8 Radio Evolution toward the CRA

Various protocols have been proposed by which radio devices may share the radio

spectrum. The US FCC Part 15 rules permit low-power devices to operate in some

bands. In 2003, a Report and Order (R&O) made unused TV spectrum available

for low-power RF-LAN applications, making the manufacturer responsible for

ensuring that the radios obey this simple constraint. DARPA’s XG program developed a language for expressing spectrum use policy [26]. Other more general protocols based on peek-through to legacy users have also been proposed [33].

Does this mean that a radio must transition instantaneously from the SCA to

the CRA? Probably not. The six-component AACR architecture may be implemented with minimal SP, minimal learning, and no autonomous ability to modify

itself. Regulators hold manufacturers responsible for the behaviors of such radios.

The simpler the architecture, the simpler the problem of explaining it to regulators

and of getting concurrence among manufacturers regarding open architecture

interfaces that facilitate technology insertion and teaming. Manufacturers who

fully understand the level to which a highly autonomous CR might unintentionally

reprogram itself to violate regulatory constraints may decide they want to field

aware–adaptive (AA) radios, but may not want to take the risks associated with

self-modifying CRs just yet.

Thus, one can envision a gradual evolution toward the CRA beginning initially

with a minimal set of functions mutually agreeable among the growing community of AACR stakeholders. Subsequently, the introduction of new services will

drive the introduction of new capabilities and additional APIs, perhaps informed

by the CRA.



14.7 Cognition Architecture Research Topics

The cognition cycle and related inference hierarchy imply a large scope of

hard research problems for CR. Parsing incoming messages requires NL text

494



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