Software Defined Radio Basics and its Role on Improvement of Cognitive Radio with an eye on Cognitive Radio Limits

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Software Defined Radio Basics and its Role on
Improvement of Cognitive Radio with an eye on
Cognitive Radio Limits

• ANKUSH HARIT
• HADI ALASTI

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Software Defined Radio
ANKUSH HARIT
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SOFTWARE DEFINED RADIO

• A radio implemented in software rather than
  hardware in which operational parameters like
  operating frequency range of the transmitter,
  type of modulation etc. can be changed by
  altering the software without any hardware
  changes.

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FEATURES

• Very less hardware required as software conducts
  a major role instead of hardware.
• Very flexible, can change software design
  depending on different protocols. Example, mobile
  phones tend to operate on different GSM bands in
  different countries.
• future-proof, multi-service, multi-mode,
  multiband, multi-standard terminals and
  infrastructure equipment

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BASIC DESIGN

• Includes three sections
• RF section(Analog hardware)
• IF section (Digital)
• Base band section (DIGITAL)

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WHAT YOUR SOFTWARE INCLUDES

• Signal modulation is generated or defined by the
  computer(microcontroller) or software.
• Baseband operations and processing and link layer
  protocols are implemented in software.

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HOW IT WORKS

• Waveforms are generated as sampled digital
  signals, converted from digital to analog via a
  wideband DAC and then possibly upconverted from
  IF to RF.
• The receiver, similarly, employs a wideband
  Analog to Digital Converter (ADC) that captures
  all of the channels of the software radio node.
• The receiver then extracts, downconverts and
  demodulates the channel waveform using software
  on a general purpose processor.

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ADVANTAGES

• Reconfigured easily.
• Quickly and easily upgradable with enhanced
  features.
• Can talk and listen to multiple channels at the
  same time.
• Can build new and unique radios according to
  specific needs.
• Cheap.

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EXAMPLES OF SDR
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RECENT DEVELOPMENTS

• Intel targets WiMAX with software radio device
• Can handle WiFi, WiMAX and Digital TV on single
  ship
• There is a shift from people wanting their
  content any time, anywhere to any device, any
  network, and the problem is there are too many
  radios, Jeff Hoffman, system architect for the
  wireless communications lab.

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Cognitive Radio
HADI ALASTI
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Cognitive Radio-1 Definition

• Original definition by Joseph Mitolla (1999)
• A radio that employs model based reasoning to
  achieve a specified level of competence in
  radio-related domains
• Simon Haykins definition (shortened)
• An ambient-aware, intelligent radio which learn
  from its surroundings and adapt itself to
• Highly reliable communication, anywhere,
  anytime
• Efficient use of Radio Spectrum

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Cognitive Radio-2 CR FCC

• FCC measurements 90 of the time, many licensed
  frequency bands remain unused.
• FCC is altering regulations for more flexible use
  of the licensed W-spectrum.
• FCC proposal on opportunistic channel usage
  cognitive radio listened to the W-channel in
  either time or frequency, which resources are
  unused (Figure).

• FCC 2nd market-oriented policies (2000)
• Spectrum leasing
• Dynamic spectrum leasing
• Private commons
• Interruptible spectrum leasing

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Cognitive Radio-3 Any Standards?

• FCC (NPRM) explored use of cognitive radio for
  dynamic spectrum allocation.
• IEEE 802.22 WG on Wireless Regional Area
  networks (WRAN) is developing a cognitive radio
  PHY/MAC for license-exempt devices on spectrum
  allocated to TV broadcast services.
• XG DARPA Program Millitary attempt to integrate
  dynamic spectrum allocation into network (Use of
  vacant holes of the spectrum, dynamically)

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Cognitive Radio-4 Pros Cons

• Pros
• Pros of SDR
• Utilize scarcity of the spectrum
• Connectivity between channels, waveforms, etc.
• Potentially creation of novel waveforms.

• Cons
• SDR Cons
• Complexity (S/W and H/W)
• Standardization (FCC)

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Cognitive Radio-5 CR in Advance

• Future CR (unlike XG-DARPA) uses
• Partially occupied parts of spectrum (grey).
• The unused parts of the spectrum (white)

For discrimination of the available spectrum and
existing signals, CR Employs 1- Clutter
Suppression (using sub-space enhancement or other
techniques) 2- Signal(s) Detection 3- Feature
Extraction (image processing, SVD, Mapping,
sub-space tracking) 4-Clustering (iterative
learning through adaptation, non-iterative
learning in initialization) 5- Signal
Classification (Computational, Statistical,
Connectionist approaches) 6- Machine Learning 7-
Proper Decision Metrics for Fair allocation of
spectrum
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Cognitive Radio-6 CR Machine learning

• In general, machine learning enables the
  cognitive communication system to
• Characterize the time and frequency domain
  behavior of the signal
• Predict the future time and frequency of the
  signal
• Identify the presence of the new signal types
• Construct models an features for new signal
  types
• Maintain the previously acquired knowledge about
  the signals
• Modify weightings based on the observed data

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Cognitive Radio-7 Application of Techniques ,an
example

• A learning module facilitates adaptation in the
  standard classification process, then the
  presence of new types of waveforms can be
  detected,
• Features that best facilitate classification of
  the previously and newly identified signals can
  be determined,
• Waveforms can be generated by using the basis-set
  orthogonal to the ones present in the
  environment.

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Cognitive Radio-8 Cognitive Communications
System Methodology and Signal Processing Flow
(General View)
Signal detection is followed by feature
extraction, clustering (unsupervised learning),
signal classification into types, machine
learning, and prediction to understand the time
and frequency domain behaviors of the existing
signals and, based on some decision metrics or
policies, to transmit the signals in both the
white and gray space so that new signals do not
interfere with existing ones
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Cognitive Radio-9 Limitation

• Capacity and the performance of the Cognitive
  Radio device depends on
• The number of existing active CR devices
• The interference level from each CR device
• The perfection of the implemented algorithm over
  SDR

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Cognitive Radio-10 Summary

• CR is going to be Standard in Future
• CR, by employing SDR let to use the spectrum
  more efficiently
• Intelligent signal processing, pattern
  classification, waveform design, machine
  learning and prediction algorithm should be
  employed
• Capacity and performance of CR is function of
  number and power of interfering signals,
  perfection of the implemented technologies and
  algorithms over SDR

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Cognitive Radio-11 References

• N. Mody, et. al. Recent Advances in Cognitive
  Communications, IEEE Communication Magazine, pp.
  54-61, October 2007
• N. Devroye, et al. Limits on Communications in a
  Cognitive Radio Channel, IEEE Communication
  Magazine, pp. 44-49, Jun. 2006.

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Questions?