Spectrum Sensing and Allocation
Techniques for Cognitive Radios
Farrukh Javed
F-05-020/07-UET - PHD-CASE-CP-40
Sequence of Presentation
 Section I – Cognitive Radios
 Introduction
 Next generation networks
 Cognitive radios
 Section II – Spectrum Sensing
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Transmitter detection
Cooperative detection
Interference based detection
Spectrum sensing challenges
 Section III – Spectrum Allocation
 Spectrum analysis
 Spectrum decision
 Section IV – Future of Cognitive Radios
 Conclusion
Cognitive Radios
Section – I
Motivation for Cognitive Radios
Spectrum Scarcity [1]
Motivation for Cognitive Radios
Spectrum Utilisation [1]
Motivation for Cognitive Radios
Measured Spectrum Occupancy Averaged over Six Locations
PLM, Amateur, others: 30-54 MHz
TV 2-6, RC: 54-88 MHz
Air traffic Control, Aero Nav: 108-138 MHz
Fixed Mobile, Amateur, others:138-174 MHz
TV 7-13: 174-216 MHz
Maritime Mobile, Amateur, others: 216-225 MHz
Fixed Mobile, Aero, others: 225-406 MHz
Amateur, Fixed, Mobile, Radiolocation, 406-470 MHz
TV 14-20: 470-512 MHz
TV 21-36: 512-608 MHz
TV 37-51: 608-698 MHz
TV 52-69: 698-806 MHz
Cell phone and SMR: 806-902 MHz
Unlicensed: 902-928 MHz
Paging, SMS, Fixed, BX Aux, and FMS: 928-906 MHz
IFF, TACAN, GPS, others: 960-1240 MHz
Amateur: 1240-1300 MHz
Aero Radar, Military: 1300-1400 MHz
Space/Satellite, Fixed Mobile, Telemetry: 1400-1525 MHz
Mobile Satellite, GPS, Meteorologicial: 1525-1710 MHz
Fixed, Fixed Mobile: 1710-1850 MHz
PCS, Asyn, Iso: 1850-1990 MHz
TV Aux: 1990-2110 MHz
Common Carriers, Private, MDS: 2110-2200 MHz
Space Operation, Fixed: 2200-2300 MHz
Amateur, WCS, DARS: 2300-2360 MHz
Telemetry: 2360-2390 MHz
U-PCS, ISM (Unlicensed): 2390-2500 MHz
ITFS, MMDS: 2500-2686 MHz
Surveillance Radar: 2686-2900 MHz
0.0%
25.0%
50.0%
Spectrum Occupancy
Spectrum Concentration [2]
75.0%
100.0%
Cognition
 Oxford English Dictionary definition of “cognition” as
“The action or faculty of knowing taken in its widest sense, including
sensation, perception, conception, etc., as distinguished from feeling and
volition”
 Encyclopedia Encarta defines “cognition” as
“To acquire knowledge by use of reasoning, intuition or perception”
 Encyclopedia of computer Sciences gives a three point
computational view of “cognition” as
“1. Mental state and processes intervene between input stimuli and output
responses
2.The mental state and processes are described by algorithms
3.The mental states and processes lend themselves to scientific investigations”
Cognitive Radio
 Joseph Mitola introduced the idea of Cognitive Radio in 2000 as
“Situation in which wireless nodes and related networks are sufficiently
computationally intelligent about radio resources and related computer to
computer communication to detect the user communication needs as a function of
user context and to provide the resources most required”
 Simon Haykin explains the concept in six key words
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Awareness
Intelligent
Learning
Adaptability
Reliability
Efficiency
 An intelligent radio capable of adapting itself to best suit its surrounding
radio environment
Operating Principal of CR
 Overlay CRs utilise the concept of spectrum holes
 Underlay CRs use the concept of interference temperature
Power
Overlay Cognitive Radios
Time
Frequency
Interference temperature model
 Interference temperatureTI is specified in Kelvin and is defined as
where PI (fc , B) is the average interference power inWatts centered at fc, covering bandwidth B measured
in Hertz. Boltzmann's constant k is 1.38 x 10-23
 Any Un-licensed transmission must not violate the interference temperature limit at the
licensed receivers. Mi is a fractional value between 0 and 1, representing a multiplicative
attenuation due to fading and path loss between the unlicensed transmitter and the
licensed receiver.
 The TL is to be decided by regulatory authority such as FCC or PTA
Underlay Cognitive Radios
Interference Temperature Model [10]
Interference Temperature Level
 Interference temperature is the maximum RF interference
acceptable at a receiving antenna
Basic Characteristics of
Cognitive Radios
 Cognitive Capability
 Re-configurability
Cognitive Capability
 Cognitive Cycle
 Spectrum Sensing
 Spectrum Allocation
 Spectrum Analysis
 Spectrum Decision
Cognitive cycle [3]
Re - Configurability
 Operating Frequency
 Modulation Scheme
 Transmission Power
 Communication Technology
 Directivity of Transmission
Next Generation Networks
 Introduction
 Protocol Layers and Cognitive Radio Functionalities
xG Network Functionalities [3]
Spectrum Sensing
Section – II
Spectrum Sensing Techniques
Spectrum
Sensing
Matched Filter
Detection
Transmitter
Detection
Cooperative
Detection
Energy
Detection
Cyclo-stationary
Feature
Detection
Interference
Based Detection
Transmitter Detection
 Introduction
 Techniques
 Matched Filter Detection
 Energy Detection
 Cyclo – Stationary Feature Detection
Matched Filter Detection
 Introduction
 Opportunities
 Commonly Used
 High Processing Gain
 Challenges
 Matched Filter Bound
 A priori knowledge of transmission is required
Energy Detection
 Introduction
 Opportunities
 Easy implementation
 Multi path and fading channel studies carried out
 Challenges
 Critical selection of threshold
 Susceptible to noise power variations
 Communication type identification not possible
 Reduced flexibility
Cyclo – Stationary Feature Detection
 Introduction
 Opportunities
 Robust against un-certain noise powers
 Transmitter information is not required
 Neural network application has been found very feasible
 Challenges
 Computationally complex
 Transmission type identification is not possible
 Reduced flexibility
Transmitter Detection Un – Certainties
 Receiver Un-certainty
 Shadowing Un-certainty
(a) Receiver Uncertainty (b) Shadowing Uncertainty [3]
Cooperative Detection
 Introduction
 Centralised Detection
 Distributed Detection
 Cooperative Detection Opportunities
 No receiver or shadowing un-certainties
 Effects of degrading factors mitigated
 Primary User’ interference reduced
 Cooperative Detection Challenges
 Implementation Complexity
 Constrained Resources
 Primary user un-certainty un-resolved
Interference Based Detection
Interference Temperature Model [10]
Opportunities and Challenges of
Interference Based Detection
 Opportunities
 Focus on primary receiver rather than primary transmitter
 Frequency parameters of choice can be utilised
 Challenge
 Receiver temperature detection
 Due to interference power constraints, the underlay techniques
can only be employed for short range communications
Few Generalised
Spectrum Sensing Challenges
 Multi user environment
 Interference temperature measurement
 Speed of detection etc.
Spectrum Allocation
Section – III
Spectrum Allocation
Spectrum Analysis
 Channel capacity
 Primary user related information
 xG user information
Channel Capacity
 Path Loss
 Wireless Link Layer
 Link Layer Delay
 Noise Info
User Related Information
(Primary and xG Users)
 Interference
 Holding Time
 User Transmission Parameters
Spectrum Analysis Challenges and
Opportunities
 Challenges
 Heterogeneous Spectrum Sensing
 Non Cooperative Primary and xG users
 Varying Transmission Parameters
 Real Time Analysis
 Delays in Processing
 Opportunities
Spectrum Decision
 Spectrum management
 Spectrum mobility
 Spectrum sharing
 User related info
Spectrum Management
 Decision Model
 Multiple Spectrum decision
 Reduced Transmission Power
 Cooperation with reconfiguration
 Heterogeneous Spectrum
Spectrum Mobility
 Introduction
 Challenges
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Latency
Suitable Algorithm
Appearance of a Primary User
Vertical and Inter-Cell Handoff Scheme
Suitable Threshold for Handoff
Spectrum Mobility in Time Domain
Spectrum Mobility in Space
 Opportunities
 Prioritised White Space
 Soft and Hard Handoff
Spectrum Sharing
 Architecture Based Classification
 Centralised or Distributed
 Challenges and Opportunities
 Access Behaviour Classification
 Cooperative and Non-cooperative Sharing
 Challenges and Opportunities
 Access Technology Classification
 Overlay and Underlay Techniques
 Challenges and Opportunities
 Generalised Spectrum Sharing Challenges
 Common control Channel
 Dynamic radio range
 Spectrum Unit
Future of Cognitive Radios
Section IV
Cognitive Radio Advantages
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All of the benefits of software defined radio
Improved link performance
Adapt away from bad channels
Increase data rate on good channels
Improved spectrum utilization
Fill in unused spectrum
Move away from over occupied spectrum
New business propositions
High speed internet in rural areas
High data rate application networks (e.g., Video-conferencing)
Significant interest from FCC, DoD
Possible use in TV band refarming
Cognitive Radio Drawbacks
 All the software radio drawbacks
 Significant research to realize
 Information collection and modeling
 Decision processes
 Learning processes
 Hardware support
 Regulatory concerns
 Loss of control
 Fear of undesirable adaptations
 Need some way to ensure that adaptations yield desirable
networks
How can CR improve spectrum
utilization?
 Allocate the frequency usage in a network
 Assist secondary markets with frequency use, implemented
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by mutual agreements
Negotiate frequency use between users
Provide automated frequency coordination
Enable unlicensed users when spectrum not in use
Overcome incompatibilities among existing communication
services
Potential Applications of CR
 Leased networks
 Military usage
 Emergency situations
 Mesh networks
 Licensed user may enhance its performance
 Improving UWB transmission by avoiding NBI
Jeffery H Reed and Wills G Worcester
Conclusion
Spectrum Sensing and Allocation Techniques for Cognitive Radios