Performance of Spectrum

1
Performance of Spectrum Monitoring for Channel
Selection in Cognitive Radio
Prashant Bajpayee
Advisor Dr. Daniel Noneaker
SURE 2005

• Motivation
• Currently most radio-frequency spectrum is
  assigned exclusively to primary users (e.g.
  Broadcasting of T.V. channels)
• Assigned spectrum is often underutilized in many
  locations at specific times
• This unused spectrum is lost opportunity for
  other potential communication systems
• General Solution
• Exploitation of unutilized spectrum on
  secondary user basis and Cognitive radio is
  viewed as a novel approach for efficient
  utilization

• System Details
• Multiple channel communication system
• Channel monitoring approach used by destination
• When no data is transmitting, sequentially
  monitor channel to determine level of noise in
  each channel
• When RTS is received,destination should send CTS
  specifying channel with least intereference.

• Assume DS Spread Spectrum binary antipodal
  signaling is used by transmitter so that
• During monitoring of traffic channel j its
  received signal is and
  are
  independent random process
• Two types of channel
• Good channel with lesser interference
• Bad channel with more noise interference

• Decision Statistic
• Monitor channel 1 by forming statistic
• Where
  
• Detection Technique
• Similarly for all channels we generate chi-square
  random variable with degree 2n and pick
  channel with smallest value of
  

• Characteristic of CR
• Intelligent wireless communication system
• Aware of its environment
• Methodology of understanding-by-building to learn
  from environment
• Adapt to statistical variances in the
  input-stimuli
• Reconfigurable
• CR has the capability of reconfigurability which
  is provided by a platform known as Software-
  defined radio on which CR is built

• Generalized Model
• CR alters between frequency monitoring and other
  tasks
• Each channel has time-varying interference/noise
• Now each channel is represented as two-state
  Markov random process
• state of channel 1 at time k, may be 0 or
  1

0
1

• Conclusions
• On increasing n, error probability decreases.
• On increasing c, error probability decreases.

• Advantages
• Highly reliable communications whenever and
  wherever needed
• Efficient utilization of the radio spectrum
• Dynamically reuse available spectrum by changing
  its parameter

• Conclusions
• For large T-coh, increasing channel , error
  probability decreases.
• For moderate T-coh, there is an optimal number
  of channel.

• Now each channel can be said good or bad
  depending upon its state at that time
• All Channels changes their states after each time
  interval n
• New decision statistics are generated after nn1
  time interval but only for one channel at a
  time
• Efficiency of system n1/nn1

Monitor f2
Monitor f1
n1 qn
-----
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• Key properties of Cognitive Radio
• This Spectrum monitoring capability
• Dynamic spectrum assignment protocols/rules
• Purpose of Research
• Development and simulation of a mathematical
  model of channel monitoring function of CR
• Analyze the effect of time-varying interference
  in each channel and design trade-offs that result

t0
2n2n1
LnLn1
work
work
n
nn1
2nn1

• Conclusions
• For fixed efficiency and T-coh, there is an
  optimal n.
• Increasing efficiency, increases error
  probability.
• Increasing efficiency, decreases n-optimal.

• Conclusions
• On increasing n, error probability decreases.
• On increasing c, error probability decreases.

• Acknowledgement
• Dr. Daniel Noneaker
• Dr. Harlan Russell
• Dr. Xiao-Bang Xu
• Dr. Michael Pursley
• NSF

• Future work
• Consider a more general Markov model with
  different parameter
• Examine the performance in terms of bit error
  probability
• Analyze the effect of mutual coupling amongst
  different radios on channel-noise distribution
  of each radio.

• c ratio of noise variances of good and bad
  channels
• Assume
• Pe Probability of selecting BAD channel
• Channel no. of channels in radio.

Simulation Details n time required to generate
each statistics and qual to number of chi-square
random variables which add up to form a test
statistic n1 the time radio spends on other
tasks T_coh measure of rate of change of states