Background Spectrum Classification for Cognitive Radio Tree Scheme Simple Scheme Greedy SPRT Shridatt Sugrim, Melike Baykal-Gursoy and Predrag Spasojevic Motivation •Cognitive radios (CR) need to build a transmission strategy (TS) •This strategy is usually built blindly •No prior knowledge of Spectrum Occupancy •Given prior occupancy probabilities the CR could build a TS faster •CRs would be able to use more spectral opportunities and have a lower interference probability The Problem •Estimate probability of occupancy for each channel before the CR starts using them •Learning this model fast (limited number of measurement opportunities) •Satisfy a bound on probability of error for these estimates Our Solution • Change the problem to a Classification Problem (use composite Hypothesis) • Use a Sequential probability ratio test (SPRT) to minimize the number of samples need • SPRTs generate threshold lines • Use the distance to threshold lines as a measure of expected stopping time • Build a measurement distribution strategy that prioritizes channels with shorter stopping times Composite Hypothesis 1 : > ϕ Threshold Lines Completion distance , Alternative Approaches Performance The Result • Channels grouped by occupancy probability • Bounded probability of misclassification • CRs can now start sensing with the low occupancy set • CRs know to avoid the high occupancy set Probability of error Bounded misclassifica tion probability Channels Classified Sim ilar Discovery Rate 4 channels Classified Wasted Measurement s Wasted Measure ments Spectrum Occupancy SPRT < ( 1 , 1 ) … ( ¿ ¿ , 1 ) ( 1 , 0 ) … ( , 0 ) < ¿ Measurement distribution strategy ( , ) = { , + ( ) ∞ < > is a penalty for taking measurements is the channel index, is the sample index is the stopping time for channel

Background Spectrum Classification for Cognitive Radio

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Background Spectrum Classification for Cognitive Radio. Shridatt Sugrim, Melike Baykal-Gursoy and Predrag Spasojevic. Measurement distribution strategy. Our Solution. Motivation. The Problem. Change the problem to a Classification Problem (use composite Hypothesis) - PowerPoint PPT Presentation

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Background Spectrum Classification for Cognitive Radio

Tree Scheme

Simple SchemeGreedy SPRT

Shridatt Sugrim, Melike Baykal-Gursoy and Predrag Spasojevic

Motivation

• Cognitive radios (CR) need to build a transmission strategy (TS)• This strategy is usually built blindly •No prior knowledge of Spectrum Occupancy•Given prior occupancy probabilities the CR could build a TS faster• CRs would be able to use more spectral opportunities and have a lower interference probability

The Problem• Estimate probability of occupancy for each channel before the CR starts using them• Learning this model fast (limited number of measurement opportunities)• Satisfy a bound on probabilityof error for these estimates

Our Solution• Change the problem to a

Classification Problem(use composite Hypothesis)• Use a Sequential probability ratio

test (SPRT) to minimize the number of samples need• SPRTs generate threshold lines• Use the distance to threshold

lines as a measure of expected stopping time• Build a measurement distribution

strategy that prioritizes channels with shorter stopping timesComposite Hypothesis𝐻1 :𝑝>ϕ

Threshold Lines

Completion distance

𝑒𝑚 ,𝑛

Alternative Approaches

Performance

The Result• Channels grouped by occupancy

probability• Bounded probability of