1. Spectrum Sensing and Identification
Chapter 4
Spectrum Sensing and Identification
“Cognitive Radio Communications and Networks: Principles and Practice”
By A. M. Wyglinski, M. Nekovee, Y. T. Hou (Elsevier, December 2009)

2. Outline Introduction Primary Signal Detection
Spectrum Opportunities Detection
Performance vs. Constraint
Sensing Accuracy vs. Sensing Overhead

3. Introduction
Limited supply

4. Introduction
Growing demand

5. Current Policy & Spectrum Scarcity

6. Spectrum Opportunities in Space, Time, & Frequency
(Credit: DARPA XG)
(Credit: ACSP Cornell)

7. Primary Signal Detection
Choice of detectors
Criteria:
Bayesian
Neyman-Pearson
Parameter settings?
Energy detection
Pros: easily implemented; minimal assumptions
Cons: poor performance with noise uncertainty and with multiple secondary users
Performance ∼ 1/SNR2 at low SNR

8. Choice of Detectors - Cyclic Detectors (2)
Exploit guard bands in frequency, known carriers, data rates, modulation type
Pros:
fc, Ts easy to detect via square-law devices, or cyclic approaches
Cyclic approaches useful when σ2n is unknown (avoid SNR wall)
Easily implemented via FFTs
Cons:
Timing and frequency jitter can be detrimental
Requires long integration times
RF non-linearities; Spectral leakage (ACI).

9. Choice of Detectors: Matched Filter (3)
Exploit pilots or sync (PN) sequences in primary (WRAN )
Pros:
Correlation detection is usually better than energy detection.
Performance ∼ 1/SNR at low SNR
Cons:
fading may null pilot; need to cope with time and freq sync

10. Other Detectors Receiver leakage Wild-Ramachandran, Dyspan’05
Signal correlation Zeng et al, PIMRC’07
Fast fading Larson-Regnoli, CommLett’07
Multiple antennas Pandhripande-Linnartz, ICC’07
HMM classifier Kyouwoong et al, Dyspan’07
Wavelet-based Tian-Giannakis, CrownCom’06
Multi-resolution sensing Neihart-Roy-Allstot, ISCAS’07
Compressed sensing Tian-Giannakis, ICASSP’07

11. Spectrum Opportunities Detection
A channel is an opportunity for A − B if
the transmission from A to B can succeed
the interference power to primary is below a prescribed level

12. Spectrum Opportunity: Definition
A channel is an opportunity for A − B if
the transmission from A to B can succeed
the interference power to primary is below a prescribed level

13. Spectrum Opportunity: Definition
A channel is an opportunity for A − B if
the transmission from A to B can succeed
the interference power to primary is below a prescribed level

14. Spectrum Opportunity: Properties
Determined by both transmitting and receiving activities of primary users.
Asymmetric (an opportunity for A−B may not be one for B−A).

15. Detection of Primary Receivers
rI: interference range, Rp: primary tx range, rD: detection range
Detecting primary Rx within rI by detecting primary Tx within rD

16. Detecting Primary Signals (LBT)
rD: detection range.
H0: no primary Tx within rD, H1: alternative.
False alarms and miss detections occur due to noise and fading.

17. From Detecting Signal to Detecting Opportunity
H0: opportunity, H1: alternative.
Even with perfect ears, exposed Tx(X) ⇒ FA, hidden Rx(Y) ⇒ MD.
Adjusting detection range rD leads to different operating points.

18. When Is Detecting Signal = Detecting Opportunity?
A Necessary and Sufficient Condition:
NS condition: ∀X ∈ Ptx(A) ∩ Pctx(B), its receivers are in Prx(A)
Perfect detection achieved when detecting Ptx(A) ∪ Ptx(B)

19. Miss Detection May not Lead to Collision
There is no primary receiver around A
There are primary transmitters around B

20. Miss Detection May Lead to Success
There are primary receivers around A
There is no primary transmitter around B

21. Correctly Identified Opportunity May Not Lead to Success
Successful data transmission and failed ACK

22. Performance vs. Constraint
Optimal under relaxed constraint on the average number of active arms.
Asymptotically optimal (N →∞ w. M/N fixed) under certain conditions.
Near optimal performance observed from extensive numerical examples.

23. Performance vs. Constraint
Two Models
Global Interference Model
Local Interference Model

24. Performance vs. Constraint
Throughput comparison.

25. Sensing Accuracy vs. Sensing Overhead
Optimal sensing time: efficiency η versus sensing window length n for various SNRs and PMD.

26. Sensing Accuracy vs. Sensing Overhead
Optimal sensing time: efficiency η and optimal window length n∗/N versus slot length N.

27. Chapter 4 Summary The following topics have been covered:
Different types of detectors for primary signal detection
Detection of spectrum opportunities based on the detection of primary signals.
The trade-off between performance and interference constraint.
The trade-off between sensing accuracy and sensing overhead.