1. Cooperative spectrum sensing in cognitive radio Aminmohammad Roozgard

2. Users Primary User (PU) Secondary User (SU) Cognitive Radio(CR)

3. Definition Probability of False alarm: – probability of a CR user declaring that a PU is present when the spectrum is actually free Probability of detection: – probability of a CR user declaring that a PU is present when the spectrum is indeed occupied by the PU

4. objectives CR users should not cause harmful interference to PUs by either switching to an available band or limiting its interference with PUs at an acceptable level CR users should efficiently identify and exploit the spectrum holes for required throughput and quality-of-service (QoS)

5. Sensing problems multipath fading Shadowing the receiver uncertainty problem

6. Why cooperation enhance the sensing performance by using the spatial diversity in the observations of spatially located CR users (detection performance cannot be improved by increasing the sensitivity, when the SNR of PU signals is below a certain level)

7. Gain vs Overhead Cooperation Gain – performance improvement due to spatial diversity Cooperation Overhead – any extra sensing time, delay, energy, and operations devoted to cooperative sensing compared to the individual (non-cooperative) spectrum sensing case – any performance degradation in correlated shadowing or the vulnerability to security attacks

8. Main questions How can cognitive radios cooperate? (cooperation methods) How much can be gained from cooperation? (cooperation gain) What is the overhead associated with cooperation? (cooperation overhead)

9. Signal detection

10. Cooperation categories a)Centralized b)Distributed c)Relay-assisted

11. Channels Sensing channel: – selected licensed channel where a physical point- to-point link between the PU transmitter and each cooperating CR user for observing the primary signal Reporting channel: – For data reporting, all CR users are tuned to a control channel where a physical point-to-point link between each cooperating CR user and the FC for sending the sensing results

12. Centralized Cooperation the Fusion Center (FC) selects a channel for sensing and instructs all cooperating CR users to individually perform local sensing all cooperating CR users report their sensing results via the control channel the FC combines the received local sensing information, determines the presence of PUs, and diffuses the decision back to cooperating CR users

13. Distributed Cooperation does not rely on a FC for making the cooperative decision CR users communicate among themselves and converge to a unified decision on the presence or absence of PUs – by iterations – based on a distributed algorithm, each CR user sends its own sensing data to other users combines its data with the received data decides whether or not the PU is present sends its decision repeat until converge

14. Relay-assist cooperation both sensing channel and report channel are not perfect – a CR user observing a weak sensing channel and a strong report channel – a CR user with a strong sensing channel and a weak report channel CRs can complement and cooperate with each other to improve the performance of cooperative sensing

15. Cooperation steps Local sensing Reporting Data Fusion

16. Elements of cooperation Cooperation models: how CRs cooperate for sensing – parallel fusion network models – game theoretical models Sensing techniques taking observation samples

17. Elements of cooperation Hypothesis testing a statistical test to determine the presence or absence of a PU. – individually by each cooperating user – performed by the fusion center Control channel and reporting concerns how the sensing results can be efficiently and reliably reported – bandwidth-limited – fading-susceptible control channel

18. Elements of cooperation Data fusion: process of combining the reported shared sensing results – signal combining techniques – decision fusion rules User selection: how to optimally select the cooperating CRs – maximize the cooperative gain – minimize the cooperation overhead Knowledge base stores the information of sensing – improve the detection performance – a priori knowledge – knowledge accumulated through the experience.

19. Cooperation models Parallel fusion model – sensing Game theoretical models – Cooperation

20. Sensing Technique Wide band Narrow band Coherent – Using prior knowledge Non coherent – No prior knowledge

21. Sensing Technique Energy detection – Long sensing time – depend on noise – No distinguish between PU & SU Cyclostationary feature detection – High computational complexity – Long sensing time Compressed sensing – Hardware

22. Hypothesis testing Binary hypothesis testing – Likelihood ratio test (LRT) – Bayes test Composite hypothesis testing Sequential testing – Two thresholds

23. Control channel Bandwidth requirement – Censoring reduces the unnecessary reporting and the usage of control channel bandwidth – Fixed bands – Dynamic bands Reliability requirement – perfect error-free control channel – Gaussian noise – multipath fading – correlated shadowing

24. Data Fusion Soft combining – complete local test statistics – Best Result – Methods: Equal gain combining (EGC) Maximal ratio combining (MRC) Quantized soft combining – Only the quantized data for soft combining Hard combining – users make a local decision and transmit the one bit decision – Less channel bandwidth – Methods: And Or Majority

25. User Selection independent CR users for cooperation can improve the robustness of sensing results removing malicious users Methods: – Centralized selection – Cluster-based selection

26. Knowledge base Rules – enhance the detection performance Accumulated knowledge Learned experience – alleviate the burden of cooperative sensing retrieving the spectrum information – list of PU-occupied channels from the database. Approaches – radio environment map (REM) – received signal strength (RSS) profiles – Channel gain map – power spectral density (PSD) map

27. gain and overhead sensing time and delay – Number of samples – Collision on report Channel – Relay data* – Synchronization* channel impairments – Multipath fading and shadowing – Spatially correlated shadowing having a small number of CR users over a large distance may be more effective than a large number of closely located users

28. gain and overhead energy efficiency – Censoring Users – Sleeping – Optimal sensing time* – Optimal number of CRs* cooperation efficiency – Sensing scheduling* – Speed of converge* Mobility – PU mobility* – SU mobility

29. gain and overhead Security – Data falsification Anomaly detection* – Attacks PU emulation attack Control channel jamming Node capture attack* wideband sensing – Multi-band cooperative sensing* – Wideband cooperative sensing*

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32. Reference Akyildiz, Ian F., Brandon F. Lo, and Ravikumar Balakrishnan. "Cooperative spectrum sensing in cognitive radio networks: A survey." Physical Communication 4, no. 1 (2011): 40- 62.

34. Example Movement