Impact of Mobility on Spectrum Sensing in Cognitive Radio Networks

1. Impact of Mobility on Spectrum Sensing in Cognitive Radio Networks Alexander W. Min and Kang G. Shin Real-Time Computing Laboratory (RTCL) Electrical Engineering and Computer Science (EECS) The University of Michigan

2. Introduction • Cognitive Radio Networks (CRNs) • Improve spectrum efficiency via opportunistic spectrum access • Primary and secondary users share spectrum • IEEE 802.22 WRANs •CR-based international standard •Infrastructure-based network •Primary : TV transmitters or WMs •Secondary : CPEs (i.e., houses) Provide wireless broadband access in rural areas by reusing TV bands Spectrum sensing - key enabling technology

3. Spectrum Sensing in IEEE 802.22 • Requirements for in-band sensing in IEEE 802.22 • Secondary users must detect: -- Very weak primary signals (< -20 dB) -- Small delay (CDT < 2 seconds) Constraints -- High accuracy (PFA, PMD < 0.1) • Limited sensing time (QoS) Single sensor with one-time sensing is NOT enough • MAC-layer solution approaches Our focus Sensor cooperation Sensing scheduling + MAC PHY Energy detection

4. Tradeoff: Cooperation vs. Scheduling t0 t0 time time • In-band sensing in IEEE 802.22 Feature detection : Accurate, BUT expensive Energy detection : Simple, BUT inaccurate CDT (2 seconds) … t0 time Q1) How many and which sensors? (Cooperative sensing) … –)Reporting time Q2) How many times to sense? (sensing scheduling) –) Detection delay, frequent interruptions Minimize sensing overheads under detectability requirements

5. Related Work – Spectrum Sensing • MAC-layer approaches • [Visotskyet al. 05] • Cooperative sensing with i.i.d. sensors • [Lee and Akyildiz 08] • Optimal framework for spectrum selection and scheduling • [Ghasemi and Sousa 07] • Asymptotic performance of cooperative sensing under correlated shadowing • [Kim and Shin 08] • Optimal in-band sensing in 802.22 • [Huang et al. 09] • Tradeoff in sensing-transmission policy • [Selenet al. 08] • Sensor selection for i.i.d. sensors • [Min and Shin 09] • Optimal sensor selection and optimal stopping time for scheduling sensing None of them considers mobile sensors

6. Motivation • Mobile Sensors in CRNs • Portable devices in IEEE 802.22 • Challenges: sensing, interference management, routing etc Q) How much performance gain from mobile sensors?

7. How much gain from stationary sensors? • Spatio-Temporal variations in RSSs Sensors with high RSSs Sensors with low RSSs Location-dependent RSSs Cooperation > Scheduling Limited sensing scheduling gain A. W. Min, K.G. Shin, An Optimal Sensing Framework based on RSS-profile in Cognitive Radio Networks, In Proc. IEEE SECON 2009, Rome, Italy

8. Why mobile sensors? • Stationary vs. Mobile sensors 2-D shadowing field Test Statistics static sensor mobile sensor Mobility increases spatio-temporal variations in RSSs

9. Outline • Sensing performance analysis • Test Statistic: single/multiple sensors • Hypothesis testing • Sensing scheduling gain • Optimal sensing strategy • Cooperative sensing vs. sensing scheduling • Numerical results • Conclusion and Future work

10. Test statistics - single sensor • Single mobile sensor • Test statistics – Gaussian approximation • • Covariance matrix • • Correlation function Vn : speed of sensor n ∆t : sensing interval • Each sensor has correlated measurements

11. Test statistics - multiple sensors • Multiple mobile sensor • • Hypothesis testing • • Covariance matrix Sequence of measurements are independent among sensors

12. Sensing Performance - analysis • Log-likelihood Ratio Test (LRT) • • Likelihood function x: (NM)-dimensional Gaussian r.v. • • Theoretical performance Detection performance depends on: Sensor speed, sensing interval, de-correlation distance, etc

13. Scheduling gain - analysis • Sensor cooperation vs. sensing scheduling • • Sensing scheduling gain Def) Thenumber of i.i.d. stationary sensors required to achieve the same level of sensing performance with a single mobile sensor • Asymptotic performance • As Δd  ∞, sensing M times is equivalent to having M i.i.d. sensors 1 ≤ scheduling gain ≤ M V=0 V= ∞

14. Scheduling gain – numerical results Mobility increases sensing scheduling gain

15. Optimal Sensing Strategy • Objective • • Minimize the sensing overheads while meeting • the detection requirements • Types of overheads • • Throughput overhead (tr) • • Delay overhead (td) • • Energy overhead (ε) • Sensing overhead minimization • • Objective function • • Optimal combination of (N,M)

16. Effect of sensor speed Fast moving sensors improve sensing performance Severe shadowing

17. Effect of sensing scheduling Mobility improves detection performance

18. Effect of received signal strength Mobility helps in low SNR environments

19. Tradeoff : cooperation vs. scheduling Space vs. time domain sensing

20. Minimum sensing overhead Optimal sensing strategy depends on sensing cost

21. Summary & Future work • Mobile sensors in CRNs • Tradeoff in cooperation vs. scheduling • Achievable sensing performance gain Sensor mobility improves sensing performance! • Future work • Hybrid use of static and mobile sensors • Mobility for small-scale primary detection

22. Thank you Alexander W. Min alexmin@eecs.umich.edu Visit Real-Time Computing Lab (RTCL) http://kabru.eecs.umich.edu