1. An algorithm for dynamic spectrum allocation in shadowing environment and with communication constraints Konstantinos Koufos Helsinki University of Technology Communications Laboratory Instructor : Lic. Tech. Kalle Ruttik Supervisor : Professor Riku Jäntti

2. CONTENTS  Motivation  Background work  System Model  Proposed algorithm  Power detection  Distributed power detection  Results  Conclusions  Future work

3. MOTIVATION  Measurements show that the spectrum is underutilised (TV Broadcast) ─ Rightful owners leave it partially unused (temporarily,spatially)  Sporadically used spectrum could be accessed by other users too  This access is called Dynamic Spectrum Allocation (DSA)  DSA access : Efficient and Adaptive

4. BACKGROUND WORK  Co-existence – Interference control  Two step decision  What is the worst case scenario? How much efficient DSA could be? How much adaptive DSA could be?  Accessibility control to the open spectrum  Applications of game theory on available frequency channels

5. SYSTEM MODEL I 1. Three system components 2. Three critical power levels 3. Semi-mobile secondary users 4. The noise level is known 5. No deterministic components 6. Unknown coding and modulation 7. Power detection 8. δ,ε,ω are known and positive (WHY?) 9. Outage req. for primary users:

6. SYSTEM MODEL II Collaborative spectrum sensing benefits Send measurements to the fusion centre The fusion centre decides and broadcasts Two schemes are studied ─ Centralized ─ Decentralized Decentralized scheme is more challenging ─ less capacity and power requirement ─ cooperation between fusion and sensors for system wise optimization

7. PROPOSED ALGORITHM I Power detection of the primary signal Output : decision threshold T 1 Power identification of the primary signal Output : decision threshold T 2 First step : The primary signal is assumed to be absent if it at most δ dB above the noise level. Second step : The transmission does not probably generate interference if the primary signal is at most ε dB above the noise level. Where T 1 and T 2 depends on?

8. PROPOSED ALGORITHM II Block diagram 1. Obtain an estimate within [T 1,T 2 ] 2. Interference estimation unknow attenuation unknown distance to the transmitter 3. Worst case interference estimation RULE Initiate transmission provided the generated interference is negligible compared to the noise level

9. POWER DETECTION The primary signal is assumed to be absent if it is at most δ dB above the noise level The distribution of the measured samples is assumed to be Gaussian: i.i.d To decide optimally we use Bayes test and Neymann-Pearson approach What is the distribution of How do we fix

10. DISTRIBUTED POWER DETECTION Centralized scheme The complete LLR is communicated The fusion adds the received LLRs and compares the result with a threshold Centralized scheme is equivalent to a single sensor system with more degrees of freedom when there is no shadowing. Decentralized scheme A single bit decision is transmitted to the fusion Unlike centralized scheme two decision thresholds have to be set : Procedure Independent users sense the spectrum, calculate LLR and send it to the fusion

11. RESULTS I DETECTION FOR SINGLE USER

12. RESULTS II DETECTION WITH SHADOWING Due to the obstacles along the propagation path the signal level is not deterministic at a particular transmitter-receiver separation We assume that the signal level is distributed log-normally All the samples experience the same shadowing

13. RESULTS III DISTRIBUTED DETECTION with shadowing without shadowing For single user the shadowing samples are correlated The user should consider the probability of deep fading Assume independent shadow fading among the secondary users The mean and the variance of the shadowing distribution is common for all The effect of shadowing could be averaged out Low threshold

14. CONCLUSIONS 1. A three step algorithm for DSA access was proposed based on the generated interference at the cell border 2. The first step was presented 3. The performance depends on the outage requirement, on the SNR and on the number of power samples 4. For a single user in the presence of shadowing almost no spectrum reuse 5. The performance was greatly improved by collecting measurements made by multiple independent users and jointly process them at a fusion centre 6. The performance was affected by the amount of information conveyed from the sensors to the fusion 7. Two extremes were studying providing useful performance bounds for any practical distributed detection scheme

15. FUTURE WORK 1. Sequential distributed detection. 2. Under shadow fading numerical integration was used to evaluate the distribution of the test statistic in the presence of primary signal. The log-normal distribution could be upper bounded by strair function and analytical solutions could be retrieved instead. 3. Correlated shadow fading could be considered 4. Joint optimization of the three algorithm steps