Cognitive Radio Architecture Evolution

1. Cognitive Radio Architecture Evolution Karol Schober Based on paper by Joseph Mitola, III, Senior Member IEEE

2. Introduction • CR prototype introduced 1998-1999 • Exchanging of business cards (‘May, I introduce’) • Intelligence involved • Past five years - SDR & CR under research • concerning : spectrum allocation, market, bussiness and open architecture • Described is architecture for evolving heterogeneous networks • cellular merged with hot spots • wireless technologies merged with human interface technology

3. Outline • Cognitive Radio Architectures • Architecture and Use Case Evolution • Sensory Perception in the Evolving CRA • Quality of information

4. SDR architecture • GSM 900/1800 • CDMA • Bluetooth • PSTN…. Most of functionality can be synthesized in software-based chips like FPGA, Single-chip Arrays and Blade servers • speech • internet access • multimedia content AD/DA convertors are an issue Radio architecture: framework by which products maybe integrated in to evolving sequence of designs with specific rules - public/proprietary

5. Complexity of SDR To manage complexity object and layer oriented programming has been adopted CR in addition to SDR is capable of Sensing the environment and fit content to user

6. Why are resources constrained? • Regulation is due to historical reasons • Small/large bands were dedicated to public interest with respect to economic aspect • TV, 1st and 2nd generation cellular networks • Nowadays the radios are capable of multiband transmission and they are practically everywhere (ubiquity) Heterogeneity of UE allows new way to go – Dynamic Spectrum Allocation

7. Dynamic Spectrum Access • Process of increasing spectrum efficiency employing real-time adjustment of radio resources • A real-time spectrum auction between systems with different purpose, e.g. • cellular network( stolen spectrum during peak hours) • public safety (more access points for public safety) • Countries treat CR differently • TV spectrum in US, European conservativeness, EU direction for secondary training, Ireland DySPAN 100MHz • The ideal iCR is difficult to implement thus XG defined • Simplified CR, simple rule-engine that controls radios air interface to conform to spectrum used policies (policy language) according to Haykin Near-Future

8. Haykin’s DSA Key enabler for DSA Integration of cognitive nodes into the Network

9. How is iCR different? • Self-awareness, user awareness and machine learning Planing technologies • Sensory perceptions: • RF • Location • Motion • Temperature • Vision • Speech • …. To identify changes in RF scene (IMEC Belgium) CR prototype – Wake epoch

10. Epochs • Wake epoch • see previous slide • e.g. detection of new RF networks • Sleep epoch • Computationally intensive pattern analyses, self-organizing, autonomous learning • Prayer epoch • interaction with higher authorities such as cognitive networks about restrictions , advice

11. Networking and CRA evolution • Neither DSA , not iCRA provide architecture for cognitive wireless networks (CWN’s) • No real-time spectrum auction (standardization necessary) • Supportive distributed network • Policy language • Method of payment

12. Proposals – Fritzek and Katz • CWN CRA characterized by cooperation among intelligent entities • Cooperation considering : game theory, relays power allocation, diversity, cross-layer optimization, stability and security, distributed antennas, cooperative header compression, coding, distributed spatial channel control

13. Proposals- Osaka University • Biological systems –robustness to catastrophe • Molecular processes, immune system, social insects, prey-predator relations • Posses : Membership perception, network awareness, buffer management, message filtering • Strassner’s key issues with lingua franca • Placing the cognition to layers (e.g. to sense congestions)

14. Architecture and Use case evolution • Media services and Internet changed the use case for Cellular networks HOW? • Product Differentiation • present Multimedia services competition • User specific services • Protocol stack • IPv4 should be adopted even if not ideal and later drift towards IPv6 • OA&M • Network management and administration based on self-awareness • Agent-based evolved CRAs may assist to overcome misconfigurations • Location Awareness • Not a “killer app” , but e.g. Google Maps, MapQuest • will be able to move QoS to QoI

15. Continue • Spectrum Awareness • before network ordered the UE what band to listen to • now the awareness comes to play, switching between WIFI, 3G, Bluetooth • recognition of Emergency calls in D-band U.S 700Mhz • Spectrum auction • recently, cross-licensing of small parts of band • Jondral’s group: leasing of BW chunks for 5s for browsing and email for few cents would increase Spectrum utilization by 15-25% (how about revenue?) • User expectations • Users adjust their expectations and usage (low/high mobility, hotspot, 3G) • Operators move towards femtocells • Femtocells recognized by GPS(not indoors ), computer vision, speech

16. The use case for Femto-cell handover • SAS hotel in Stockholm • The call are dropped when entering • GPS cannot say whether you are inside (glass foyer) • Camera would be a solution

17. First Responder Situation awareness • the prioritizing of transmission (resource management) should be based on users situation, e.g. • specific location • surrounding (smoke) • Movement (trapped) • intent (rescue someone, escape) • Radio should be aware of user’s physical setting when getting resources

18. Commercial Sentient Spaces • Confluence of technologies (3G, Wi-Fi, ….) • Interference suppression • Cognitive load balancing • Cooperative power management • Elder/child care with speech and coputer vision • Turning off stove • Eating pills • Input of data • Moving service from administrator to user (car-rental check-in) • Near future with IPv6 -> Users of wireless become devices rather than people • The smart homes are apart of radio, but can help to autonomously adjust radio resource priorities to changing needs of users. • Radio is as well mean to fast deploy the services • Radio may be a control for large number of objects in smart-homes.

19. Sensory Perception in the Evolving CRA • the point is to identify aspect of sensory technologies for future cognitive radio • Computer vision • Surveillance (fall in parking lot) • Internet retrieval • The Video scene API should assist to CR to determine proper speed and priority (car accident) • Human Language Translation • For unburdening the user from contact with HMI • Can assist to identify user needs better (e.g. interact with medical devices)

20. Computer speech • with Windows XP does not appear to be in wide use • Precision [raw error rate] • 3-10% in home office • 25% • 14.7% topic spotting • Speaker identification • Background noise disturbing the model • Thus only soft biometric measure (contribute to overall Authorization )

21. Text Understanding • Used in Business intelligence markets (source WIKI) • refers to skills, technologies, applications and practices used to help a business acquire a better understanding of its commercial context. Business intelligence may also refer to the collected information itself. • Common functions of business intelligence technologies are reporting, OLAP, analytics, data mining, business performance management, benchmarking, text mining, and predictive analytics. • Causal relationship between unstructured customer contact reports (uCCR) • Takes a lot of labor work • mix word sense disambiguation, named entity detection, sentence structure analysis • Google depends on the laws of very large numbers • Typically there are small amount of uCCRs • Android – statistical machine learning

22. Text Understanding -continue • Query tool based on ALICE – AI better in answering than Google • Unstructured comments in wireless networks service, maintenance record • CR communities may analyze themselves, optimize and save costs • Functional description languages

23. Quality of Information QoI=Quantity*Precision*Recall*Accuracy*Detail*Timeliness*Validity • Paremeters are • Real [0..1] • Are best at 1 • Monotonic and approach 0 to degrade the QoI • Quantity • No information for given situation, quantity is 0 • Older information is better than no (maps) • This was economically stupid, in future needed (congestion of networks)

24. QoI continue • Precision and Recall • Degree to which information correspond to user’s need • Recall 1 = all relevant documents retrieved • Precision 1 = no irrelevant documents retrieved • user may provide feedback by rejecting or ignoring • Accuracy • Spelling the president name wrong • Numerical accuracy • Dependence (quadratic, linear, exponential, fractal ….) • Timeliness • User’s time when the information is to be employed • If needed now: then 1/ε is a good measure • There might be window when Timeliness fall to zero immediately (death ) • Wake up call should not be 15minutes earlier  • Detail • If sufficient detail then information provided is complete (I get the directions to Restaurant) • Promoting User as the 8th layer

25. Challenges and opportunities • Some spectrums as GPS, UWB cannot be detected other than with correlation • Some bands are occupied 0.1% time and are necessary 100% (radar bands, airport) → noway to share • Emergency channels have to be clear to have maximal SNR possible (“Mayday” must be heard) • CRA should posses knowledge of forbidden bands • Event though many paper exists on spectrum-auctions and web-page rental of spectrum exists, there is no architecture deployed for real-time auctions

26. Conclusion in the box

27. Questions? Please send to Mitola