1. Cognitive Radio Networks
Mo Dong

2. Presentation Outline Introduction Definition
Cognitive radio network architecture
Dynamic Spectrum Access in CRN

3. Introduction 1

4. Why cognitive radio? Pros: Effectively controls interferenc
Simple to design hardware
Cons:
Utilization of 0.5% in the 3-4 GHz
And 0.3% in 4-5 GHz
Multiple allocation over all of the band
A crisis of spectrum availability

5. A new approach to spectrum licensing is needed
Spectrum hole
A new approach to spectrum licensing is needed

6. Definition 2

7. Cognitive radio : “cognitive Radio” was first introduced by J.Mitola :
An intelligent wireless communication system that is aware of its surrounding environment (i.e., outside world), and uses the methodology of understanding-by-building to learn from the environment and adapt its internal states to statistical variations in the incoming RF stimuli by making corresponding changes in certain operating parameters (e.g., transmit-power, carrierfrequency, and modulation strategy) in real-time, with two primary objectives in mind:
· highly reliable communications whenever and wherever needed;
· efficient utilization of the radio spectrum.

8. Cognitive radio : FCC definition :
A ‘‘Cognitive Radio’’ is a radio that
can change its transmitter parameters
(So must be Reconfigurable)
based on
interaction with the environment in which it operates.
(So must have some capabilities such as sensing)

9. Cognitive radio network architecture3

10. Components of CRN Primary network Secondary network Primary users:
Primary users have the license to operate in certain spectrum bands
Primary base station:
Controls the access of primary users to spectrum
Secondary network
Secondary users:
Secondary users have no licensed bands assigned to them.
Secondary base-station:
A fixed infrastructure component with cognitive radio capabilities and provides single hop connection to secondary users.
Spectrum broker :
Scheduling server shares the spectrum resources between different cognitive radio networks.

11. Network access types
CR Network Access: CRs can access their own base station on both licensed and unlicensed spectrum bands
CR Ad Hoc Access: CRs can communicate with other CRs through an ad hoc connection on both licensed and unlicensed spectrum bands.
Primary Network Access : CRs can access primary base station through the licensed bands.

12. Dynamic Spectrum Access in CR4

13. Dynamic Spectrum Access
HOW TO REALIZE CR
Capacity
Mobility
Connectivity
Dynamic Spectrum Access

14. Dynamic Spectrum Access
Opportunistic Access Model
Collaborative Access Model
SU is like a smart mice. They sniff around and if there is no PU, they will seize the day
SU and PU agree on the use of spectrum and they can temporarily forget that they are naturally mutual exclusive and achieve a win-win state.

15. Dynamic Spectrum Access
Opportunistic Access Model
sensing
access
evict

16. Dynamic Spectrum Access
Collaborative Access Model
Contact with DCN
Choose the channel wanted
Reach Agreement on a common behalf
Use it until time expire or PU change its mind

17. Dynamic Spectrum Access
Collaborative Opportunistic
Pros：
Efficiency，
Easy for infrastructure
Hard in theory
Cons:
Need across layer design to be realized
Pros：
Quick，
adaptive，
Hard in theory
Cons:
Cannot make money
Hard to implement

18. Dynamic Spectrum Access
Collaborative Opportunistic
Pros：
Efficiency，
Easy for infrastructure
Hard in theory
Cons:
Need across layer design to be realized
Pros：
Quick，
adaptive，
Hard in theory
Cons:
Cannot make money
Hard to implement
Channel
Mobility

19. Dynamic Spectrum Access
Game Model
Auction Model
Contract Model
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20. Game Models
The behavior of the cognitive radios in dynamic spectrum access networks can be modeled as a dynamic spectrum sharing game (DSSG).

21. Game Models Non-cooperative DSSG without centralized control
The focus is on distributed design and cooperation simulation.
Cooperative DSSG
users do enforceable spectrum sharing through centralized authorities. Nash bargaining Solution plays an important role in cooperative games.
Negotiated or leasing-based dynamic spectrum sharing
This scenario can be modeled as multiplayer non- cooperative game with incomplete information. Auction theory is applied to formulate and analyze the interactions.

22. Auction Model Auction-Based Spectrum Sharing Game
VCG is usually used to achieve socially optimal solution
It may not be suitable for spectrum sharing because of the temperature-constraint, information overhead and computational burden.
Two other auctions are generally used:
SINR Auction: charging secondary users according to their received signal-to-interference-plus-noise ratio.
Power Auction: charging secondary users based on their received power

23. My Work
Opportunistic Spectrum Access to 3G Wireless CDMA Networks for Cognitive Radio
Double Auction for Spectrum Resource Allocation using Coalitional Game Approach
Recently ⋯⋯

24. References
[1] I. Akyildiz, W. Lee, M. Vuran, and S. Mohanty, “NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey,” Computer Networks, vol. 50, no. 13, pp. 2127–2159, 2006.
[2] L. Hu, V. Iversen, and L. Dittmann, “Survey of PHY and LINK Layer Functions of Cognitive Radio Networks for Opportunistic Spectrum Sharing,” Communications and Networking in China, pp. 10–24, 2009.
[3] Y. Xiao and F. Hu, Cognitive radio networks. Auerbach Publications, 2008.
[4] I. Akyildiz, W. Lee, M. Vuran, and S. Mohanty, “A survey on spectrum management in cognitive radio networks,” IEEECommunications Magazine, vol. 46, no. 4, pp. 40–48, 2008.
[5] Y. Yi, J. Zhang, Q. Zhang, T. Jiang, and J. Zhang, “Cooperative Communication- Aware Spectrum Leasing in Cognitive Radio Networks,” in 2010 IEEE Symposium on New Frontiers in Dynamic Spectrum, 2010, pp. 1–11.
[6] Z. Ji and K. Liu, “Cognitive radios for dynamic spectrum access-dynamic spectrum sharing: A game theoretical overview,” IEEE Communications Magazine, vol. 45, no. 5, pp. 88–94, 2007.
[7] L. Chen, S. Iellamo, M. Coupechoux, P. Godlewski, P. da Vinci, and I. Milan, “An Auction Framework for Spectrum Allocation with Interference Constraint in Cognitive Radio Networks.”