1. User Interference Effect on Routing of Cognitive Radio Ad-Hoc Networks
Tauqeer Safdar
Lecturer
IT-Networking
Higher College of Technology (HCT)

2. Presentation Outline Introduction Problem Formulation
Cognitive radio systems
Applications
Challenges
References

3. Introduction 1

4. Why cognitive radio?
Current status: the frequency bands are statically assigned to specific wireless operators/services
Problems: The static frequency allocation policy results in a low utilization of the licensed frequency spectrum. For example, in most of the time only 6% of the frequency spectrum is active [FCC/American Foundation Broadband Forum, June 2003].
Current spectrum policy needs to be re-explored

5. Cognitive Radio Ad-Hoc Network (CRAHN)
Fixed Spectrum Assignment policy spectrum white spaces
Inefficient spectrum utilization
Cognitive radio ad-hoc network (CRAHN):
A new paradigm that provides the capability to share or use the spectrum through Dynamic Spectrum Access (DSA).

6. Dynamic Spectrum Access
The concept of dynamic spectrum access (DSA) has been proposed by the Federal Communication Committee (FCC) as a solution to the potential spectrum scarcity and spectrum underutilizations problems
Basic principle: secondary users can “borrow” spectrum from primary users, but always respect primary users’ priority rights
Secondary Users
Zzzzzz
Secondary (unlicensed) users temporarily utilize frequency bands when these frequency bands are not occupied by the primary (licensed) users while simultaneously respecting the priority rights of the primary users
Ideally, primary users do not perceive the existence of secondary users
Primary Users
Hey, don’t waist the spectrum

7. Problem Formulation 3

8. Routing Effected in CRAHN Due to User Interference

9. Problem Statement
To provide the user interference-aware routing so that the end-to-end delay and packet collision can be minimized and Average Data Rate is improved under Dynamic Spectrum Access & Spectrum Mobility environment of CRAHN.

10. Proposed Solution & Methodology4

11. Network-Layered Architecture of CRAHN

12. Proposed Solution
Analyze the impact of user interference on QoS in CRAHN routing.
Implementation of channel selection through the learning and decision mechanism on Network layer for route calculation during routing.
The channel information is accessed through learning agent from MAC layer using the spectrum mobility manager.
Minimize the end-to-end delay and user interference in terms of packet collision.
Simulate the result using the CRCN based on NS-2 simulator.

13. Methodology

14. Methodology Routing table Decision block Learning Block
the channel information such as, transmission rate, modulation, channel switching delay etc.
Decision block
path information and QoS performance
QoS evaluation block influences the decision block by measuring.
how close the current performance of the routing algorithm fares with the requirements specified by the application layer.
Learning Block
tunes the working of the routing layer over time
helps the decision block to make progressively better channel and path switching decisions.

15. Implementation of Learning Agent through Learning Block

16. Findings & Calculations5

17. Simulations
CRCN simulator is a software based network simulator for network-level simulations. [20]
Based on open-source NS-2. [21]

18. Findings
Impact of transmission rate on packet delivery ratio

19. Impact of transmission rate on average end-to-end delay

20. End-to-End Delay.

21. Applications, Obstacles & Future Work6

22. Cognitive Radio and Military Networks
How is the military planning on using cognitive radio?

23. Drivers in Commercial and Military Networks
Many of the same commercial applications also apply to military networks
Opportunistic spectrum utilization
Improved link reliability
Automated interoperability
Cheaper radios
Collaborative networks
Military has much greater need for advanced networking techniques
MANETs and infrastructure-less networks
Disruption tolerant
Dynamic distribution of services
Energy constrained devices
Goal is to intelligently adapt device, link, and network parameters to help achieve mission objectives

24. Typical Cognitive Radio Applications
What does cognitive radio enable?
 Cognitive Radio Technologies, 2007

25. Requires a cross layer design
Challenges
Interference avoidance
QoS awareness
Seamless communication
Requires a cross layer design

26. Conclusion
The overall end-to-end delay has been minimized for CRAHN routing.
Interference-Aware routing for the efficient transmission in CRAHN is proposed in a cross layer fashion of network architectural stack.
Reinforcement learning is implemented on network layer for proper interference handling by secondary users.