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User Interference Effect on Routing of Cognitive Radio Ad-Hoc Networks

User Interference Effect on Routing of Cognitive Radio Ad-Hoc Networks. Tauqeer Safdar Lecturer IT-Networking Higher College of Technology (HCT). Presentation Outline. Introduction Problem Formulation Cognitive radio systems Applications Challenges References. Introduction. 1.

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User Interference Effect on Routing of Cognitive Radio Ad-Hoc Networks

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  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. Secondary Users Zzzzzz Zzzzzz Zzzzzz Hey, don’t waist the spectrum Primary Users 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 Ideally, primary users do not perceive the existence of secondary users

  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 & Methodology 4

  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 • 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 & Calculations 5

  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 Work 6

  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. 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.

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