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Opportunistic Spectrum Access in Cognitive Radio Networks

Opportunistic Spectrum Access in Cognitive Radio Networks. Project Team: Z. Ding and X. Liu (co-PIs) S. Huang and E. Jung (GSR) University of California, Davis. (Well known) Motivations for Cognitive Radio Networks . Spectrum scarcity. More wireless services.

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Opportunistic Spectrum Access in Cognitive Radio Networks

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  1. Opportunistic Spectrum Access in Cognitive Radio Networks Project Team: Z. Ding and X. Liu (co-PIs) S. Huang and E. Jung (GSR) University of California, Davis

  2. (Well known) Motivations for Cognitive Radio Networks • Spectrum scarcity. • More wireless services. • Inefficient static spectrum allocation. • Existence of a large amount of under-utilized spectrum. • Advantage of flexible and cognitive spectrum access scheme needed: cognitive radio.

  3. Opportunistic Spectrum Access • Design Objectives: • Non-intrusiveness • Spectral efficiency • Cost efficiency • Decentralized

  4. Three basic access schemes PU -- primary user (licensee of the channel) SU -- secondary user (cognitive ratio)

  5. Problem Formulation • Assumptions: • Exponentially distributed idle period • General primary busy period distribution • Perfect sensing • Knowledge of average idle time/busy time • Constraint Metrics: • Bounded collision probability • Bounded overlapping time • Optimization problem:

  6. Fundamental limits of opportunistic spectrum access • Primary channel with exponentially distributed idle period • Bounded collision probability constraints • Maximum achievable throughput of a secondary user  --- collision probability bound  --- percentage of idle time (by primary users)

  7. Comparison of VX and VAC

  8. Comparison of VX and KS

  9. Observations • VX, VAC and KS schemes have indistinguishable throughput performance, under collision probability constraint; • The smaller the packet length, the larger the throughput. • The result can be extended to systems with multiple primary users and multiple secondary users (treat all secondary users as a “super” secondary user)

  10. Fixed length packet wins • Under the collision probability constraint, the secondary user achieves the maximum throughput when it transmits fixed length packets

  11. Overhead Consideration • Optimal packet length achieves trade-off between overhead and collision probability

  12. Relation between two constraint metrics

  13. Multi-band multiple secondary systems • No synchronization between secondary users and primary users • No control channel for secondary users • Collision probability constraint • Perfect sensing

  14. Two sensing strategies

  15. Simulation result for Multi-band competitive systems

  16. Smart Antenna Technique Applied in Cognitive Radio Networks • Design Objective: • Maximize the QoS of SUs while protecting PUs • Design MAC Protocols to take advantages of smart antenna technologies • System Setup: • One primary Tx (PT), one primary Rx (PR) • One cognitive Tx (CT) , one cognitive Rx (CR) • PT and CT transmit simultaneously to PR and CR, respectively • Performance metric: • talk-able zone of CR

  17. System Model

  18. Optimal Beamforming Problem with Constraints • Can be solved efficiently by convex optimization method

  19. A Typical Beamforming pattern of a Secondary TX

  20. Simulation Results (1) • PT uses omni-directional antenna • PRs are evenly distributed over the area centered at PT • Interference to PR is less than 0.1 of the received signal power • Spectrum efficiency increased at least by:

  21. Simulation Results (2) • PT uses Transmit beamforming • PRs are evenly distributed over the area centered at PT • Interference to PR is less than 0.1 of the received signal power • Spectrum efficiency increased at least:

  22. Integration of MAC/PHY design in Cognitive Radio Networks • Design Objective: • Under the collision probability constraint, increase the capacity of secondary users • A cross-layer approach • Channel models • Rich scattering environment: Rayleigh fading MISO channel from CT to CR and PR • Rayleigh SISO fading channel from PT to PR and CR

  23. Received signal model • Idea: • when overlapping happens, primary user can decode its signal as long as the interference power from secondary user is very small. • Transmit beamforming helps in this scenario, since it can mitigate the interference to primary users; • Collision probability:

  24. Simulation Result

  25. Conclusions • Opportunistic spectrum access of secondary users can increase the spectrum efficiency of system • Smart antenna technique enables concurrent transmission of primary users and secondary users, and reduces interference to primary user • Integration of PHY/MAC layer can improve system’s spectrum efficiency

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