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Core-PC: A Class of Correlative Power Control Algorithms for Single Channel Mobile Ad Hoc Networks

Core-PC: A Class of Correlative Power Control Algorithms for Single Channel Mobile Ad Hoc Networks. Jun Zhang and Brahim Bensaou The Hong Kong University of Science and Technology TWC 07. Outline. Introduction Correlative Power Constraints Core-PC Performance Evaluation Conclusion.

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Core-PC: A Class of Correlative Power Control Algorithms for Single Channel Mobile Ad Hoc Networks

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  1. Core-PC: A Class of Correlative Power Control Algorithms for Single Channel Mobile Ad Hoc Networks Jun Zhang and Brahim Bensaou The Hong Kong University of Science and Technology TWC 07

  2. Outline • Introduction • Correlative Power Constraints • Core-PC • Performance Evaluation • Conclusion

  3. Introduction • The energy supply in wireless devices is limited by their battery capacity. • From measurements in real systems, • Packet processing only consumes a small fraction • The energy is consumed by the • transmission • reception • listening to the channels

  4. Introduction • It is important to design power control algorithms that • Improving network throughput • Reducing energy consumption

  5. Goal • To design power controlled MAC protocols • Throughput better than IEEE 802.11 • Energy consumption smaller than IEEE 802.11

  6. Introduction • All previous works on power control only consider the assignment of the transmission power of each frame separately.

  7. Introduction • The authors derive a set of equations that correlate the transmission powers of RTS, CTS, DATA and ACK frames. • The authors derive a class of adaptive power control algorithms (Core-PC).

  8. Correlative Power Constraints -- Basic Framework and Definitions • The transmission zone • The received power level of a frame from node i in its transmission zone is higher than or equal to κ. • The carrier sensing zone • The received power level of a frame from node i in its carrier sensing zone is higher than or equal to η.

  9. Path loss Correlative Power Constraints -- Noise Level Estimation • When node A is receiving the CTS reply from a node B, we assume • The channel at node A is idle. • The node’s NAV is always set and the node is silenced whenever it is in the transmission zone. • The thermal noise level is negligible. • The propagation model is the two ray ground propagation model.

  10. Correlative Power Constraints -- Noise Level Estimation • Ravg: average transmission range • Pavg:average transmission power • Δ : the density of simultaneous transmittersoutside A’s transmission zone • Δ is upper bounded by

  11. Correlative Power Constraints -- Noise Level Estimation According to the two ray ground propagation model

  12. The transmission power of CTSfrom nodeBto node A The received power of RTS from node A to node B at location B SIR threshold RTS A B CTS Correlative Power Constraints -- Requirements on Power Assignment for Frame Reception The received power of the CTS at node A must also fulfill the SIR requirement.

  13. A B Correlative Power Constraints -- Requirements on Power Assignment for Frame Reception

  14. Correlative Power Constraints -- Requirements on Power Assignment for Frame Reception • To simplify the notation,

  15. Correlative Power Constraints -- Requirements on Power Assignment for Frame Reception

  16. Correlative Power Constraints -- Feasibility of Power Assignment

  17. Correlative Power Constraints -- Feasibility of Power Assignment The minimal possible power assignment for a DATA frame in a successful 4-way handshake is

  18. Core-PC

  19. Core-PC • In Algorithm 1, different combination of (PRTS,Pavg) lead to different power assignment algorithms.

  20. Core-PC • Three alternative approaches may be adopted for setting the PRTS. • (a) Simple scenario • PRTS=Pmax • (b) Symmetric scenario • PRTS=PCTS • (c) Minimum power scenario • The RTS frame is transmitted at a power level such that the DATA transmission power is minimized.

  21. transmission power of acaptured frame Core-PC • Similarly, there are different ways of choosing the value of Pavg. • (A) Worst case scenario • Pavg=Pmax • (B) Node-related adaptive scenario • (i) initially Pavg=Pmax • (ii) all other nodes transmit their DATA frame at the same power level • (C) Network-related adaptive scenario • Pavg=0.9Pavg+0.1Pt

  22. Performance Evaluation • Simulator: NS-2 • Routes: AODV • Data rate: 11Mbps • κ: 3.652e-10 Watts • η: 1.559e-11 Watts • ζ: 10dB • Pmax: 0.2818 Watts • Rmax: 250m

  23. Performance Evaluation -- Single Hop Scenario • CBR traffic is generated and carried in UDP datagrams with a packet size of 512 bytes • Two packet sending rate: • 200 packets/s per sender • 400 packets/s per sender (I) 200m (II) 150m 50m

  24. Performance Evaluation -- Single Hop Scenario Rate = 200 PKT/SECEND 200m

  25. Performance Evaluation -- Single Hop Scenario Rate = 400 PKT/SECEND 200m

  26. Performance Evaluation -- Single Hop Scenario Rate = 400 PKT/SECEND 150m

  27. Performance Evaluation -- Multi-Hop Static Scenario • 49 nodes • 400*400 m2 area • 7 flows are set between randomly chosen end-to-end source-destination pairs • Packet size is 512 bytes

  28. Performance Evaluation -- Multi-Hop Static Scenario

  29. Performance Evaluation -- Multi-Hop Static Scenario

  30. Conclusion • The correlations among the required transmission power of RTS/CTS/DATA/ACK • derived constraints that ensure the correct delivery • Using these constraints • The authors developed a class of correlative power control algorithms • Simulations have shown the algorithm achieves • Higher throughput • Lesser energy consumption

  31. Thank you

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