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Unified “Black Box” PHY Abstraction Methodology

Unified “Black Box” PHY Abstraction Methodology. Jeff Gilbert, Won-Joon Choi, Qinfang Sun, Ardavan Tehrani, Huanchun Ye Atheros Communications B.Jechoux, H.Bonneville Mitsubishi ITE Stefano Valle, Angelo Poloni STMicroelectronics. PHY Abstraction problem.

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Unified “Black Box” PHY Abstraction Methodology

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  1. Unified “Black Box” PHY Abstraction Methodology Jeff Gilbert, Won-Joon Choi, Qinfang Sun,Ardavan Tehrani, Huanchun YeAtheros Communications B.Jechoux, H.BonnevilleMitsubishi ITE Stefano Valle, Angelo PoloniSTMicroelectronics Atheros / Mitsubishi ITE / ST Micro

  2. PHY Abstraction problem • PHY / MAC Interface can drastically impact overall results: • Time varying channel creates time varying PER • Time varying channel could affect systems with feedback • This affects overall delay, jitter and throughput • Challenge • Properly model detailed PHY characteristics • Keep flexibility to adapt to various PHYs • Keep simulation effort reasonable Atheros / Mitsubishi ITE / ST Micro

  3. Channel Model PHY Model MAC / System Model Ideal PHY / MAC System Simulation DistanceModel # Channel Packet error and chan feedback info RateSelection Advantages: - Full accuracy of link-level PHY and detailed MAC / System simulation Disadvantages: - Large computational requirements for large simulations with many nodes Approximations is required to make the simulations feasible Atheros / Mitsubishi ITE / ST Micro

  4. Two Basic Approaches • Model PHY as black box using tables (more here) • Allows use of full-accuracy PHY and Channel model • PHY model used “as-is” – no formulas or approximations required • Approximations made at PHY/MAC boundary • Incorporate simplified PHY into MAC sim (Intel) • Use derived, approximate model of PHY • Incorporate directly into MAC/System simulations – interface cleaner Atheros / Mitsubishi ITE / ST Micro

  5. Features of Black Box Method • PHY simulations do not scale with the number of data rates • Good modeling of 11n channel characteristics & variations. • Accurate modeling of PHY proposals with all impairments • Includes rate adaptation as part of PHY • Easy interface to merge different PHY and MAC proposals Atheros / Mitsubishi ITE / ST Micro

  6. Table Channel Model Channel Model Black Box MAC / System Model Table Black Box PHY Overview PHY Simulation Pre-generates table for MAC simulations MAC Simulation Uses PHY simulation data for MAC simulation DistanceModel # DistanceModel # Channel Channel Data rates PHY Model PHY Performance PHY performance Concept: Abstract PHY performance vs. channel condition into table Difficulties: Reducing channel dimensionality and num data rates dependence Atheros / Mitsubishi ITE / ST Micro

  7. Using Capacity to Characterize Channels • The dimensionality of channel state must be reduced to limit table size • Otherwise for a freq-selective MIMO channel, the dimensionality would be O(nNumFreqBins*NumStreams) • As per 802.11-04/0064 (ST) Channel Capacity can be used to reduce the dimensionality while retaining fidelity • Achievable data rate vs. capacity mapping has been verified in initial tests (Atheros) Atheros / Mitsubishi ITE / ST Micro

  8. PER vs capacity (vs SNR) mapping Suppressing SNR dimension SNR Atheros / Mitsubishi ITE / ST Micro

  9. Table Channel Model Channel Model Black Box Capacity Calc. Capacity Calc. MAC / System Model Table Using Channel Capacity (CC) PHY Simulation Pre-generates table for MAC simulations MAC Simulation Uses PHY simulation data for MAC simulation DistanceModel # DistanceModel # Channel Channel Data rates PHY Model CC PHY Performance PHY performance CC Concept: Reduce dimensionality of channel by using its MIMO capacity PHY model uses actual channel to compute performance Atheros / Mitsubishi ITE / ST Micro

  10. Validation of the Methodology for SISO • Validation carried out by using: • 802.11a, Rate 54 Mbps with SISO channel D; • Continuous packet transmission; • Comparison of the results obtained with two approaches: • Pure Link-Level simulation (50,000 simulated packets) • Full channel model (500,000 simulated packets) plus PERvsCC LUTs; parameters: • Channel Capacity resolution in LUTs: 0.5 and 1 b/s/Hz; • Time resolution in Channel Capacity generation: 0.5 and 1 ms; • with and without suppressing SNR dimension; • Metrics for comparison: • PER, Average of Burst of Error Length (BEL), Standard Deviation of BEL, pdf of BEL Atheros / Mitsubishi ITE / ST Micro

  11. Accuracy on PER Further details in appendix Atheros / Mitsubishi ITE / ST Micro

  12. Extending Channel Capacity to MIMO • Different SNR and channel conditions may lead to the same capacity • Initial tests show that capacity is sufficient to represent performance (more validation is needed) • If capacity alone is not sufficient, additional measurements may be added. Options: • SNR • Condition number of the channel • Near/far: within or beyond the distance break point of 11n channel models Atheros / Mitsubishi ITE / ST Micro

  13. Table Channel Model Channel Model Black Box Capacity Calc. Capacity Calc. Randomly choose pass / fail based onper-rate statistics MAC / System Modelw/ Rate Adaptation Table Conventional LUT-based Methods PHY Simulation MAC Simulation Channel DistanceModel # DistanceModel # Channel CC Data rates Statistics of PERs per data rate andMPDU size PHY Model Statistics of PERs per data rate andMPDU size CC Pass/Fail Data rate Conventional table-based PHY simulations have difficulties simulating systems with many rates (ABL, MIMO etc) since PHY sims scale with the number of rates Atheros / Mitsubishi ITE / ST Micro

  14. Including Rate Adaptation w/ PHY • Typical table-based systems record PER statistics for each data rate • For MIMO with independent rates on each stream, the number of rate combinations is NumRatesNumTxStreams • For Adaptive Bit Loading, rate set is continuous • This is solved by including rate adaptation w/ PHY • Number of runs does not grow with number of data rates • Richness of PHY / rate adaptation interface is not limited by storing in table Atheros / Mitsubishi ITE / ST Micro

  15. Table Channel Model Channel Model Capacity Calc. Capacity Calc. MAC / System Model Table Rate Adaptive LUT-based Methods PHY Simulation MAC Simulation DistanceModel # Channel DistanceModel # Channel Black Box Feedback CC Rate Adaptation PHY Model Statistics of pairs of“data rates” / PERs RateSelection Randomly choose data rate, PE based on stats Statistics of pairs of“data rates” / PERs CC Pass/Fail Data rate Rate Adaptive table-based PHY simulations do not scale with the number ofrates and the rich PHY / Rate Adaptation feedback is present Atheros / Mitsubishi ITE / ST Micro

  16. Channel Model Channel Model Capacity Calc. Capacity Calc. MAC / System Model Table Ideal PHY emulation PHY Simulation MAC Simulation DistanceModel # Channel DistanceModel # Channel Black Box Feedback CC Rate Adaptation PHY Model RateSelection Spectral efficiency > CC? CC Statistics of pairs of“data rates” / PERs Pass/Fail Data rate Ideal PHY (i.e. the one achieving a PER equal to the Outage Capacity) can be included in the MAC simulator; Rate Adaptation can be included as well. No LUT required for this case; see also 11-04-0184-00-000 (STMicroelectronics). Atheros / Mitsubishi ITE / ST Micro

  17. Black Box PHY Method Summary • Consider PHY Model as a “black box” from MAC perspective • Critical to allow accurate modeling of all proposals’ PHY in an accurate and automated manner • Use of look-up tables giving PHY performance vs. channel conditions via channel capacity • Channel model run in system simulation to determine lookup into look-up tables • Rate adaptation modeled in the black box as well to allow rich interaction between PHY and rate adaptation Atheros / Mitsubishi ITE / ST Micro

  18. Channel Model Capacity Calc. Generating the Table Data DistanceModel # Channel Black Box Feedback Rate Adaptation PHY Model RateSelection CC PacketError? DataRate The run of the PHY model with rate adaptation over a channel sequence generates a sequence of (CC, DataRate, PacketError?) sets Atheros / Mitsubishi ITE / ST Micro

  19. Storing the Table Data Atheros / Mitsubishi ITE / ST Micro

  20. Using Table Data (w/ interp)Statistics can be used with or without interpolation. With interpolation shown below: And a random CC sequence from the channel model and CC calculation: 25, 26, 27, 28, 28, 27, 26, 26, 25 Atheros / Mitsubishi ITE / ST Micro

  21. Using Table Data (no interp)Statistics can be used with or without interpolation. W/o interpolation shown below: And a random CC sequence from the channel model and CC calculation: 25, 26, 27, 28, 28, 27, 26, 26, 25 Atheros / Mitsubishi ITE / ST Micro

  22. Many-Rate PHY Operation • PHY simulation time is independent of the number of data rates • This is why rate adaptation needed to be incorporated into PHY simulation • If many different rates are selected, the statistics on each rate may be coarsely sampled but when aggregated they will be accurate • I.e. the PER accuracy scales with the total number of packets simulated, and not the number of packets per rate as with conventional table methods Atheros / Mitsubishi ITE / ST Micro

  23. Packet Length Effects • If the total number of packet lengths used in the system simulations is small, all used packet lengths can be generated in the table. • If there are many different lengths, a few representative rates (100, 1000, 10000) can be simulated and performance at intermediate lengths can be calculated by extrapolating from the closest rate via: • PERnew = 1 - (1-PERold)(NewLen/OldLen) Atheros / Mitsubishi ITE / ST Micro

  24. PHY Simulation Details • Run detailed PHY simulations to generate performance over a range of channel capacities. Run one set per: • MPDU size • (Binned distance or SNR offset) / Model • Each set of PHY simulations shall include: • Time variation due to Doppler and fading • N=10000 packets with packet spacing of Tcoherence/100 • Rate adaptation/feedback • Output of each set of PHY simulation: • (Ri, di), 1 i  N, where Ri is the data rate of packet i and di is pass or fail. • Condense into: (Rk, rk, Pk), where k is an arbitrary data rate index, rk is the probability of using rate k, and Pk is the PER of rate k. Atheros / Mitsubishi ITE / ST Micro

  25. Simulation Requirements Atheros / Mitsubishi ITE / ST Micro

  26. Issues • Co-channel or adjacent channel interference • Reduction in capacity can be directly modelled • Per-packet impacts of packet mis-rating not included • However usage models do not include much • CSMA/CA still handled correctly in MAC simulation • Rate adaptation approximations • Collision effects incorporated in MAC correctly result in packet losses but do not affect rate adaptation • Number of simulations to generate the table Atheros / Mitsubishi ITE / ST Micro

  27. Conclusions • The “Black Box PHY” methodology allows arbitrary PHYs to be included in MAC/System simulations with little MAC sim computation • Incorporating rate adaptation into PHY simulations facilitates the use of systems with many rates (MIMO, Adaptive Bit Loading) • Channel variation is presented as in the channel model • Some approximations in PHY / MAC interface Atheros / Mitsubishi ITE / ST Micro

  28. References • 11-03/0863 Packet Error Probability Prediction 802.11 MAC Simulation (Intel) • 11-04/0064 Time Correlated Packet Errors in MAC Simulations (STm) • 11-04/0120 PHY Abstraction to be Used in MAC Simulation (Mitsubishi) • 11-04/0172 Black Box PHY Abstraction Methodology (Atheros / Mitsubishi) • 11-04/0182 Record and Playback PHY Abstraction 802.11n MAC Simulations Using Soft PER Estimates (Marvell) • 11-04/0183 Record and Playback PHY Abstraction 802.11n MAC Simulations using Binary PER Estimates (Marvell) • 11-04/0184 Proposal PHY Abstraction In MAC Simulators (STm) Atheros / Mitsubishi ITE / ST Micro

  29. Appendix Atheros / Mitsubishi ITE / ST Micro

  30. CC to PER mapping validation • 100 channel realization considered; • 1000 packets sent over each channel realization and PER estimated; • 2 SNRs considered • Relative error (see slide 3) is defined as where PERLut is the PER computed through linear interpolation of PERvsCC LUT values at the CC of interest and PERActual is the PER as estimated for the considered channel realization having the same CC. Atheros / Mitsubishi ITE / ST Micro

  31. Atheros / Mitsubishi ITE / ST Micro

  32. 30.00 25.00 20.00 15.00 20 Individual 24 Individual 10.00 Error 5.00 0.00 1 -5.00 PER 0.1 0.01 0.001 Relative error Atheros / Mitsubishi ITE / ST Micro

  33. Accuracy on Average BEL Atheros / Mitsubishi ITE / ST Micro

  34. Accuracy on Standard Deviation of BEL Atheros / Mitsubishi ITE / ST Micro

  35. Accuracy of PDF of BEL (SNR = 16 dB) Atheros / Mitsubishi ITE / ST Micro

  36. Accuracy of PDF of BEL (SNR = 20 dB) Atheros / Mitsubishi ITE / ST Micro

  37. Accuracy of PDF of BEL (SNR = 24 dB) Atheros / Mitsubishi ITE / ST Micro

  38. Accuracy of PDF of BEL (SNR = 28 dB) Atheros / Mitsubishi ITE / ST Micro

  39. Accuracy of PDF of BEL (SNR = 32 dB) Atheros / Mitsubishi ITE / ST Micro

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