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Comments on PHY Abstraction

Comments on PHY Abstraction. John S. Sadowsky ( john.sadowsky@intel.com ) Intel. References on PER Prediction. Sadowsky & Li, 11-03-0863, Packet Error Probability Prediction for 802.11 MAC Simulation Sadowsky, 11-04-0304, PER Prediction for 802.11n MAC Simulation

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Comments on PHY Abstraction

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  1. Comments on PHY Abstraction John S. Sadowsky ( john.sadowsky@intel.com ) Intel John S. Sadowsky, Intel

  2. References on PER Prediction • Sadowsky & Li, 11-03-0863, Packet Error Probability Prediction for 802.11 MAC Simulation • Sadowsky, 11-04-0304, PER Prediction for 802.11n MAC Simulation • Key reference for claims made here • Ketchum, et. al., 11-04-0174, PHY Abstraction for System Simulation • Ketchum, et. al, 11-04-0269, PHY Abstraction based on PER Prediction John S. Sadowsky, Intel

  3. The Methodologies • Black Box • TGn channel models  channel state • LUT( channel state)  Rate • LUT from ensemble average PHY simulation • Ensemble average over channel realizations • Ensemble average over link adaptation • PER Prediction • TGn channel models • Space-frequency post detection SNRs • Point of abstraction = Viterbi decoder • Parametric PER prediction John S. Sadowsky, Intel

  4. Best Known Methods - GSM • Frequency hopping, temporal fading and multi-burst interleavingvariable quality soft metrics to the Viterbi decoder • ITU fading channels and LUT PER prediction • Point of abstraction = FEC decoder • References • Olofsson, et. al., “Improved interface between link level and system level simulations applied to GSM, ICUPC ’97. • Hamalain, et. al., “A novel interface between link and system level simulations,” • Mogensen & Wigard, “A simple mapping from C/I to FER and BER for GSM type air-interface,” PIMRC ’96. • Malkamaki, et. al., “A method for combining radio link simulations and system simulations for a slow frequency hopped cellular system,” ’94. • Many 3GPP GERAN technical contributions John S. Sadowsky, Intel

  5. Fighting Jensen Ensemble average LUT Eg.: g(x) = rate adaptation where x = channel states How do you characterize the “Jensen’s error” in the black box method? John S. Sadowsky, Intel

  6. Impairments • Black Box • Full TGn impairments included in PHY simulations  LUT • PER Prediction • Prediction model is validated against PHY simulations with full TGn impairments • Key impairments is captured in post detection SNR calculation • Channel estimation error John S. Sadowsky, Intel

  7. Complexity • Black Box • LUT for each channel model • LUT extrapolation for multiple packet lengths • Interference scenarios ??? • PER Prediction • Common prediction formula for all channel modelsSee 11-04-0304 • Packet length scales fluidly John S. Sadowsky, Intel

  8. Summary John S. Sadowsky, Intel

  9. Summary John S. Sadowsky, Intel

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