1 / 9

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

lilian
Download Presentation

Comments on PHY Abstraction

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related