Packet Error Probability Prediction for 802.11 MAC Simulation November 2003 Packet Error Probability Prediction for 802.11 MAC Simulation John S. Sadowsky & Qinghua Li ( john.sadowsky@intel.com, qinghua.li@intel.com ) Intel John S. Sadowsky & Qinghua Li, Intel

Overview of MAC Simulator November 2003 Overview of MAC Simulator Multiple APs and STAs Collisions and Interference Channel Models Gross propagation and shadowing Space-Frequency Selective Fading PHY Model Predict Pe = packet error probability, given Space-frequency slective fading Interference Profile Will NOT do full link level simulation John S. Sadowsky & Qinghua Li, Intel

Freq. Selective Fading & Interference November 2003 Freq. Selective Fading & Interference John S. Sadowsky & Qinghua Li, Intel

Step 1: Pe Prediction from Ps November 2003 Step 1: Pe Prediction from Ps Ps = probability of a Viterbi decoder error within the duration of a single OFDM symbol Ps is independent of packet length Eliminates one dimension in the model fit. Basic Assumption OFDM symbol errors are roughly independent Why Ps? OFDM symbols define the basic periodicity of soft metric quality at the input to the Viterbi decoder multiple interference segments within packet John S. Sadowsky & Qinghua Li, Intel

November 2003 One OFDM Symbol John S. Sadowsky & Qinghua Li, Intel

November 2003 Pe Prediction from Ps Validation of Pe Prediction using 40 MHz SISO Simulations with Model D channel and 1000 byte packets. MCS Symbol Length (bits) N = Num. Avg. Rel. Error RMS R = ½ BPSK 48 167 11.5% 16.4% R = 1/2 16 QAM 192 41.8 4.3% 5.7% R = ¾ 72 111 16.8% 28.8% 288 27.9 9.2% 15.2% QPSK 96 84 5.3% 7.5% R = 2/3 64 QAM 384 20.9 6.6% 8.6% 144 56 17.1% 27.4% 432 18.6 6.2% 12.7% John S. Sadowsky & Qinghua Li, Intel

Conclusions on Pe from Ps November 2003 Conclusions on Pe from Ps Pe Estimate is biased high See average relative error Pessimistic estimates are good Symbol Length in Viterbi trellis stages Should be larger than ~100 stages R = ¾ needs longer symbols Low rates  use “multi-symbols” to get length Primary source of error is Ps prediction Not Ps  Pe John S. Sadowsky & Qinghua Li, Intel

Step 2: Ps Prediction Available Inputs November 2003 Step 2: Ps Prediction Available Inputs Space-frequency selective channel realization Interference profile SNR does NOT predict Ps (or Pe) very well SC (subcarrier) average SNR per channel realization does NOT work either Solution: Compressor Function Convert SC SNRs to Pb = raw bit error probability Used in GSM/GPRS & WCDMA community SC average Pb is a better Ps predictor John S. Sadowsky & Qinghua Li, Intel

Ps Prediction Next 2 slides – how well does it work? November 2003 John S. Sadowsky & Qinghua Li, Intel

November 2003 Each point is one channel realization. Simulations were run until 500 packet errors occurred, per point. John S. Sadowsky & Qinghua Li, Intel

Simple Predictor Same Data as previous slide. November 2003 Simple Predictor Same Data as previous slide. Each point is one channel realization. Simulations were run until 500 packet errors occurred, per point. John S. Sadowsky & Qinghua Li, Intel

Average Pb (raw bit error probability) November 2003 Average Pb (raw bit error probability) Provide an adequate predictor of Ps Clear linear trend on log-log scale Accuracy is best at larger Ps values This is important because we need accuracte prediction of Pe only for Pe > 1%. Pe below 1% is effectively zero in a MAC simulator. For example, we don’t care if the true value was 0.01% if we predicted 0.1% - both are effectively zero. John S. Sadowsky & Qinghua Li, Intel