1. Record and Playback PHY Abstraction for 802.11n MAC Simulations
March
Record and Playback PHY Abstraction for n MAC Simulations
Hemanth Sampath Erik Lindskog
Ravi Narasimhan Atul Salhotra
H. Sampath,E. Lindskog, R. Narasimhan, and A. Salhotra, Marvell

2. Record & Playback PHY Abstraction Scheme
March
Record & Playback PHY Abstraction Scheme
PHY Record:
Generate n channel sequence of N samples, with sampling time dT
Pass channel sequence through PHY simulator including rate adaptation [Black Box Methodology IEEE /01 72r0]
Generate a PHY record with sequence of chosen rates and corresponding PASS/FAIL decisions.
MAC Playback:
The MAC replays PHY record for each user
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

3. Simulation Diagram March 12 2004
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

4. Record & Playback Features
March
Record & Playback Features
PHY simulations do not scale with number of users
Include rate adaptation (& power control) as part of PHY [IEEE /01 72r0]. Captures the rich dynamics of rate adaptation.
Good modeling of 11n channel characteristics & variations.
Accurate modeling of PHY proposals with all impairments.
Easy interface to merge different PHY and MAC proposals !
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

5. Channel Sequence Simulations Results:
March
Channel Sequence
Simulations Results:
25 channel coherence times is sufficient to capture richness of channel.
Possible values of N and dT for ~ 25 coherence times (assuming ~ 160msec coherence time from 11n channel models at 5 GHz) N
dT (msec)
250 16
500 8
1000 4
4000 1
~ 4msec sampling with 1000 channels is sufficient for correctly predicting PHY performance with (PHY based rate adaptation.)
Smaller N desirable for smaller PHY
records
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

6. Performance Validation with N=1000 channel realizations
March
Performance Validation with N=1000 channel realizations
PHY performance accurately modeled with N=1000 & dT = 4msec
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

7. Capacity Calculation with N=1000 channels
March
Capacity Calculation with N=1000 channels
Capacity distribution accurately modeled with N=1000 & dT = 4msec
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

8. Example PHY Record (1000 byte pkt)
March
Example PHY Record (1000 byte pkt)
Avg SNR = 3 dB
Avg SNR = 27 dB
Avg SNR = 30 dB
time R1
P/F T 6
t+dT 12
t+2dT 1
t+(P1)dt R1
P/F 54 1 48 R1
P/F 72 1 54
…….
Avg SNR can vary with path-loss and shadowing. [Example: 0:3:30] dB
Records are computed for different packet sizes in usage model.
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

9. MAC Simulations t = Inter-packet spacing
March
MAC Simulations
For each user, playback sequence of recommended rates and associated packet pass or fail events
t = Inter-packet spacing
For time < dT, MAC packets are transmitted with identical rate and pass/fail decision (as specified by the PHY record)
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

10. March
Potential Issue
Interpolation: Multiple packets are sent using the same pass/fail and rate, leading to increased throughput variability
Define: Inter-packet spacing = t (< dT)
Number of packets (M) transmitted per dT time = dT / t
For dT ~ 4 msec and worse case t ~ 200 micro sec, M = 20 packets may be sent with identical rate & pass-fail decisions.
Simulations:
Worse case simulation: MAC throughput with dT = 4msec, t = 0.2 msec is not significantly affected compared to ideal MAC simulation with dT = t = 0.2 msec.
This is because dT << channel coherence time.
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

11. MAC Throughput Validation in worse-case scenario
March
MAC Throughput Validation in worse-case scenario
MAC throughput with parameters (dT = 4msec, t = 0.2 msec) is similar to ideal MAC simulation with dT = t = 0.2 msec
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

12. Potential Issue & Improvements
March
Potential Issue & Improvements
Issue: MAC based rate adaptation not possible.
Issue handled using a modified PHY record:
PHY simulates pass/fail decisions for alternative rates for each channel realization.
The PHY record will have pass/fail decisions for recommended rate and alternative rates, for each channel realization.
Algorithm for simulating alternate rates:
If recommended rate FAILS, simulate lower rates until packet passes for the current channel realization.
If recommended rate PASSES, simulate higher rates until packet fails for the current channel realization.
Sufficient information for determining pass/fail decisions for all rates
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

13. Example PHY Record with Alternate Rates
March
Example PHY Record with Alternate Rates
Avg SNR = 30 dB R1
P/F R2 R3 … 54 1 48 36 72 .. ….
Only a few rates need to be simulated around the recommended rate regardless of total number of rates. (Record size does not increase drastically!)
MAC based rate adaptation algorithms and feedback delays can be modeled
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

14. Example MAC Simulation
March
Example MAC Simulation
Example MAC adaptation:
Increase rate if more
than 2 packets
pass.
Decrease rate if more
than 2 packets fail.
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

15. Estimated Simulation Time for Generating Records
March
Estimated Simulation Time for Generating Records
In Marvell MATLAB PHY simulator:
Simulating a 1000 byte packet transmission on a 2 GHz processor takes 2.5 seconds on average.
Record with N=1000 entries and 10 Avg. SNR indices (0, 3, 6,..,30 dB) with 1 rate per time instant would take
1000 entries x 2.5 seconds/entry x 10 SNR ~= 7 hours.
Comparison: This time is similar to a typical PHY simulation that generates one PER vs SNR plot (assuming 1000 channels per SNR and 10 SNR points).
Only 1 PHY record generated per channel model & packet-size.
Simulation time not scale with the number of users
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

16. Conclusions Record-Playback methodology has several advantages:
March
Conclusions
Record-Playback methodology has several advantages:
Includes full n channel models.
Complete modeling of PHY with impairments.
Includes rate adaptation in PHY and MAC.
Easy to merge different PHY and MAC proposals!
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

17. March
References
11-03/0863 Packet Error Probability Prediction 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 n MAC Simulations Using Soft PER Estimates (Marvell)
11-04/0183r1 Record and Playback PHY Abstraction n MAC Simulations using Binary PER Estimates (Marvell)
11-04/0184 Proposal PHY Abstraction In MAC Simulators (STm)
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

18. March
Appendix
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

19. Capacity Calculation with N=1000 channels
March
Capacity Calculation with N=1000 channels
Capacity distribution accurately modeled with N=1000 & dT = 4msec
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

20. Capacity Calculation with N=1000 channels
March
Capacity Calculation with N=1000 channels
Capacity distribution accurately modeled with N=1000 & dT = 4msec
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

21. Capacity Calculation with N=1000 channels
March
Capacity Calculation with N=1000 channels
Capacity distribution accurately modeled with N=1000 & dT = 4msec
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell

22. Performance Validation with N=1000 channel realizations
March
Performance Validation with N=1000 channel realizations
PHY performance accurately modeled with N=1000 & dT = 4msec
H. Sampath, E. Lindskog, R.Narasimhan, A. Salhotra, Marvell