Motivation: Create improved physical layer models for the ns-3 SpectrumWifiPhy framework: Frequency selective fading channels MIMO channels Interference between technologies Approach: Use a commercial link simulator and perform link-to-system mapping to ns-3 Results: 1) A table-based OFDM error model validated against IEEE 802.11 TGn AWGN results 2) Initial link-to-system mapping results for TGn fading channel models D and E 3) A reproducible, extensible methodology

1. Link-to-System Mapping for
ns-3 Wi-Fi OFDM Error
Models
Rohan Patidar, Sumit Roy, Thomas R.
Henderson, Amrutha Chandramohan
Workshop on ns-3, June 2017

2. Presentation Overview
> Motivation: Create improved physical layer models
for the ns-3 SpectrumWifiPhy framework:
– Frequency selective fading channels
– MIMO channels
– Interference between technologies
> Approach: Use a commercial link simulator and
perform link-to-system mapping to ns-3
> Results:
1) A table-based OFDM error model validated against IEEE
802.11 TGn AWGN results
2) Initial link-to-system mapping results for TGn fading
channel models D and E
3) A reproducible, extensible methodology

3. Current ns-3 Wi-Fi Phy Abstraction
YansWifiChannel
YansWifiPhy
MacLow
YansWifiPhy
MacLow
upper layers
upper layers
Propagation Loss and
Delay models
YansWifiPhy
MacLow
upper layers
Interference
Helper ErrorModel
After exposing the Packet object to
loss and delay, Packet objects are
copied to every other Phy attached
to the Wifi Channel, with a receive power
Error model objects
probabilistically drop
packets based on the
SINR of the received
packets
Wi-Fi node
Wi-Fi node Wi-Fi node
Packet objects are
copied to the Wifi
Channel object, and
associated with a
transmit power
The Phy layer uses an
Interference Helper object to
track and aggregate
interference signals
Path loss + shadowing + fading

4. Current ns-3 Wi-Fi Phy Abstraction (cont.)
> Interference Helper
> AWGN error models
– YANS
– NIST
– New (YANS & NIST)[1]
[1] C. Hepner, A. Witt, and R. Muenzner. SINCOM 2015

5. Issues
> Wi-Fi Phy research is typically conducted with
symbol-level "link simulators" for higher fidelity
– e.g. MATLAB WLAN System Toolbox
– divergence between AWGN and fading channels is
significant
PER vs SNR for AWGN and Frequency selective channel model -E [2]
[2] . Perahia and R. Stacey. 2013. Next Generation Wireless LANs: 802.11n and 802.11 ac.
Cambridge University Press.

6. SpectrumWifiPhy opportunity
> The recently introduced ns-3 SpectrumWifiPhy can
decompose Wi-Fi signals into subcarrier
representations
> How to handle this on the receive side?
– Integration of a link simulator with ns-3 is possible, but
runs too slowly to be practical for most network
scenarios[3]
312.5 KHz subcarriers 312.5 KHz subcarriers
[3] Jens Mittag, et al. Proceedings of the IEEE 99.7 (2011)

7. Approach
> Link-to-system mapping based on MATLAB WLAN
System Toolbox
> Follows the approach chosen by ns-3 LTE authors[4]
> Recommended by IEEE TGax
[4] Mezzavilla, Marco, et al. "A lightweight and accurate link abstraction model for the simulation
of LTE networks in ns-3." ACM, 2012.

8. First steps: AWGN validation
> MATLAB WLAN System Toolbox was set up for
OFDM 5 GHz 802.11n configuration, with AWGN
channel, and validated against IEEE 802.11 TGn
data for MCS 0-7
Validation of Matlab WLAN Toolbox simulations for MCS 0 to 7
against TGN[5] results
[5] S. A. Mujtaba. 2005. TGnSync Proposal PHY Results. IEEE P802.11 Wireless LANs(2005).

9. OfdmTableErrorModel
> For each MCS, step through SNR range in 0.2 dB
increments
> Send enough packets to meet confidence interval
goals
> Simulations performed in accordance with CC-59:
– Ideal channel, perfect estimation, perfect synchronization,
known noise variance, no phase noise, etc.
> Table loaded at initialization, and users can replace
default tables with their own
Sample table data, 802.11n,
MCS 0, 1458 byte packets
First column is SNR (dB),
second is PER
# MCS 0
-4.00000 1.00000
-3.80000 1.00000
...
-0.80000 1.00000
-0.60000 0.99751
-0.40000 0.98284
-0.20000 0.93473
0.00000 0.77713
0.20000 0.61598
0.40000 0.39391
0.60000 0.23602
0.80000 0.12170

10. OfdmTableErrorModel (cont.)
> Actual SNRs will not align with 0.2 dB resolution of
table
– Solution: Interpolate
> Link simulations not exhaustively run for each
packet size
– Solution: Use extrapolation approach proposed by TGax
– Two reference packet sizes (1458 bytes, and 32 bytes)

11. Comparison with YANS and NIST error models
> YANS is closest fit to TGn models (and our
OfdmTableErrorModel)

12. Frequency-selective channels
> For each MCS, we need two tables to handle a
scalar SNR for AWGN channels
> Frequency-selective channels present a vector of
subcarrier SNRs to the receiver
– generating tables for all channel realizations is not
feasible
> We seek to distill offline link simulations for
channels of interest into simpler table
representations in ns-3
– This practice is called ‘link-to-system mapping’

13. EESM approach
> Link-to-system mapping is an empirical mapping
of detailed link simulations to an abstracted
representation used in a system simulator
> Several approaches have been defined
– RBIR
– MIESM (used by LTE)
– EESM: A Union-Chernoff bound on error probabilities to
define an "effective SNR"
subcarrier SNRs
empirically determined constant

14. EESM workflow
> For each channel model of interest, conduct a number of link
simulations for each MCS
> Use an iterative optimization method to find a Beta value for
each MCS
> Compile a per-channel model of MCS and beta values

15. Sample results
> SISO simulations for TGn indoor channel model D
> Comparison between actual PERs due to the link
simulations (discrete points) and predicted values
based on EESM (solid lines)

16. Additional details
> PER estimation workflow
> One β values can be used for different packet sizes (same
MCS)
EESM
Channel Type
Bandwidth
β
Table
Subcarrier Power Vector
β Effective
Power
PER vs
SNR
(AWGN)
MCS Index
Packet Size
PER

17. ns-3 implementation issues
> New frequency-selective fading models must be
developed for SpectrumWifiPhy usage
– MATLAB code for generating channel realizations is not
publicly releasable
> Configuration of fading model (in the channel
object) and EESM table to load (in the
SpectrumWifiPhy) must be coordinated
> Need policies for gracefully handling
configurations that fall out of scope of tables (e.g.
table for 20 MHz channel width exists but 40 MHz
does not)
> Generating tables is laborious due to link
simulation runtimes

18. Related work
> Error Models
– Analysis of ns-3 physical layer abstraction [1]
– Investigation and Improvements to the OFDM Wi-Fi
Physical Layer Abstraction in ns-3 [6]
> Link to System mapping
– RBIR based PHY layer abstraction for 802.11ac/ax [8]
– MI based link abstraction for LTE network[4]
[1] C. Hepner, A. Witt, and R. Muenzner. SINCOM 2015
[4] [4] Mezzavilla, Marco, et al. "A lightweight and accurate link abstraction model for the simulation
of LTE networks in ns-3." ACM, 2012
[6] Hossein Safavi-Naeini, et.al. Proceedings of the Workshop on ns-3. ACM, 2016.
[8] Hoefel, et al. "On Application of PHY Layer Abstraction Techniques for System Level Simulation and
Adaptive Modulation in IEEE 802.11 ac/ax Systems.“ (2016).

19. Reproducing and extending the results
> Extendable
– Replaceable PER vs SNR data file (AWGN) in given format.
– Determine Beta values for different channel realizations
(also must provide propagation loss model providing the
realization)
> Reproducible (using MATLAB WLAN System
Toolbox)
– Scripts for WLAN toolbox available[7] for AWGN
simulation.
– Script for optimal EESM parameter estimation and
performance evaluation
– Provision for generating tables for desired channel model
and channel bandwidth.
[7] https://bitbucket.org/rohanpatidar/wlan

20. Future work and issues
> Many more link simulations must be conducted to
fill in channels of interest (SISO)
> MIMO presents another issue (correlation of the
channels seen by antenna elements)
> Interference modeling (YANS ‘chunking’ model)
> Cross-technology models (LTE or Bluetooth into
Wi-Fi)
> Additional physical layer events (e.g. frame capture
model) can be simulated

21. Backup

22. ns-3 implementation (including future
directions)
SpectrumChannel
SpectrumWifiPhy
MacLow
LteEnbPhy
LteEnbMac
upper layers
upper layers
PropagationLoss
Fading Channel Coefficients
SpectrumWifiPhy
MacLow
upper layers
SignalTracker ErrorModel
Signal represented by
a power spectral density
on a Spectrum Model
Provision for complete signal
representation (for Link-Sim
support)
All signals not filtered
by channel are handed
over to the signal
tracker, also with
channel coefficients
SignalTracker replaces
InterferenceHelper. Depending on
desired abstraction , it can store non-
aggregated or aggregated signals
New error models
This interface passes enough signal
information to allow for high-fidelity link
simulators to reconstruct symbol-level
signals, or to implement different levels
of averaging/aggregation of signal content
ErrorModel interface is
also rich enough to
allow users to
implement different
modeling strategies
new component
new component
LTE node
Wi-Fi node Wi-Fi node
Can be replaced by link
layer simulator
Frame synchronization and
capture effect modelled

23. Backup

24. Backup

25. Backup

26. References
1. C. Hepner, A. Witt, and R. Muenzner. In Depth Analysis of the ns-3 Physical
Layer Abstraction for WLAN Systems and Evaluation of its Influences on
Network Simulation Results. SINCOM 2015
2. E. Perahia and R. Stacey. 2013. Next Generation Wireless LANs: 802.11n and
802.11ac. Cambridge University Press.
3. Mittag, Jens, et al. "Enabling accurate cross-layer PHY/MAC/NET simulation
studies of vehicular communication networks." Proceedings of the IEEE 99.7
(2011): 1311-1326.
4. Mezzavilla, Marco, et al. "A lightweight and accurate link abstraction model
for the simulation of LTE networks in ns-3." Proceedings of the 15th ACM
international conference on Modeling, analysis and simulation of wireless
and mobile systems. ACM, 2012.
5. S. A. Mujtaba. TGnSync Proposal PHY Results. Technical Report IEEE 802.11-
04/891r5, Agere Systems, July 2005.
6. Safavi-Naeini, Hossein-Ali, Farah Nadeem, and Sumit Roy. "Investigation and
Improvements to the OFDM Wi-Fi Physical Layer Abstraction in ns-3."
Proceedings of the Workshop on ns-3. ACM, 2016.
7. https://bitbucket.org/rohanpatidar/wlan