1. Jens Mittag DSN Research Group – Institute of Telematics – University of Karlsruhe ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction with SIMUTools 2009 March 2nd, 2009 Decentralized Systems and Network Services Research Group and Junior Research Group for Traffic Telematics Institute of Telematics – University of Karlsruhe

2. Jens Mittag, Timo Bingmann DSN Research Group – Institute of Telematics – University of Karlsruhe 2 I. Background » Characteristics of VANETs: –Very high mobility of network nodes –Diverse environment – urban scenarios – rural scenarios – highway scenarios –Radio signal propagation conditions are – changing rapidly over time – different w.r.t. environmental effects –Fully distributed communication system » Our ns-2 / ns-3 experience –ns-2 PHY/MAC improvements, e.g. cumulative interference, capture capabilities or Nakagami-m distribution (2006) –Port of improvements to ns-3 finished – merge into main branch pending » Research background: Vehicular Ad-hoc NETworks: –Protocol development, evaluation and optimization

3. Jens Mittag, Timo Bingmann DSN Research Group – Institute of Telematics – University of Karlsruhe 3 I. Motivation » How should we model the quality of the wireless communication channel? » Based on which set of rules should we decide whether a packet can be successfully decoded? Radio Propagation Modeling Transceiver Reception Modeling

4. Jens Mittag, Timo Bingmann DSN Research Group – Institute of Telematics – University of Karlsruhe 4 II. Wifi Architecture of ns-3 MacHigh Queue DcaTxop DcfManager StationManager MacRxMiddle MacLow WifiPhy WifiChannel InterferenceHelper ErrorRateModel PropagationLossModel MAC PHY WIRELESS CHANNEL FOCUS OF THIS TALK

5. Jens Mittag, Timo Bingmann DSN Research Group – Institute of Telematics – University of Karlsruhe 5 III. Radio Signal Propagation » 3 different scales of signal strength variation » PathLoss: –Friis –Two-Ray Ground –LogDistance –ThreeLogDistance » Shadowing: –LogNormal Shadowing » Fast fading: –Nakagami-m –Rician Fading –Rayleigh Fading

6. Jens Mittag, Timo Bingmann DSN Research Group – Institute of Telematics – University of Karlsruhe 6 III. Radio Signal Propagation » ns-3 calculates one signal strength for each packet » Principle: chaining of several propagation loss models » 3 different scales of signal strength variation Friis Shadowing Nakagami-m TxPwr RxPwr

7. Jens Mittag, Timo Bingmann DSN Research Group – Institute of Telematics – University of Karlsruhe 7 III. Radio Signal Propagation » Issues with model usage –Currently, (most) models are applied in a probabilistic way – no correlation for receivers in a close proximity – no possible correlation of successive packet receptions – No consideration of scenario semantics – e.g. no radio obstacles such as buildings, trucks, … –No consideration of signal strength variations during packet reception – e.g. due to a time- and frequency-selective channel Choosing the right model and parametrization is a tough job and requires a thorough understanding of the communication system and of influencing environmental effects!

8. Jens Mittag, Timo Bingmann DSN Research Group – Institute of Telematics – University of Karlsruhe 8 IV. Transceiver Reception Modeling » How to model the reception behavior of a transceiver? –How to decide whether a packet can be successfully decoded? » How are interfering packets and background noise modeled? –Additive White Gaussian Noise Channel model 1.Detection of the preamble 2.1st decision: could the header be successfully decoded? 3.2nd decision: could the payload be successfully decoded?

9. Jens Mittag, Timo Bingmann DSN Research Group – Institute of Telematics – University of Karlsruhe 9 IV. Additive White Gaussian Noise Channel

10. Jens Mittag, Timo Bingmann DSN Research Group – Institute of Telematics – University of Karlsruhe 10 IV. Additive White Gaussian Noise Channel » Reception quality of packet –Ratio of Signal Strength to Noise & Interference SINR = Signal Noise + Interference

11. Jens Mittag, Timo Bingmann DSN Research Group – Institute of Telematics – University of Karlsruhe 11 V. Reception Criterion » Bit-Error Rate based decision –For each packet segment with a constant SINR compute corresponding BER –Mapping Φ: SINR → BER can be derived analytically or empirically for each modulation scheme (coded/uncoded) –Combine the BERs into a Packet Error Rate (PER) P = 1 – (1 – BER ) err i i L i by Krishna Pillai (http://www.dsplog.com/) Assumption: BitErrors are uniformly distributed and independent!

12. Jens Mittag, Timo Bingmann DSN Research Group – Institute of Telematics – University of Karlsruhe 12 V. Reception Criterion » SINR based decision –Determine the minimum experienced SINR level of a packet –Compare this SINR with a threshold –Thresholds are measured experimentally using real hardware – e.g. 5dB for BPSK with Atheros chipsets – e.g. 8dB for QPSK with Atheros chipsets

13. Jens Mittag, Timo Bingmann DSN Research Group – Institute of Telematics – University of Karlsruhe 13 V. Reception Criterions » Capture Effect –So far, synchronization to a packet is only possible when receiver is in idle state, i.e., Phy is searching for a preamble –Modern chipsets support a feature called „packet capturing“ – even if receiver is already synchronized to a packet, it is able „switch“ over to a new arriving packet – SINR of new packet has to be sufficiently high → capture threshold –Value for capture threshold is a trade-off – capture threshold too low → aggressive capture policy – capture threshold too high → conservative capture policy

14. Jens Mittag, Timo Bingmann DSN Research Group – Institute of Telematics – University of Karlsruhe 14 VI. Conclusion » We have different models to account for radio propagation characteristics –Pathloss –Shadowing –Fast Fading » We have different models to reflect transceiver technology –Additive White Gaussian Noise channel –BER-based reception criterion –SINR-based reception criterion –Capture model Again, choosing the right model and the right parametrization is difficult. A wrong configuration of the wifi might lead to invalid protocol results!