Jens MittagDSN Research Group – Institute of Telematics – University of Karlsruhe

ns-3 and wifi -An overview of physical

layer models

Jens Mittag, Timo BingmannWorkshop on ns-3 – in conjunction with SIMUTools 2009

March 2nd, 2009

Decentralized Systems and Network Services Research Groupand Junior Research Group for Traffic Telematics

Institute of Telematics – University of Karlsruhe

Jens Mittag, Timo BingmannDSN Research Group – Institute of Telematics – University of Karlsruhe

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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

Jens Mittag, Timo BingmannDSN Research Group – Institute of Telematics – University of Karlsruhe

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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 PropagationModeling

Transceiver ReceptionModeling

Jens Mittag, Timo BingmannDSN Research Group – Institute of Telematics – University of Karlsruhe

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II. Wifi Architecture of ns-3

MacHigh

Queue

DcaTxopDcfManager

StationManagerMacRxMiddle

MacLow

WifiPhy

WifiChannel

InterferenceHelper

ErrorRateModel

PropagationLossModel

MAC

PHY

WIRELESSCHANNEL

FOCUS OF THIS TALK

Jens Mittag, Timo BingmannDSN Research Group – Institute of Telematics – University of Karlsruhe

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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

Jens Mittag, Timo BingmannDSN Research Group – Institute of Telematics – University of Karlsruhe

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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-mTxPwr RxPwr

Jens Mittag, Timo BingmannDSN Research Group – Institute of Telematics – University of Karlsruhe

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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!

Jens Mittag, Timo BingmannDSN Research Group – Institute of Telematics – University of Karlsruhe

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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 preamble2. 1st decision: could the header

be successfully decoded?3. 2nd decision: could the payload

be successfully decoded?

Jens Mittag, Timo BingmannDSN Research Group – Institute of Telematics – University of Karlsruhe

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IV. Additive White Gaussian Noise Channel

Jens Mittag, Timo BingmannDSN Research Group – Institute of Telematics – University of Karlsruhe

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IV. Additive White Gaussian Noise Channel

» Reception quality of packet

– Ratio of Signal Strength to Noise & Interference

SINR = Signal

Noise + Interference

Jens Mittag, Timo BingmannDSN Research Group – Institute of Telematics – University of Karlsruhe

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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

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Assumption: BitErrors are uniformly distributed and independent!

Jens Mittag, Timo BingmannDSN Research Group – Institute of Telematics – University of Karlsruhe

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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

Jens Mittag, Timo BingmannDSN Research Group – Institute of Telematics – University of Karlsruhe

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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

Jens Mittag, Timo BingmannDSN Research Group – Institute of Telematics – University of Karlsruhe

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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 rightparametrization is difficult. A wrong configurationof the wifi might lead to invalid protocol results!