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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

ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

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Page 1: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

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 TelematicsInstitute of Telematics – University of Karlsruhe

Page 2: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

Jens Mittag, Timo BingmannDSN 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: V ehicular A d-hoc NET works:– Protocol development, evaluation and optimization

Page 3: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

Jens Mittag, Timo BingmannDSN 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 shouldwe decide whether a packet can besuccessfully decoded?

Radio PropagationModeling

Transceiver ReceptionModeling

Page 4: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

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

4

II. Wifi Architecture of ns-3

MacHigh

Queue

DcaTxopDcfManager

StationManagerMacRxMiddle

MacLow

WifiPhy

WifiChannel

InterferenceHelper

ErrorRateModel

PropagationLossModel

MAC

PHY

WIRELESSCHANNEL

FOCUS OF THIS TALK

Page 5: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

Jens Mittag, Timo BingmannDSN 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

Page 6: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

Jens Mittag, Timo BingmannDSN 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-mTxPwr RxPwr

Page 7: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

Jens Mittag, Timo BingmannDSN 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 parametrizationis a tough job and requires a thorough understanding

of the communication system and of influencingenvironmental effects!

Page 8: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

Jens Mittag, Timo BingmannDSN 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 preamble2. 1st decision : could the header

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

be successfully decoded?

Page 9: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

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

9

IV. Additive White Gaussian Noise Channel

Page 10: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

Jens Mittag, Timo BingmannDSN 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

Page 11: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

Jens Mittag, Timo BingmannDSN 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 eachmodulation scheme (coded/uncoded)

– Combine the BERs into a Packet Error Rate (PER)

P = 1 – (1 – BER )err

ii

L i

byK

rishna Pillai(http://w

ww

.dsplog.com/)

Assumption: BitErrors are uniformlydistributed and independent!

Page 12: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

Jens Mittag, Timo BingmannDSN 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

Page 13: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

Jens Mittag, Timo BingmannDSN 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

Page 14: ns-3 and wifi - An overview of physical layer models · 2010-03-18 · ns-3 and wifi - An overview of physical layer models Jens Mittag, Timo Bingmann Workshop on ns-3 – in conjunction

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 propagationcharacteristics

– 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!