an adaptive protocol for distributed beamforming - simulations … · 2011-10-04 · case studies...

大学共同利用機関法人情報・システム研究機構

国立情報学研究所National Institute of Informatics

Information Systems Architecture Science Research Division

An adaptive protocol for distributed beamformingSimulations and experiments

Stephan Sigg, Michael Beigl

KIVS 2011, 10.03.2011, Kiel

Introduction Distributed beamformig schemes Protocol Environmental impacts Conclusion

Outline

Introduction

Distributed beamformig schemes

A protocol for distributed adaptive beamforming

Environmental impacts

Conclusion

Stephan Sigg | An adaptive protocol for distributed beamforming | 2大学共同利用機関法人情報・システム研究機構




Introduction

Distributed adaptive transmit beamformingDistributed nodes synchronise the carrier frequency and phase offset oftransmit signalsLow power and processing devicesNon-synchronised local oscillators





Outline

Introduction




Conclusion





Introduction

Distributed synchronisation schemes

Closed loop carrier synchronisation1

Receiver

Transmitter

Receiver

Transmitter

Receiver

Transmitter

Source

Source

Source

Source

Source

common master beacon

to all source nodes

Receive node broadcasts

Receiver

Transmitter

Receive nodes bounce the

beacon back on distinct

CDMA channels

phase offset of each node on these

CDMA channels

Receiver transmits the relative Synchronised nodes transmit

as a distributed beamformer

to the receiver

1Y. Tu and G. Pottie, Coherent Cooperative Transmission from Multiple Adjacent Antennas to a Distant Stationary

Antenna Through AWGN Channels, Proceedings of the IEEE VTC, 2002





Introduction


Cosed loop feedback based carrier synchronisation2

Receiver

Transmitter

Receiver

Transmitter

Source

Source

Source

Source

Source

Receiver

Transmitter

alter the phase and frequency

Receive nodes randomly

of their carrier signal

Receive nodes transmit

simultaneously as a

distributed beamformer

Remote node estimates the

synchronisation quality of the

received superimposed sum signal

Remote node broadcasts the

synchronisation performance as

feedback to the network

Receiver

Transmitter

2R. Mudumbai, J. Hespanha, U. Madhow, G. Barriac, Distributed transmit beamforming using feedback control, IEEE

Transactions on Information Theory 56(1), volume 56, January 2010





Outline

Introduction




Conclusion






Pmut,i Probability to alter the phase-offset of device i(Pmut,i ∈ [0, 1])

Pdist,i Probability distribution for the random process of device i(Pdist,i ∈ {normal, uniform, . . . })

Pvar ,i Variance for the random phase alteration process of devicei (Pvar ,i ∈ [0, π])






1. One device broadcasts a data sequence sd to devices in its proximity.

2. Devices decide whether to participate in the transmission.

Decision parameters: energy, min. # of participating devices, cpu load

3. Closed-loop iterative feedback-based carrier synchronisation isachieved. Devices utilise Pmut,i , Pdist,i , Pvar ,i .

4. Upon sufficient synchronisation the receiver broadcasts ack.

5. Devices collaboratively transmit sd .

6. Optimisation parameters Pmut,i , Pdist,i and Pvar ,i are adaptedaccording to the performance achieved in the current environmentalsetting.






0 0.5 1 1.5 2 2.5 3−2

0

2x 10

−10

Time [ms]

Modulated transmit signal for device 1

0 0.5 1 1.5 2 2.5 30

0.5

1

Time [ms]

Transmitted bit sequence

0 0.5 1 1.5 2 2.5 3−2

0

2x 10

−10

Time [ms]

Modulated transmit signal for device n

0 0.5 1 1.5 2 2.5 3−2

0

2x 10

−9

Time [ms]

Received superimposed sum signal

0 0.5 1 1.5 2 2.5 3−5

0

5x 10

−9

Time [ms]

Demodulated received sum signal

Shift in the phase offset of transmit signals






0 0.5 1 1.5 2 2.5 3−1

0

1x 10

−11

Time [ms]

Modulated transmit signal for device 10 0.5 1 1.5 2 2.5 3

0.5

1

Time [ms]


0 0.5 1 1.5 2 2.5 3−1

0

1x 10

−11

Time [ms]


0 0.5 1 1.5 2 2.5 3−5

0

5x 10

−10

Time [ms]


0 0.5 1 1.5 2 2.5 3−5

0

5x 10

−10

Time [ms]







0 0.5 1 1.5 2 2.5 3−2

0

2x 10

−10

Time [ms]

Modulated transmit signal for device 10 0.5 1 1.5 2 2.5 3

0

0.5

1

Time [ms]


0 0.5 1 1.5 2 2.5 3−2

0

2x 10

−10

Time [ms]


0 0.5 1 1.5 2 2.5 3−2

0

2x 10

−9

Time [ms]


0 0.5 1 1.5 2 2.5 3−2

0

2x 10

−9

Time [ms]






Outline

Introduction




Conclusion






Beamforming of received signal components based on receiverfeedback

The feedback is impacted by environmental situations

Distance between transmitter and receiverNetwork sizeMobility






Distance100meters, mutation probability 0.1






Network size






MobilityReceiver moving at 5m/sec following a random walk model






Receiver

Distance: 5.5m

(11 m, 16,4m

)

Transmitter 3

Transmitter 2

Transmitter 1

72 cm44 cm





Outline

Introduction




Conclusion






0 1000 2000 3000 4000 5000 60001

2

3

4

5

6

7x 10

−9 Median fitness values ( Network size: 100 nodes )

Iteration count

RM

SE

Phase alteration probability: 0.5

Phase alteration probability: 0.875





Conclusion

We investigated a protocol for feedback based distributed adaptivebeamforming

The protocol is environment adaptive and thus enables emergentand organic behaviour.

It was shown that the synchronisation performance can be improvedalready with straightforward learning methods

Further work

Study more advanced learning methodsDevelop a sensor node able to alter phase and frequency offsetCase studies in sensor network instrumentations




Questions?

Stephan [email protected]





Introduction

Receiv

er

feed

back

Cosed loop feedback based carriersynchronisation

Algorithm always converges to the optimum a

Expected optimisation time O(n) when ineach iteration the optimum Probabilitydistribution is chosen a

Optimisation time can be improved by factor2 when erroneous decisions are not discardedbut inverted b

Phase and frequency synchronisation feasiblec

aR. Mudumbai, J. Hespanha, U. Madhow, G. Barriac, Distributed transmit

beamforming using feedback control, IEEE Transactions on Information Theory56(1), volume 56, January 2010

bJ. Bucklew, W. Sethares, Convergence of a class of decentralised beamforming

algorithms, IEEE Transactions on Signal Processing 56(6), volume 56, 2008cM. Seo, M. Rodwell, U. Madhow, A Feedback-Based Distributed phased array

technique and its application to 60-GHz wireless sensor network, IEEE MTT-SInternational Microwave Symposium Digest, 2008





Introduction

Receiv

er

feed

back

We derived thatExpected optimisation time of synchronisationalgorithm E [TP ] = Θ (n · k · log(n)) a

Uniform distributed phase offsetMutation probability: 1

n

Asymptotically optimum optimisationapproach b

E [TP ] = Θ (n)

aS.Sigg, R.Masri, M.Beigl, Feedback based closed-loop carrier synchronisation:

A sharp asymptotic bound, an asymptotically optimal approach, simulations andexperiments, IEEE Transactions on Mobile Computing (TMC), 2011

bR.Masri, S.Sigg, M.Beigl, An asymptotically optimal approach to the

distributed adaptive transmit beamforming in wireless sensor networks, Proceedingsof the 16th European Wireless Conference, 2010






Experimental settingSeparation of transmit antennas [m] 0.44Distance to receive antenna [m] 5.5 / 11 / 16.4Transmit frequency [MHz] fTX = 2400Receive frequency [MHz] fRX = 902Iterations per experiment 400Mobility stationaryIdentical experiments 12Transmit devices 3Receive devices 1

Algorithmic configurationRandom distribution of the phase alteration normal distributionPhase alteration probability 0.33 / 0.66 / 1.00Variance for normal distributed phase offset [π] 0.25 / 1

HardwareGain of receive antenna [dBi] GRX = 3Gain of transmit antenna [dBi] GTX = 3





Introduction


Open loop carrier synchronisation3

frequency and local oscillators in

a closed−loop synchronisation

Transmit nodes synchronise their The receiver broadcasts a sinusoidal

signal for open−loop synchronisation

to the transmit nodes

The synchronised nodes transmit

as a distributed beamformer to the

receiver

Receiver

Transmitter

Maste

r

Source

Source

Source

Source

Receiver

Transmitter

Receiver

Transmitter

3R. Mudumbai, G. Barriac and U. Madhow, On the feasibility of distributed beamforming in wireless networks, IEEE

Transactions on Wireless Communications, Vol 6, May 2007






7 0.90625

1.151049 e−09

8 0.85938

1.182819 e−09

9 0.89062

1.209551 e−09

6 5 0.9375

4 0.875

3 0.752 0.25

1 0.5

1.438299 e−09 1.198927 e−09

1.191585 e−09

0.8375

1.139293 e−09

1.155027 e−09

1.230101 e−09

RMSE

Nr prob




an adaptive protocol for distributed beamforming - simulations … · 2011-10-04 · case studies...

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