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 An adaptive protocol for distributed beamforming Simulations and experiments Stephan Sigg, Michael Beigl KIVS 2011, 10.03.2011, Kiel
Outline Introduction Distributed beamformig schemes Environmental impacts Conclusion Stephan Sigg An adaptive protocol for distributed beamforming 2
Introduction Distributed adaptive transmit beamforming Distributed nodes synchronise the carrier frequency and phase offset of transmit signals Low power and processing devices Non-synchronised local oscillators Stephan Sigg An adaptive protocol for distributed beamforming 3
Outline Introduction Distributed beamformig schemes Environmental impacts Conclusion Stephan Sigg An adaptive protocol for distributed beamforming 4
Introduction Distributed synchronisation schemes Closed loop carrier synchronisation 1 Receiver Receiver Receiver Receiver Source Transmitter Transmitter Transmitter Transmitter Source Source Source Source Receive node broadcasts common master beacon to all source nodes Receive nodes bounce the beacon back on distinct CDMA channels Receiver transmits the relative phase offset of each node on these CDMA channels Synchronised nodes transmit as a distributed beamformer to the receiver 1 Y. 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 Stephan Sigg An adaptive protocol for distributed beamforming 5
Introduction Distributed synchronisation schemes Cosed loop feedback based carrier synchronisation 2 Receiver Receiver Receiver Receiver Source Transmitter Transmitter Transmitter Transmitter Source Source Source Source Receive nodes randomly alter the phase and frequency 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 2 R. Mudumbai, J. Hespanha, U. Madhow, G. Barriac, Distributed transmit beamforming using feedback control, IEEE Transactions on Information Theory 56(1), volume 56, January 2010 Stephan Sigg An adaptive protocol for distributed beamforming 6
Outline Introduction Distributed beamformig schemes Environmental impacts Conclusion Stephan Sigg An adaptive protocol for distributed beamforming 7
P mut,i P dist,i P var,i Probability to alter the phase-offset of device i (P mut,i [0, 1]) Probability distribution for the random process of device i (P dist,i {normal, uniform,... }) Variance for the random phase alteration process of device i (P var,i [0, π]) Stephan Sigg An adaptive protocol for distributed beamforming 8
1. One device broadcasts a data sequence s d 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 is achieved. Devices utilise P mut,i, P dist,i, P var,i. 4. Upon sufficient synchronisation the receiver broadcasts ack. 5. Devices collaboratively transmit s d. 6. Optimisation parameters P mut,i, P dist,i and P var,i are adapted according to the performance achieved in the current environmental setting. Stephan Sigg An adaptive protocol for distributed beamforming 9
1 Transmitted bit sequence 0.5 0 0 0.5 1 1.5 2 2.5 3 Time [ms] 2 x 10 10 Modulated transmit signal for device 1 0 2 0 0.5 1 1.5 2 2.5 3 Shift in the phase offset Time [ms] of transmit signals 2 x 10 10 Modulated transmit signal for device n 0 2 0 0.5 1 1.5 2 2.5 3 Time [ms] 2 x 10 9 Received superimposed sum signal 0 2 0 0.5 1 1.5 2 2.5 3 Time [ms] 5 x 10 9 Demodulated received sum signal 0 5 0 0.5 1 1.5 2 2.5 3 Time [ms] Stephan Sigg An adaptive protocol for distributed beamforming 10
1 Transmitted bit sequence 0.5 0 0.5 1 1.5 2 2.5 Time [ms] 3 1 x 10 11 Modulated transmit signal for device 1 0 1 0 0.5 1 1.5 2 2.5 3 1 x 10 11 Modulated transmit signal for device n Time [ms] 0 1 0 0.5 1 1.5 2 2.5 3 Time [ms] 5 x 10 10 Received superimposed sum signal 0 5 0 0.5 1 1.5 2 2.5 3 Time [ms] 5 x 10 10 Demodulated received sum signal 0 5 0 0.5 1 1.5 2 2.5 3 Time [ms] Stephan Sigg An adaptive protocol for distributed beamforming 11
1 Transmitted bit sequence 0.5 0 0 0.5 1 1.5 2 2.5 3 2 x Time [ms] 10 10 Modulated transmit signal for device 1 0 2 0 0.5 1 1.5 2 2.5 3 2 x 10 10 Modulated transmit signal for device n Time [ms] 0 2 0 0.5 1 1.5 2 2.5 3 Time [ms] 2 x 10 9 Received superimposed sum signal 0 2 0 0.5 1 1.5 2 2.5 3 Time [ms] 2 x 10 9 Demodulated received sum signal 0 2 0 0.5 1 1.5 2 2.5 3 Time [ms] Stephan Sigg An adaptive protocol for distributed beamforming 12
Stephan Sigg An adaptive protocol for distributed beamforming 13
Outline Introduction Distributed beamformig schemes Environmental impacts Conclusion Stephan Sigg An adaptive protocol for distributed beamforming 14
Beamforming of received signal components based on receiver feedback The feedback is impacted by environmental situations Distance between transmitter and receiver Network size Mobility Stephan Sigg An adaptive protocol for distributed beamforming 15
Beamforming of received signal components based on receiver feedback The feedback is impacted by environmental situations Distance between transmitter and receiver Network size Mobility Stephan Sigg An adaptive protocol for distributed beamforming 16
Distance 100meters, mutation probability 0.1 Stephan Sigg An adaptive protocol for distributed beamforming 17
Distance 150meters, mutation probability 0.1 Stephan Sigg An adaptive protocol for distributed beamforming 18
Distance 200meters, mutation probability 0.1 Stephan Sigg An adaptive protocol for distributed beamforming 19
Distance 300meters, mutation probability 0.2 Stephan Sigg An adaptive protocol for distributed beamforming 20
Distance 300meters, mutation probability 0.6 Stephan Sigg An adaptive protocol for distributed beamforming 21
Beamforming of received signal components based on receiver feedback The feedback is impacted by environmental situations Distance between transmitter and receiver Network size Mobility Stephan Sigg An adaptive protocol for distributed beamforming 22
Network size Stephan Sigg An adaptive protocol for distributed beamforming 23
Beamforming of received signal components based on receiver feedback The feedback is impacted by environmental situations Distance between transmitter and receiver Network size Mobility Stephan Sigg An adaptive protocol for distributed beamforming 24
Mobility Receiver moving at 5m/sec following a random walk model Stephan Sigg An adaptive protocol for distributed beamforming 25
Introduction Distributed beamformig schemes Protocol Environmental impacts Conclusion 44 cm 72 cm Transmitter 1 Transmitter 2 Distance: 5.5m (11 m, 16,4m) Transmitter 3 Receiver 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 Stephan Sigg An adaptive protocol for distributed beamforming 26
Stephan Sigg An adaptive protocol for distributed beamforming 27
Stephan Sigg An adaptive protocol for distributed beamforming 28
Outline Introduction Distributed beamformig schemes Environmental impacts Conclusion Stephan Sigg An adaptive protocol for distributed beamforming 29
7 6 x 10 9 Median fitness values ( Network size: 100 nodes ) Phase alteration probability: 0.5 Phase alteration probability: 0.875 5 RMSE 4 3 2 1 0 1000 2000 3000 4000 5000 6000 Iteration count Stephan Sigg An adaptive protocol for distributed beamforming 30
Conclusion We investigated a protocol for feedback based distributed adaptive beamforming The protocol is environment adaptive and thus enables emergent and organic behaviour. It was shown that the synchronisation performance can be improved already with straightforward learning methods Further work Study more advanced learning methods Develop a sensor node able to alter phase and frequency offset Case studies in sensor network instrumentations Stephan Sigg An adaptive protocol for distributed beamforming 31
Questions? Stephan Sigg sigg@nii.ac.jp Stephan Sigg An adaptive protocol for distributed beamforming 32
Introduction Receiver feedback Cosed loop feedback based carrier synchronisation Algorithm always converges to the optimum a Expected optimisation time O(n) when in each iteration the optimum Probability distribution is chosen a Optimisation time can be improved by factor 2 when erroneous decisions are not discarded but inverted b Phase and frequency synchronisation feasible c a R. Mudumbai, J. Hespanha, U. Madhow, G. Barriac, Distributed transmit beamforming using feedback control, IEEE Transactions on Information Theory 56(1), volume 56, January 2010 b J. Bucklew, W. Sethares, Convergence of a class of decentralised beamforming algorithms, IEEE Transactions on Signal Processing 56(6), volume 56, 2008 c M. Seo, M. Rodwell, U. Madhow, A Feedback-Based Distributed phased array technique and its application to 60-GHz wireless sensor network, IEEE MTT-S International Microwave Symposium Digest, 2008 Stephan Sigg An adaptive protocol for distributed beamforming 33
Introduction Receiver feedback We derived that Expected optimisation time of synchronisation algorithm E[T P ] = Θ (n k log(n)) a Uniform distributed phase offset 1 Mutation probability: n Asymptotically optimum optimisation approach b E[T P] = Θ (n) a S.Sigg, R.Masri, M.Beigl, Feedback based closed-loop carrier synchronisation: A sharp asymptotic bound, an asymptotically optimal approach, simulations and experiments, IEEE Transactions on Mobile Computing (TMC), 2011 b R.Masri, S.Sigg, M.Beigl, An asymptotically optimal approach to the distributed adaptive transmit beamforming in wireless sensor networks, Proceedings of the 16th European Wireless Conference, 2010 Stephan Sigg An adaptive protocol for distributed beamforming 34
Experimental setting Separation of transmit antennas [m] 0.44 Distance to receive antenna [m] 5.5 / 11 / 16.4 Transmit frequency [MHz] f TX = 2400 Receive frequency [MHz] f RX = 902 Iterations per experiment 400 Mobility stationary Identical experiments 12 Transmit devices 3 Receive devices 1 Algorithmic configuration Random distribution of the phase alteration normal distribution Phase alteration probability 0.33 / 0.66 / 1.00 Variance for normal distributed phase offset [π] 0.25 / 1 Hardware Gain of receive antenna [dbi] G RX = 3 Gain of transmit antenna [dbi] G TX = 3 Stephan Sigg An adaptive protocol for distributed beamforming 35
Stephan Sigg An adaptive protocol for distributed beamforming 36
Introduction Distributed synchronisation schemes Open loop carrier synchronisation 3 Receiver Receiver Receiver Transmitter Source Transmitter Transmitter Source Source Source Master Transmit nodes synchronise their frequency and local oscillators in a closed loop synchronisation 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 3 R. Mudumbai, G. Barriac and U. Madhow, On the feasibility of distributed beamforming in wireless networks, IEEE Transactions on Wireless Communications, Vol 6, May 2007 Stephan Sigg An adaptive protocol for distributed beamforming 37
1 0.5 1.230101 e 09 2 0.25 3 0.75 1.438299 e 09 1.198927 e 09 4 0.875 1.139293 e 09 6 0.8375 5 0.9375 1.191585 e 09 1.155027 e 09 Nr prob RMSE 8 0.85938 1.182819 e 09 9 0.89062 1.209551 e 09 7 0.90625 1.151049 e 09 Stephan Sigg An adaptive protocol for distributed beamforming 38