Underwater Acoustic OFDM: Past, Present, and Future Shengli Zhou - - PowerPoint PPT Presentation

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Underwater Acoustic OFDM: Past, Present, and Future Shengli Zhou - - PowerPoint PPT Presentation

Underwater Acoustic OFDM: Past, Present, and Future Shengli Zhou Dept. of Electrical and Computer Engineering University of Connecticut http://uwsn.engr.uconn.edu WUWNET11 Dec. 2, 2011 Shengli Zhou (University of Connecticut) Plenary


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SLIDE 1

Underwater Acoustic OFDM: Past, Present, and Future

Shengli Zhou

  • Dept. of Electrical and Computer Engineering

University of Connecticut http://uwsn.engr.uconn.edu

WUWNET’11

  • Dec. 2, 2011

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 2

Underwater Communications

Cable Acoustic communications (ACOMM) Electromagnetic communications (Wireless Fibre Systems) Optical communications (Blue-Green Laser)

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 3

ACOMM Techniques

Frequency shift keying (FSK)

◮ e.g., Teledyne Benthos, WHOI Micro-modem

Direct sequence spread spectrum (DSSS)

◮ e.g., LinkQuest, DSPCOMM, Tritech

Single carrier phase-shift-keying (PSK) transmissions

◮ e.g., WHOI Micro-modem, Benthos (additional processing card)

Multicarrier modulation (in the form of OFDM)

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 4

OFDM: A Prevalent Choice for Broadband Wireless Systems

DSL Modem WiFi (IEEE 802.11) WiMax (IEEE 802.16) 3GPP-LTE 4G and beyond

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 5

Number of Publications on OFDM

1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2 4 6 8 10 12 14 Year Number of Publications OCEANS Conference Papers IEEE/JASA Journal Papers

1994 - 2005: sporadic effort and little progress 2006 - 2011: sustained effort and great progress

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 6

Outline

OFDM basics: Pros and Cons Algorithm development Prototype development

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 7

Underwater Acoustic Channel Characteristics

The sound propagates too slow!

◮ Long multipath ◮ Fast variation

The SPACE’08 experiment, Martha’s Vineyard, depth 15 m

2 4 6 8 10 12 20 40 60 80 100 delay [ms] amplitude

Fast-varying multipath channel with a large delay spread

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 8

Block Transmission over LTI Channels

Consider a linear time invariant (LTI) multipath channel h(t) =

Np

  • p=1

Apδ(τ − τp) Time domain waveform distortion; intersymbol interference (ISI) arises; complex channel equalizer needed y(t) = s(t) ∗ h(t) Frequency domain Y (f) = H(f)S(f) If s(t) is carefully constructed with no ISI in frequency domain S(f)|f=fm = s[m] Then no ISI at the receiver side Y (f)|f=fm = H(fm)s[m]

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 9

Basics of Orthogonal Frequency Division Multiplexing

Frequency domain; fm − fk = (m − k) 1

T

S(f) =

  • k

s[k]sinc

  • (f − fk)T
  • ,

S(f)|f=fm = s[m]

−5 −4 −3 −2 −1 1 2 3 4 5 −0.2 0.2 0.4 0.6 0.8 1 1.2

Frequency Frequency Fesponse s[k] s[k+1] s[k−1]

Time domain waveform; g(t): rectangular pulse shaper s(t) =

  • k

s[k]ej2πfktg(t), fk = fc + k T

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 10

Pros and Cons of OFDM

Pros:

◮ Convert a dispersive channel to a set of parallel simple channels

  • zm = H(fm)s[m] + nm

K/2−1

m=−K/2

◮ Receiver complexity does not depend on the channel delay spread! Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 11

Pros and Cons of OFDM

Pros:

◮ Convert a dispersive channel to a set of parallel simple channels

  • zm = H(fm)s[m] + nm

K/2−1

m=−K/2

◮ Receiver complexity does not depend on the channel delay spread!

Cons:

◮ Poor performance on faded subchannels. ◮ Sensitive to the Doppler effect ⋆ Doppler shifts destroy the subcarrier orthogonality, and hence leads

to intercarrier interference (ICI)

◮ Large peak-to-average power ratio (PAPR) Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 12

How to Drastically Enhance Performance in Fading Channels?

5 10 15 20 25 10

−6

10

−5

10

−4

10

−3

10

−2

10

−1

10 SNR(dB) average BER fading AWGN

(a) BER vs SNR

−5 5 10 15 20 25 1 2 3 4 5 6 7 8 9 SNR(dB) Capacity fading AWGN

(b) Capacity vs SNR Fading channel drastically affects the uncoded performance Fading channel has the potential for reliable data transmission Solution: coded OFDM with strong codes, e.g., Turbo, LDPC codes that are capacity-achieving

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 13

How to Deal With the Doppler Effect?

ICI is inevitable! Need signal processing algorithms to address ICI explicitly

Signal processing tailored to underwater channels OFDM demodulation

One example: Progressive receiver [JSTSP’2011] There are other alternative approaches

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 14

Progressive Receiver

Adapt the receiver to channel conditions automatically without any a priori information Achieves both low complexity and robust performance over time-varying UWA channels

H0 H1 H2 H3

z

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . = +

n s

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 15

Receiver Structure

No

success or D = Dmax

Yes

Output decisions Nonbinary LDPC decoding ICI equalization Noise variance estimation Channel estimation Increase D; provide soft information Pre-processing; set D = 0

z = HDs + n

  • 1. The system model keeps

being updated Increase the span of ICI in equalization model Increase the maximum possible Doppler spread in channel estimation

  • 2. Soft information from the

channel decoder is utilized

  • 3. No extra pilot-overhead

needed

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 16

Block Success Percentage: SPACE08

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1 2 3 4 5 6 7 8 D = 3 D = 2 D = 1 D = 0 Success percentage vs. number of phones

S1 (60 m)

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1 2 3 4 5 6 7 8 D = 3 D = 2 D = 1 D = 0 Success percentage vs. number of phones

S5 (1000 m) Averaged over Julian dates 295-302 With 4 phones: 90% (D = 0), 95% (D = 1), and up to 98.8% (D = 3)

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 17

How to Alleviate the PAPR Impact?

6 8 10 12 14 16 10

−3

10

−2

10

−1

10 Thresh [dB] Pr(PAPR>Thresh) QPSK 8−QAM 16−QAM Multicarrier without PAPR control

Multicarrier with PAPR control

Single−Carrier

QPSK: The gap between OFDM and single-carrier is about 6dB QAMs: The gap between OFDM and single-carrier is about 4dB Design considerations on power amplifier and transducer:

◮ Peak or average power constrained? Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 18

Summary

OFDM is an elegant scheme It has a clear advantage for short-range long dispersive multipath channels. It is an appealing technique for shallow-water high-data-rate acoustic applications

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 19

WUWNet’07 Demo, Sept. 2007

Link A to B Link B to A

Single-input single-output (SISO) OFDM in-air demonstration The data rate is 3.1 kb/s, with QPSK modulation, rate 1/2 LDPC coding, and bandwidth of 5.5 kHz

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 20

WUWNet’08 Demo, Sept. 2008

Multi-input multi-output (2 × 2) OFDM in-air demonstration The data rate is 6.2 kb/s, with QPSK modulation, rate 1/2 LDPC coding, and bandwidth of 5.5 kHz

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 21

WUWNet’09 and ’10 Demo, Nov. 2009 & Nov. 2010

Aqua-fModem Prototype: With keyboard input and LCD display Floating-point TMS320C6713 DSP board; running @ 225 MHz Fixed-point TMS320C6416 DSP board; running @ 1 GHz

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 22

WUWNET’11 Demo: A Network of Modems

One-hop network, RTS/CTS based MAC protocol

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 23

Current / Future Issues (1)

Multi-input multi-output (MIMO)

◮ Co-located: Increase the data rate via spatial modulation

x1 x2 x Nt . . . y1 y2 y Nr . . . h11 h12 hNtNr

◮ Distributed MIMO, asynchronous MIMO

User 1 User 2 Recivers User 3 v1 v3 = 0 v2

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 24

Current / Future Issues (2)

Interference (Sonar, impulse interference, multiuser interference)

0.5 1 1.5 2 2.5 x 10

6

−600 −400 −200 200 400 600 Timedomain_for_637_phone_10

◮ Interference mitigation / avoidance / alignment / management Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 25

Current / Future Issues (3)

Networking issues

◮ MAC ◮ Routing ◮ Reliable data transfer ◮ Applications

How to efficiently interact with higher layers? Joint optimization (cross-layer design)?

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 26

Thank you!

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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SLIDE 27

Environmental Impact: S1

295 296 297 298 299 300 301 302 303 1 2 3 4 Julian Date in 2008 Wave height (m) 295 296 297 298 299 300 301 302 303 5 10 15 20 Julian Date in 2008 Wind speed (m/s)

295 296 297 298 299 300 301 302 303 1 2 3 4 5 6 7 8 9

All success, Dmax = 0 All success, Dmax = 1 All success, Dmax = 2 All success, Dmax = 3 With errors, Dmax = 3

S1 (60 m) “All success”: all 20 blocks in a file correctly decoded ICI-ignorant receiver (D = 0) works well during calm days ICI-aware receiver (D > 0) is needed when the channel conditions become worse

Shengli Zhou (University of Connecticut) Plenary Talk

  • Dec. 2, 2011

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