Adaptive communications techniques for the underwater...
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Adaptive communications Adaptive communications techniques for the underwatertechniques for the underwater
acoustic channelacoustic channel
James A. RitceyDepartment of Electrical Engineering, Box 352500
University of Washington, Seattle, WA 98195Tel: (206) 543-4702, Fax: (206) 543-3842
Email: [email protected]
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AgendaAgenda
Project overviewModulation AlternativesBit-interleaved Coded Modulation (BICM)
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Contract OverviewContract Overview
3 year projectStart Date April 2007Summer salary –RitceyOne PDRA IICurrently Mr. Chantri Polprasert (PhD Candidate in Electrical Engineering)
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4 Tasks in SOW4 Tasks in SOW
Task 1 Underwater Acoustic Channel Modeling.Task 2 Channel Adaptation and Multichannel Combining.Task 3 Coded Modulation.Task 4 Algorithm validation.
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Schedule and Effort: Start in April 2007Schedule and Effort: Start in April 2007Year Task 1 Task 2 Task 3 Task 4
1 75% 25% 0% 0%
2 25% 25% 25% 25%
3 0% 25% 25% 25%
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DisseminationDissemination
Conference and journal publicationsStudent project and thesesONR reports and presentationsSoftware and data analysis
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Project PlansProject Plans
Channel Modeling Modulation and AdaptationCoded Modulation using BICMAlgorithm Validation
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Work to Date starting April 2007Work to Date starting April 2007Develop simulation programs of different transmission systems over multipath fading channels in Matlab:
◦ Uncoded OFDMZP-OFDMCP-OFDM
◦ Uncoded SC-FDEZP-SC-FDECP-SC-FDE
Linear equalizer (MMSE)Non-linear equalizer (DFE)
◦ Coding: BICM and BICM-ID◦ BICM-ID over SC-FDE and OFDM
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Modulation OptionsModulation Options
Modulation Types◦ Cyclic Prefix Orthogonal Frequency-Division
Multiplexing (CP-OFDM)◦ Zero Padding Orthogonal Frequency-Division
Multiplexing (ZP-OFDM)◦ Cyclic Prefix Single-Carrier Frequency
Domain Equalization (CP-SC-FDE)◦ Zero Padding Single-Carrier Frequency
Domain Equalization (ZP-SC-FDE)
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System Parameters System Parameters -- BPSKBPSK
R Bit rate (bits/s)N No. of subcarriers, blocksizeP No. of CP or ZP samplesT = (N+P)/R OFDM Symbol duration (s)Δf = R/N Subcarrier spacing (Hz)B = NΔf Total Bandwidth (Hz)
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OFDMOFDMIncluded in DAB/DVB standard in Europe and the DSL modem in the USUsed in fixed broadband wireless systemsCombats multi-path fading by transmitting orthogonal symbols in parallel using narrow-band sub-channels Two variants are considered based on the sequence inserted at the transmitter to avoid Inter-block Interference (IBI):◦ CP-OFDM◦ ZP-OFDM
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CP & ZP OFDMCP & ZP OFDMCP: A copy of the last part of the symbol prepended to the transmitted symbol
ZP: A sequence of zero symbols appended after the transmitted symbol
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OFDM VariationsOFDM VariationsCP-OFDM
CP is inserted at the beginning of each transmission block No equalizer required, butSusceptible to fading on each subcarrierPeak-to-Average Power Ratio (PAPR)
ZP-OFDMZP is appended after the transmitted symbolsEqualizer needed at the receiverOverlap-Add avoids deep fadesIncreased receiver complexity over CP-OFDM
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CP OFDMCP OFDM
CP OFDM Transmission block diagram
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CP OFDM CP OFDM
12 /
, ,0
1 0 1N
th j ik Nk n i n
in S s e k N
Nπ
−
=
= = −∑ K The OFDM symbol: ,
{ } 0, 1,[ ]n n N ns s s N DFT−= L , , : a number of points
{ }' , 1, 0, 1,[ , , ]thn N P n N n n N nn S S S S S P CP− − −= L L The block: , , : length of
{ } 0, 1,[ ] :n n L nh h h −= L , Quasi-static channel impulse response
1P L≥ − Receiver: assume that 1
, ,0
, 0 1L
k n l k l n kl
y h S n k N P−
−=
= + = + −∑ K
{ }( ) ( ), , , ,0 1, , { }m n m n m n m m n N n k NR H s V m N H DFT h V DFT n= + = − = =K ,
, , , 1k n k nz y k P N P= = + −K
1, , , , ,m n m n m n m n m ns W R W H −= ⋅ =% . Assuming perfect CSI,
{ }( ) { }N n nDTF r r: N-size DFT of
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ZP OFDMZP OFDM
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ZP OFDMZP OFDM
12 /
, ,0
1 0 1N
th j ik Nk n i n
in S s e k N
Nπ
−
=
= = −∑ K The OFDM symbol: ,
{ }' 0, 1, 1[ , ,0 , ,0 ]thn n N n Pn S S S P ZP−= L L The block: , : length of
{ } 0, 1,[ ] :n n L nh h h −= L , Quasi-static channel impulse response
P L≥ Receiver: assume that 1
, ,0
, 0 1L
k n l k l n kl
y h S n k N P−
−=
= + = + −∑ K
, ,,
,
, 0 1, 1
k n k N nk n
k n
y y k Pz
y k P N++ = −⎧
= ⎨ = −⎩
K
K
{ } 0, 1,[ ]n n N ns s s N DFT−= L , , : a number of points
1, , , , ,m n m n m n m n m ns W R W H −= ⋅ =% . Assuming perfect CSI,
{ }( ) ( ), , , ,0 1, , { }m n m n m n k m n N n k NR H s V m N H DFT h V DFT n= + = − = =K ,
{ }( ) { }N n nDTF r r: N-size DFT of
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SCSC--FDEFDESingle Carrier alternative to OFDM1,2
Similar performance to OFDM with same computational complexity2 variants
ZP-SC-FDECP-SC-FDE
Frequency Domain Equalizer◦ Linear: Zero-forcing (ZF), Minimum Mean Square Error(MMSE)◦ Non-Linear: Decision feedback (DFE)◦ Frequency domain feedforward filter◦ Frequency or Time domain feedback filter2,3
1-IEEE Std 802.16TM-20042-Falconer et al., 20023-Falconer 2002
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SCSC-- Frequency Domain EqualizersFrequency Domain Equalizers
MMSEGiven information block size M, ZP-SC-FDE outperforms CP-SC-FDE4
DFEZP-SC-FDE eliminates ‘cyclic intersymbol interference’ and outperforms CP-SC-FDE5
4-Ohno 20065- Chung and Hwang 2005
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OFDM & SCOFDM & SC--FDE ComparisonFDE ComparisonModulation Pros Cons
OFDM Combats ISI using parallel narrowband transmission.
•Flat fading; channel coding is required
•High PAPR
•Susceptible to frequency offset (ICI)
SC-FDE •Yields multi-path diversity gain for uncoded transmission
•Low PAPR
•Resistance to frequency offset
•High computational complexity when calculating DFE coefficients
•PAPR: Peak-to-average power ratio
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OFDM & SCOFDM & SC--FDEFDE
OFDM
SC-FDE
◦ Increased computational complexity at the receiver
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CP SCCP SC--FDEFDE
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CP SCCP SC--FDEFDE{ } 0, 1,[ ]n n N ns s s −= L , , N is the information blocksize
{ }' , 1, 0, 1,[ , , ]thn N P n N n n N nn s s s s s P CP− − −= L L The block: , , : length of
{ } 0, 1,[ ] :n n L nh h h −= L , Quasi-static channel impulse response
1P L≥ − Receiver: assume that 1
, ,0
, 0 1L
m n l m l n kl
y h s n m N P−
−=
= + = + −∑ K
{ }{ } { } { }, , , , ,; , { } , { }k n k n k n k k n N n k N k k n N nR H S V H DFT h V DFT n S DFT s= + = = = 1
, , ,0
1 2exp( ), 0 1N
m n k n k nk
s W R j mk m NN N
π−
=
= ⋅ = −∑% K
, , , 1m n m nz y m P N P= = + −K
, , 0 1:k nW k N= −K Feedforward filter coefficients
{ }{ } { }N n nDTF r r: N-size DFT of
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ZP SCZP SC--FDEFDE
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ZP SCZP SC--FDEFDE{ } 0, 1,[ ]n n N ns s s −= L , , N is the information blocksize
{ }' 0, 1, 1, ,[ , 0 0 ]thn n N n n P nn s s s P ZP−= L L The block: , , : length of
{ } 0, 1,[ ] :n n L nh h h −= L , Quasi-static channel impulse response
1P L≥ − Receiver: assume that 1
, ,0
, 0 1L
m n l m l n kl
y h s n m N P−
−=
= + = + −∑ K
{ }{ } { } { }, , , , ,; , { } , { }k n k n k n k k n N n k N k k n N nR H S V H DFT h V DFT n S DFT s= + = = = 1
, , ,0
1 2exp( ), 0 1N
m n k n k nk
c W R j mk m N PN N
π−
=
= ⋅ = + −∑ K
, , , 0 1m n m ns c m N= = −% K
, , 0 1:k nW k N= −K Feedforward filter coefficients
{ }( ) { }N n nDTF r r: N-size DFT of
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Recent Tasks
Software development in MATLABPerformance Comparison – uncodedKnown channels
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Performance comparison between Performance comparison between ZPZP--SCSC--FDE and CPFDE and CP--SCSC--FDE using FDE using MMSE over 8MMSE over 8--tap Rayleigh fading*tap Rayleigh fading*
ZP-SC outperforms CP-SC at increased complexity
ZP-SC-FDE improves as the blocksize decreases
CP-SC-FDE improves as the blocksize increases
10 10.5 11 11.5 12 12.5 13 13.5 14 14.5 1510-4
10-3
10-2
EbNodB
BE
R
ZP 32ZP 64ZP 128CP 32CP 64CP 128
*Ohno 2006
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UncodedUncoded OFDM & ZPOFDM & ZP--SCSC--FDE FDE ComparisonComparison
10 11 12 13 14 15 16 17 18 19 2010-7
10-6
10-5
10-4
10-3
10-2
10-1
EbNo(dB)
BE
R
OFDMLE-MMSEDFE 10 tapsDFE 20 tapsDFE 30 taps
Performance comparison between OFDM & SC-DFE over 30-tap exponential decay with 1024-point FFT using QPSK modulation
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Impact of imperfect feedback taps in Impact of imperfect feedback taps in DFEDFE
Performance comparison between SC-FDE-DFE over 4-taps fixed channel with 256-point FFT using QPSK modulation
4 6 8 10 12 14 16 1810-6
10-5
10-4
10-3
10-2
10-1
100
EbNo(dB)
BE
R
Correct symbols FBDecision-directed FB
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Coded Modulation
Bit Interleaved Coded Modulation (BICM)Block DiagramLabeling IssuesAnalytical Performance EvaluationNumerical Results with Iterative Decoding
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BICM and BICMBICM and BICM--ID ReviewID ReviewBit-interleaved coded modulation (BICM)◦ Large diversity order through bit-wise interleaving◦ First introduced by Zevahi, 1992◦ Thorough anaBICM with iterative decoding (BICM-ID)◦ Constellation labeling design◦ 8-PSK: Li and Ritcey, 1997◦ 16-QAM: Chindapol and Ritcey, 1999◦ Imperfect CSI over Rayleigh fading: Huang and Ritcey
2003◦ Space Time Block Codes: Huang and Ritcey 2005
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BICMBICM--ID Block DiagramID Block Diagram
• ∏: bit-wise interleaver• ∏-1: bit-wise deinterleaver• Labeling map μ• 2m-ary constellation χ
•• Log-likelihood bit metric λ•••
Encoder
Channel
Decoder
Modulator
Demodulator
S/P
S/P
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ErrorError--Free Feedback Bound (EFF Free Feedback Bound (EFF bound)bound)
Motivation◦ Fast numerical evaluation◦ Accurate BER floor calculation
BICM union bound
dmin : the minimum Hamming distance of the convolutional encoderWI(d): the total input weight of error events at df(d,μ,χ): the pair wise error probability (PEP)kc/nc : the code rate
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EFF BoundEFF BoundPEP:
the Laplace transform of the p.d.f. of the metric differenceThe metric difference◦ Conditional Gaussian random variable with meanand variance
:the constellation point having the same binary bits as those of x except the ith bit position
: the subset of χ whose label has binary value b at the ithbit position
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Simulation parametersSimulation parametersConvolutional encoder◦ Rate: ½, 1/3, 2/3, ◦ Memory: 2, 3
Modulation: 8-PSK, 16-QAMInformation blocksize: 5000Simulate 107 information bitsMapping◦ 8-PSK: Gray, Set partitioning (SP), Semi-SP (SSP)◦ 16-QAM: Gray, Msp
Channel: AWGN, RayleighPerfect CSI at the receiverNo. of iteration: 8
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Tightness of the EFF boundTightness of the EFF bound
Performance of 16QAM BICM-ID with MSP labeling over Rayleigh fading. A four-state rate 1/2 convolutional encoder.
3 4 5 6 7 8 9 1010-7
10-6
10-5
10-4
10-3
10-2
10-1
100
Pass 1
Pass 8
EbNo(dB)
BE
R
SimulationEFF bound
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Modified Set Partitioning (MSP) Labeling Modified Set Partitioning (MSP) Labeling scheme for 16QAMscheme for 16QAM
a) Decision region of each bit before iterative decoding*
b) Decision region of each bit after iterative decoding**Chindapol and Ritcey, 1999
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Impact of labeling Impact of labeling --RayleighRayleigh
Performance of 16QAM BICM-ID with Gray and MSP labeling over Rayleigh using a rate-1/2 four-state convolutional encoder
3 4 5 6 7 8 9 1010-6
10-5
10-4
10-3
10-2
10-1
100
Pass 1
Pass 8
Pass 1
Pass 8
EbNo(dB)
BE
R
Pass1 GrayPass8 GrayPass1 MSPPass8 MSP
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Impact of labeling Impact of labeling -- AWGNAWGN
Performance of 16QAM BICM-ID with Gray and MSP labeling over AWGN using a rate-1/2 eight-state convolutional encoder
3 3.5 4 4.5 5 5.510-4
10-3
10-2
10-1
100
Pass 1
Pass 8
Pass 1
Pass 8
EbNo(dB)
BE
R
Gray MappingMSP Mapping
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8PSK and 16QAM 8PSK and 16QAM -- RayleighRayleigh
Performance comparison of 8-PSK and 16-QAM BICM-ID over Rayleigh fading channels.
4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 910-7
10-6
10-5
10-4
10-3
10-2
10-1
100
Pass 1
Pass 8
Pass 1
Pass 8
EbNo(dB)
BE
R
8PSK16QAMEff bound
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8PSK and 16QAM 8PSK and 16QAM -- AWGNAWGN
Performance comparison of 8-PSK and 16-QAM BICM-ID over AWGN channels.
3 3.5 4 4.5 5 5.510-6
10-5
10-4
10-3
10-2
10-1
100
Pass 1
Pass 6
Pass 1
Pass 8
EbNo(dB)
BE
R
8PSK16QAM
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Impact of code memoryImpact of code memory
Impact of code memory on the performance of 16-QAM BICM-ID with MSP labeling and a rate ½ convolutional code over Rayleigh fading channels
4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 910-7
10-6
10-5
10-4
10-3
10-2
10-1
100
Pass 1
Pass 84-state8-stateEff bound
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Impact of code rateImpact of code rate
Impact of code rate on the performance of 8-PSK BICM-ID with SSP labeling and a rate ½ convolutional code over Rayleigh fading channel
2 3 4 5 6 7 8 9 1010-10
10-8
10-6
10-4
10-2
100
EbNo(dB)
BE
R
Pass 1
Pass 8
Pass 1
Pass 8
Rate2/3Rate1/3Eff bound
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Impact of information block sizeImpact of information block size
Impact of information blocksize on the performance of 16-QAM BICM-ID with MSP labeling and a rate ½ convolutional code over Rayleigh fading channel
3 4 5 6 7 8 9 1010-7
10-6
10-5
10-4
10-3
10-2
10-1
100
EbNo(dB)
BE
R
50010005000Eff bound
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Application to UWA
Coherent Signaling – Channel EstimationIterative channel estimation decodingIntegration with OFDM and SC-FDE Application to UWA realistic channels
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Upcoming WorkUpcoming WorkBICM/BICM-ID over OFDM/SC-FDE◦ Perfect CSI
Use iterative decoding to combat multi-path fadingImpact of labeling, code rate over the BER performanceIts performance over different types of equalizer e.g. DFE, MMSEAdaptive modulation and equalization
◦ Imperfect CSIUse iterative decoding to combat imperfect estimate of the fading
◦ Array Combining◦ Joint estimation and decoding