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]
AgendaAgenda
Project overviewModulation AlternativesBit-interleaved Coded Modulation (BICM)
Contract OverviewContract Overview
3 year projectStart Date April 2007Summer salary –RitceyOne PDRA IICurrently Mr. Chantri Polprasert (PhD Candidate in Electrical Engineering)
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.
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%
DisseminationDissemination
Conference and journal publicationsStudent project and thesesONR reports and presentationsSoftware and data analysis
Project PlansProject Plans
Channel Modeling Modulation and AdaptationCoded Modulation using BICMAlgorithm Validation
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
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)
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)
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
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
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
CP OFDMCP OFDM
CP OFDM Transmission block diagram
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
ZP OFDMZP OFDM
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
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
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
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
OFDM & SCOFDM & SC--FDEFDE
OFDM
SC-FDE
◦ Increased computational complexity at the receiver
CP SCCP SC--FDEFDE
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
ZP SCZP SC--FDEFDE
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
Recent Tasks
Software development in MATLABPerformance Comparison – uncodedKnown channels
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
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
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
Coded Modulation
Bit Interleaved Coded Modulation (BICM)Block DiagramLabeling IssuesAnalytical Performance EvaluationNumerical Results with Iterative Decoding
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Application to UWA
Coherent Signaling – Channel EstimationIterative channel estimation decodingIntegration with OFDM and SC-FDE Application to UWA realistic channels
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
