digital communications chapeter 3. baseband demodulation/detection signal processing lab
TRANSCRIPT
Digital CommunicationsDigital Communications
Chapeter 3. Baseband Demodulation/Detection
Signal Processing Lab
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Block Diagram of a DCS
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Demodulation and Detection Modeling the received signal
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Major Sources of Errors Inter-Symbol Interference (ISI)
Due to the filtering effect of transmitter and receiver, symbols are “smeared”.
Thermal noise (AWGN)
Disturbs the signal in an additive fashion (Additive) Has flat spectral density for all frequencies interest (White) Modeled by Gaussian random process (Gaussian Noise)
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Demodulation and Detection (cont´d) Demodulation and Sampling :
Waveform recovery and preparing the received signal for detection
Improving SNR using matched filter Reducing ISI using equalizer Sampling the recovered waveform
Detection :
Estimate the transmitted symbol based on the received sample
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Baseband and Bandpass
Bandpass model of detection process is equivalent to baseband model because:
The received bandpass waveform is first transformed to a baseband waveform.
Equivalence theorem:
Performing bandpass linear signal processing followed by heterodying the signal to the baseband yields the same results as heterodying the bandpass signal to the baseband followed by a baseband linear signal processing.
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Likelihood
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Signal Space Inner (scalar) product
Properties of inner product :
)()(
)(*)()(),(
tyandtxbetweenncorrelatiocross
dttytxtytx
)(),()(),()(),()(
)(),(*)(),(
)(),()(),(
tztytztxtztytx
tytxataytx
tytxatytax
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Signal Space (cont´d)
Norm properties :
Euclidean distance between two signals :
||)(||||||)(||
)(""
|)(|)(),(||)(|| 2
txatax
txoflength
Edttxtxtxtx x
||)()(||, tytxd yx
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Signal Space (cont´d) N-dimensional orthogonal signal space is characterized by N
linearly independent functions called basis functions.
The basis functions must satisfy the orthogonality condition
If all Ki=1, the signal space is orthonormal
Njj t 1)}({
Nji
Tt
ji
jiwhere
Kdttttt
ij
iji
T
jiji
,.......,1,
0
0
1
)()()(),(0
*
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Signal Space (cont´d) Any arbitrary finite set of waveforms where each member of the set is of duration T, can be
expressed as a linear combination of N orthonormal waveforms where N≤M
Mmm ts 1)}({
Njj t 1)}({
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Vectorial Representation
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Signals and Noise
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
White Noise in Orthonormal Signal Space AWGN n(t) can be expressed as
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Eb/No: Figure of Merit in Digital Communications SNR or S/N is the average signal power to the average noise power. SNR
should be modified in terms of bit-energy in DCS because :
Signals are transmitted within a symbol duration and hence, are energy signal (zero power)
A merit at bit-level facilitates comparison of different DCSs transmitting different number of bits per symbol.
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Bit Error Probability vs Eb/No
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Decision Theory
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
MAP and ML
)|()|( :d LikelihooMaximum
)(
)(
)|(
)|( : RatioLikelihood
)()|()()|( :Theorem Bayes'Using
)|()|( :i PosteriorA Maximum
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Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Signal Detection Example
2
02
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)(ln
)|(
)|(ln)(ln : Ratiolikelihood-Log
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Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Probability of Bit Error
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)|()|(
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Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Matched Filter Receiver Problem
Design the receiver filter h(t) such that the SNR (signal power to average noise power) is maximized at the sampling time.
Solution The optimum filter is the Matched filter, given by
which is the time-reversed and delayed version of the conjugate of the transmitted signal
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Matched Filter (cont´d)
The output SNR of a matched filter depends only on the ratio of the signal energy to the PSD of the white noise at the filter input
2max
0N
E
N
S s
T
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Correlator Receiver The matched filter output at the sampling time can be realized
as the correlator output.
)(),()()()(
)]([)()(
)()()()()(
0
0
0
tstrdsrTz
dtTsrtz
dthrtrthtz
T
t
t
opt
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Matched Filter and Correlator
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Implementation of Matched Filter Receiver
),.......,,(
,......,1)()(
21 N
jj
rrr
NjtTtrr
r
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Implementation of correlator receiver
),.......,,(
,......,1)()(
21
0
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jj
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r
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Statistics of The Vector Signals AWGN channel model : r = si + n
Signal vector si=(si1, si2, … siN) is deterministic. Elements of noise vector n=(n1, n2, …, nN) are i, i.d Gaussian random
variables with zero-mean and variance N0/2. The noise vector pdf is
The elements of observed vector r=(r1, r2,….rN) are independent Gaussian random variables. Its pdf is
0
2
20
||||exp
)(
1)(
NNp
N
nnn
0
2
20
||||exp
)(
1)|(
NNp i
Ni
srsrn
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Graphical Example of ML Detection
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Average Probability of Symbol Error Erroneous decision : For the transmitted symbol mi or equivalently signal
vector si, an error in decision occurs if the observation vector r does not fall inside region Zi.
Probability of erroneous decision for a transmitted symbol
Probability of correct decision for a transmitted symbol
)| inside lienot does Pr()Pr()ˆPr( setmZsentmmm iiii r
)(1)(
)|()| inside lies Pr()(
)| inside lies Pr()Pr()ˆPr(
icie
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setmZsentmmm
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rrr
r
r
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Avg. Prob. of Symbol Error (cont´d)
Average probability of symbol error :
For equally probable symbols :
M
iiE mmMP
1
)ˆPr()(
M
i Z
i
M
iic
M
iieE
i
dmPM
mPM
mPM
MP
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)|(1
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)(
rrr
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
BER (Bit Error Rate) Received signal in Additive White Gaussian Noise Channel
After Matched Filtering & Sampling
where
)()()( tntstr i 2,1,0 iTt
2,1, inaz oi
bEa 1 bEa 2 )2/,0(: oo NNn
,
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Bit Error Probability
)|()()|()( 212121 sHPsPsHPsPPB
21)()( 21 sPsP
)|()|( 2112 sHPsHP
)|( 21 sHPPB
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Maximum Likelihood Decision
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/2
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)|(
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Ex
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b
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o
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2
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
BER versus Eb/No
bbobb RTWNNSTE /1,/,
WN
RS
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TS
N
E bbb
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/
/0
b
b
R
W
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0
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Inter-Symbol Interference (ISI)
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Inter-Symbol Interference (ISI) ISI in the detection process due to the filtering effects of the
system Overall equivalent system transfer function
creates echoes and hence time dispersion causes ISI at sampling time
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Inter-Symbol Interference (ISI) (cont’d)
Nyquist pulses: No ISI at the sampling time Ideal Nyquist pulse:
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Inter-Symbol Interference (ISI) (cont’d)
Nyquist bandwidth constraint
Ideal Nyquist filter is not realizable. Goals and trade-off in pulse-shaping
Reduce ISI Efficient bandwidth utilization Robustness to timing error (small side lobes)
]//[222
1Hzssymbol
W
RW
R
Tss
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Inter-Symbol Interference (ISI) (cont’d)
Raised-Cosine Filter A Nyquist pulse (No ISI at the sampling time)
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Inter-Symbol Interference (ISI) (cont’d)
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
3.3.2 Error-Performance Degradation
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Inter-Symbol Interference (ISI) (cont’d)
Square-Root Raised Cosine (SRRC) filter and Equalizer
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Types of Equalizers
Transversal filtering : Zero-forcing equalizer: Neglect the effect of noise Minimum mean square error (MSE) equalizer The basic limitation of a transversal equalizer is that it
performs poorly on channels having spectral nulls.
Decision feedback Using the past decisions to remove the ISI contributed
by them
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Transversal Equalizer
Signal Processing Lab., http://signal.korea.ac.krDept. of Elec. and Info. Engr., Korea Univ.
Decision Feedback Equalizer