Unformatted text preview: Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 1 Intuitive Guide to Principles of Communications
www.complextoreal.com Inter Symbol Interference (ISI) and raised cosine filtering
Intersymbol interference (ISI) is an unavoidable consequence of both wired and wireless
communication systems. Morse first noticed it on the transatlantic telegraph cables
transmitting messages using dots and dashes and it has not gone way since. He handled it
by just slowing down the transmission.
Am plitude Tim e
Sym bol T ime (a)
Am plitude Tim e
Delay Spread (b)
Fig 1  (a) What was sent, (b) What was received.
During these early attempts at transmission, it was noticed is that the received signals
tended to get elongated and smeared into each other. A short pulse to represent a dot was
received as a muchsmeared version of the same thing. The problem appeared to be
related to the properties of the medium used and the distance of signal travel. To counter
this undesired effect, intermediate repeating stations were established and ways had to be
devised to reduce this smearing.
How does this actually affect us now? Fig 2 shows a data sequence, 1,0,1,1,0, which we
wish to send. This sequence is in form of square pulses. Square pulses are nice as an
abstraction but in practice they are hard to create and also require far too much
bandwidth. So we shape them as shown in the dotted line. The shaped version looks
essentially like a square pulse and we can quickly tell what was sent even visually.
Advantage of (an arbitrary) shaping at this point is that it reduces bandwidth
requirements and can actually be created by the hardware. Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 2 Amplit ude
1 Sym bol 3 4 Tim e 2 5 Fig 2  Sequence 101101 to be sent, the dashed line is the shape that is actually sent.
Fig 3 shows each symbol as it is received. We can see what the transmission medium
creates a tail of energy that lasts much longer than intended. The energy from symbols 1
and 2 goes all the way into symbol 3. Each symbol interferes with one or more of the
subsequent symbols. The circled areas show areas of large interference.
Amplit ude I nterf erence into Sym bol 3
f rom sy mbols 1 and 2 Int erferenc e int o Sy mbol 4
from s ym bols 2 and 3 4 3 1 5 2 Tim e Fig 3  Each symbol is spread by the medium
Fig. 4 shows the actual signal seen by the receiver. It is the sum of all these distorted
symbols. Compared to the dashed line that was the transmitted signal, the received signal
looks quite indistinct. The receiver does not actually this signal, it sees only the little dots,
the value of the amplitude at the timing instant. Notice that for symbol 3, this value is
approximately half of the transmitted value, which makes this particular symbol is more
susceptible to noise and incorrect interpretation and this phenomena is the result of this
symbol delay and smearing.
Amplit ude
1 4
3 T ime
2 5 Fig 4  Received signal vs. the transmitted signal Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 3 This spreading and smearing of symbols such that the energy from one symbol effects the
next ones in such a way that the received signal has a higher probability of being
interpreted incorrectly is called Inter Symbol Interference or ISI.
ISI can be caused by many different reasons. It can be caused by filtering effects from
hardware or frequency selective fading, from nonlinearities and from charging effects.
Very few systems are immune from it and it is nearly always present in wireless
communications.
Communication system designs for both wired and wireless nearly always need to
incorporate some way of controlling it.
What can you do about ISI?
The main problem is that energy, which we wish to confine to one symbol, leaks into
others. So one of the simplest things we can do to reduce ISI is to just slow down the
signal. Transmit the next pulse of information only after allowing the received signal has
damped down, as shown below. The time it takes for the signal to die down is called
delay spread, whereas the original time of the pulse is called the symbol time. If delay
spread (see Fig. 1) is less than or equal to the symbol time then no ISI will result,
otherwise yes.
Slowing down the bit rate was the main way ISI was controlled on those initial
transmission lines. Then faster chips came and allowed us to do signal processing
controlling ISI and transmission speeds increased accordingly.
In our march for ever higher bit rates, slowing down the data rate is an easy but an
unacceptable solution. What else can we do to counter ISI that does not require reducing
the bit rate?
The main tool used to counter ISI is pulse shaping. How can pulse shaping help control
ISI? The secret lies in the digital demodulation process used. When the timing pulse
slices the signal to determine the value of the signal at that instant, it does not care what
the signal looked like before or after it. So if there was some way we could keep the
symbols from interfering in such a way that they do not affect the amplitude at the slicing
instant, we can counter ISI successfully.
Look at the wildly bouncing signal in Fig. 5.However, the receiver only sees the points at
the timing pulses (shown below the signal) and rest of the variation has no effect. So as
long at these points, we can reduce the effect of adjacent symbols, that’s all we need to
do to mitigate the effect. Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering Trans mit ted sig nal Amplit ude 4 Sign al 1 1 4 Signal 2 3 Tim e
2 5 Slicin g puls es Fig 5  We only care about what the signal does at the moment of sampling. What it
does in between is not important. Using a square pulse shape
We will start by looking at the use of a square pulse. It is an intuitive shape and we want
to see what if anything is wrong with using it.
Let's define some terms
Ts = Symbol Time, 1 second in the example below. (Don’t be confused by the
negative time. The symbol time spans both positive and negative axis.)
Rs, the symbol rate is inverse of Symbol Time, Ts. Rs is directly related to
bandwidth such that larger the symbol rate, the more bandwidth is required.
Rs = 1/Ts
Fig. 6 shows a square pulse of amplitude A, lasting 1 second. (From .5 secs to +.5 secs)
Sy mbol Time 2 1.5 1 0.5 0 0.5 1 1.5 2 Time Fig 6  The square pulse in timedomain
Since the symbol time is 1 second, the symbol rate is 1 symbol per second. The frequency
response of this square pulse (its Fourier Transform) is given by the equation
h(t ) = sin( 2πt / Ts )
where Ts = symbol time (1 sec)
2π t Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 5 Bandwidt h 8 7 6 5 4 3 2 1 1 0 2 3 4 5 6 7 8 F requency (a) Lowpass Bandpass
Bandwidt h 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 F requency (b) Bandpass
Fig 7  The frequency response of the square pulse is a sinc function
lowpass bandwidth is one half of the bandpass case.
In the above case, the symbol time is 1 second. The symbol rate hence is also equal to 1.
The frequency response of the square pulse is in the shape of a sinc function (sin x/x). It
has a maximum amplitude of ATs and it crosses the zero amplitude at integer multiples of
Rs. The lowpass bandwidth which is defined as the distance from origin to the first zero
crossing, is equal to twice the symbol rate or, 1 Hz. The bandpass case is twice that. This
lowpass, bandpass business is confusing but you can understand it better if you realize
that bandwidth is always measured on the positive axis.
The following figure shows square several pulses and their frequency response. Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 6 Tim e dom ain S1
S3 .5 . 25 .125 0 S2 .12 5 .25 .5 Tim e Frequenc y domain S3 S2 S1 8.0 4.0 3.0 2. 0 1 .0 0 1.0 2.0 3.0 4. 0 F requency 8.0 Fig 8  The effect of square pulse symbol times and their frequency response
A narrow pulse (which is approaching a delta function) has a wide frequency response
because it has a lot of frequency content. A wide one (similar to a flat line if you squint or
have a good imagination) has lesser frequency content and hence its bandwidth is
smaller. For each pulse, the bandwidth which we measure is only on the positive half and
is equal and its symbol rate in Hz.
The important thing to note at this point is that a square pulse of symbol rate Rs has a
bandwidth of Rs Hz (for bandpass signal it is twice that.)
A very important relationship:
Bandwidth of a square pulse
= Rs for lowpass signals,
= 2 times Rs for bandpass.
The frequency response of the square pulse goes on forever. This is not a good thing.
This would theoretical interfere with others and is not allowed by the FCC.
The square pulse has some disadvantages and they are
1. The square pulse is difficult to create in time domain because of
rise time and a decay time.
2. Its frequency response goes on forever and decays slowly.
The second lobe is only 13 dB lower than the first one.
3. It is very sensitive to ISI. Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 7 If a square pulse gives us a sinc function in the frequency domain, then couldn't we use a
sinc function as a pulse shape in time domain and get a brickwall (square wave)
frequency response? We can indeed.
We can use a pulse that is shaped like a sinc function instead of a square pulse and get
that very nice brickwall spectrum, with nothing spilling outside the bandwidth. This is
great.
A sequences of bits shaped with sinc pulses may look like this. Fig 9 – Transmitting a sequence (1011) by shaping the bits as sinc pulses
Let's see what is better about using the sinc pulse as a shape instead of the square pulse.
Now we change the xaxis and go the other way. The sinc pulse becomes the time
domain shape. Its frequency response is the square shape. Sy mbol Time 2 1.5 1 0.5 0 0.5 1 1.5 2 Time Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 8 Bandw idth of sinc puls e Bandw idth of square pulse 8 7 6 5 4 3 2 1 1 0 2 3 4 5 6 7 8 F requency Fig 10  The effect of sinc pulse and its frequency response
Here is the wonderful part about using the sinc pulse. As opposed to the square pulse, we
see that using the sinc pulse cuts the bandwidth requirement to onehalf! In the figure
below, several pulses are shown of symbol rates 1, 2 and 4. In each case, we see that the
required lowpass bandwidth is onehalf of the symbol rate. S2 S1
S3 3. 5 2. 5 1.5 . 5 0 .5 1.5 2.5 3. 5 Rs
6 Rs
8 S1
S3 . 5 R s
8 R s
6 . 25 .125 R s
4 Rs
2 S2 0 .125 .25 Rs
2 .5 Rs
4 Fig 11 – Pulse width vs. frequency response The bandwidth achieved by the sinc pulse is called the Nyquist bandwidth in honor of the
man who developed it. It requires only 1/2 Hz per symbol.
Can we find something even better? It turns out that we have not been able to find any
other shape that can improve on this. It is an ultimate limit for perfect reconstruction of
the signal.
Wow, two problems gone, this is great! Bandlimited spectrum in frequency domain with
no energy going to waste and small total bandwidth requirement. Not so great however,
because a sinc pulse is actually no more possible to build than is a square pulse.
Here is what we are facing Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 9 1. In time domain a true sinc pulse is of infinite length with tails extending to
infinity so the energy can theoretically continue to add up even after the signal has
ended. We can only design an approximation to the real sinc pulse of a finite
length. But truncation leads to an imperfect pulse that does not have a true sinc
pattern and allows ISI to leak in.
2. The pulse tails that fall in the adjacent symbols decay at the rate of 1/x so if there
is some error in timing, this pulse is not very forgiving. It requires nearperfect
timing to achieve decent performance.
Nyquist offered ways to build (realizable) shapes that had the same good qualities as
the sinc pulse and less of the disadvantages.
One class of pulses he proposed are called the raised cosine pulses. They are really a
modification of the sinc pulse. Where the sinc pulse has a bandwidth of W, where W
is specified as
W = 1/2Ts
The raised cosine pulses have an adjustable bandwidth which can be varied from W
to 2W. We want to get as close to W, which is called the Nyquist bandwidth, as
possible with a reasonable amount of power. The factor α related the achieved
bandwidth to the ideal bandwidth W as α = 1− W
W0 where W is Nyquist bandwidth, and W0 is the utilized bandwidth.
The factor α is called the rollof factor. It indicates how much bandwidth is being
used over the ideal bandwidth. The smaller this factor, the more efficient the scheme.
The percentage over the minimum required W is called the excess bandwidth. It is
100% for rolloff of 1.0 and 50% for rolloff of 50%. The alternate way to express the
utilized bandwidth is
W0 = (1 + α ) Rs
The typical rolloff values used for wireless communications range from .2 to .4.
Obviously we want to use as small a rolloff as possible, since this gives the smallest
bandwidth.
Here is how the class of raised cosine pulse is defined in time domain. Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering h(t ) = 10 sin( 2π t / Ts ) cos( 2π α t )
2π t
1 − (2α t / π ) 2 The first part is the sinc pulse. The second part is a cosine correction applied to the sinc
pulse to make it behave better. The sinc pulse insures that the function transitions at
integer multiples of symbol rate which makes it easy to extract timing information of the
signal. The cosine part works to reduce the excursion in between the sampling instants.
The bandwidth is now adjustable. It can be any where from 1/2 Rs to Rs. It is greater than
the Nyquist bandwidth by a factor (1+ α). For α = 0, the above equation reduces to the
sinc pulse, and for α = 1, the equation becomes that of a pure square pulse. Raised Cosine Impulse Response Am pli tude α = .8
α = .5
α = .1
Sinc puls e 20 15 10 5 0 5 10 15 20 Tim e , se cs Fig 12 – Raised cosine impulse response In frequency domain, the relationship is given by
⎧
⎪1
⎪
π Ts
⎪⎧
H ( f ) = ⎨⎨cos 2
2α
⎪⎩
⎪
⎪0
⎩ Copyright 2002 Charan Langton for f ≤
⎛
(1 − α ) ⎞⎫
⎜f−
⎟⎬
⎜
2Ts ⎟⎭
⎝
⎠ (1 − α ) 2Ts
(1 + α )
(1 − α )
for
≤f≤
2Ts
2Ts
(1 + α )
for f >
2Ts www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 11 Why do they call it raised cosine? Because the above response has a cosine function in
the frequency domain, although other many other trigonometric representations of this
equation that do not have the cosinesquared term, so it is not always clear why these are
called raised cosine.
The frequency response looks somewhat like a square pulse as we would expect. A range
of bandwidths are possible depending on the chosen α. The bandwidth can be anywhere
from 1/2 Rs (this term same as W, the Nyquist bandwidth) for the sinc pulse to Rs for the
square pulse. The bandwidth utilized is greater than the Nyquist bandwidth by a factor (1
+ α ). For α = 1 the above equation reduces to the sinc pulse, and for α = 1 the equation
becomes that of a pure square pulse. α =0
α = 1.0 α = .2
α = .4
α = .6 Ny qu is t B an dwi dth , W 2 .0 1.5 1 .0 0 .5 Exce ss
B andwi dth
W( 1 + α ) 0 .5 1.5 0 1 .0 2 .0 Fr eq uency Fig 13  The frequency response of the raised cosine pulses of Rs = 1
Example :
A satellite transponder has a bandwidth of 36 MHz. We use QPSK signaling. What data
rate is possible using a raised cosine signaling with α = .3?
For unshaped QPSK, which is a square pulse, the bandwidth requirement for lowpass is
equal to the symbol rate. For passband, the bandwidth requirement is twice that.
Rs = 1/2 36 MHz = 18 Msps.
If we use the ideal sinc pulse, we can send
Rs = B = 36 Msps
If we shape the pulse with α = .3, we can send
B = Rs(1+ α )
Rs = B/(1+ α ) = 27.7 Msps
For QPSK, with 2 bits per symbol, we get a data rate capability of 27.7*2 = 55.4 Mbps.
This is about standard for most satellite systems.
Rootraised Cosine filter Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 12 To implement the raised cosine response, we split the filtering in two parts to create a
matched set. When we split the raised cosine filtering in two parts, each part is called the
rootraised cosine. In frequency domain, we take the square root of the frequency
response hence the name rootraised cosine.
Yes, the whole raised cosine can be applied at once at the transmitter but in practice it has
been found that concatenating two filters each with a root raised cosine response (called
splitfiltering) works better. Rece ive r Transm itter Si gnal Sour ce Xm it R oo t R ais ed
Cos in e fi lter R CVR Root Ra ised
Co sine filter Other re ce iver
fu n ctio n s Chann el Fu ll Ra ise d Co si ne r esp on se sp l it in two p laces Fig 14 – Split filtering of raised cosine response, a rootraised cosine filter at the
transmitter and one at the receiver, giving a total response of a raised cosine.
The root raised cosine shaping of pulses is also called baseband filtering. The frequency
response of the root raised cosine is given by
⎧
⎪1
⎪
⎪⎧ π T
H ( f ) = ⎨⎨cos s
2α
⎪⎩
⎪
⎪0
⎩ for f ≤
⎛
(1 − α ) ⎞⎫
⎜f−
⎟⎬
⎜
2Ts ⎟⎭
⎝
⎠ (1 − α ) 2Ts
(1 − α )
(1 + α )
for
≤f≤
2Ts
2Ts
(1 + α )
for f >
2Ts Compare this to the following response for the raised cosine and you see it is just a
square root relation ship. Each of these square root responses are applied in pairs and the
total response is that of the raised cosine. Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering ⎧
⎪1
⎪
π Ts
⎪⎧
H ( f ) = ⎨⎨cos 2
2α
⎪⎩
⎪
⎪0
⎩ (1 − α ) for f ≤
⎛
(1 − α ) ⎞⎫
⎟⎬
⎜f−
⎜
2Ts ⎟⎭
⎠
⎝ 13 2Ts
(1 + α )
(1 − α )
for
≤f≤
2Ts
2Ts
(1 + α )
for f >
2Ts Compare the impulse response of the root raised filter to that of the raised cosine. We do
not see much of a difference except that there is a little bit more excursion in the rootraised cosine response. The time domain function is of course NOT the square root. The
root part applies to frequency domain.
1 0.2
6 5 4 3 2 1 0 1 2 3 6 5 4 3 2 1 0 1 2 3 4 5 6 1 0.2
4 5 6 Fig 15 – Impulse response of a. Raised cosine b. Rootraised cosine
Fig 16 shows the spectrum of the root raised cosine and the raised cosine. The bandwidth
of the raised cosine filter is specified at the 6 dB point due to the fact that the Nyquist
frequency response is reached at 3 dB which is then doubled to give 6 dB for power. The
rootraised cosine however is specified at 3 dB point because it is the square root. Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 14 Fr e que ncy Re s pons e , dB Ra ise d Cosine Fre que ncy Re sponse
Sym bol Ra te = 2
0
5
Rootrais ed c os ine, 3 dB 10
15 Rais ed c os ine, 6 dB 20
25
30
6 dB Bandw idth
of RC 35
40
1.5 2 2.5 3 3.5 4 Fr e que ncy Fig 16 – Frequency response of Raised cosine and a Rootraised cosine
Looking at the eye diagram at the transmitter and the receiver gives us some further
insight into how the rootraised cosine filtering splits the total filtering. Fig 17 – Eye diagram of shaped signals, after transmit and receive root raised cosine
filters
Root raised cosine pulses out of transmitter
receiver
α = .2, .4, .6 Copyright 2002 Charan Langton Root raised cosines pulses at the
α = .2, .4, .6 www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 15 The left side is the signal out of the first root raised cosine filter. The signal does not look
that great. But when it is filtered by the second root raised cosine filter (shown on the
right side) the output looks really nice, just as we hoped. As the rolloff factor gets larger,
the eye opens up. This says us that if there were no bandwidth limitations, it would be
much easier on the receiver if we used a large α. But since bandwidth is almost always a
limiting resource, the push is on to make α as small as possible.
Design of rootraised cosine filters
The raised cosine and the root raised cosine filters are both designed as FIR filters with a
specific number of taps. In time domain the fewer taps mean that the impulse response
has been truncated. The response of both the raised and the root raised cosine filters is
effected by choice of tap length. In general fewer taps give worse rejection. As taps
numbers are increased, the length of the time domain sequence is increased and the
rejection increases. 5 3 1 1 3 5 5 3 1 1 3 5 Fig 18 – RRC with taps sizes a. 128 and b. 64.
The two versions shown above are for tap length of 128 and 64. The shape for tap length
64 is exactly the same as the one for 128 taps; the only difference is that it has been
truncated. The effect of this truncation is that in frequency response we get some leakage
and the spectrum does not drop down as far as one for a longer tap size as shown below
in Fig 19. This is true for both raised cosine and root raised cosine filters. Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 16 As we can see the rejection increases considerably as number of taps is increased.
However if 3 dB bandwidths used as the discriminator, there is not a large difference so
most RRC filters today use either 48 or 64 tap designs.
Figure 19 shows the spectrum of a QPSK signal through the first rootraised cosine filter
of α = .3 and various tap lengths.
Rootraised Cosine Frequency Response
Symbol Rate = 2 Response, dB 0
48 Taps
64 Taps
128 Taps 10
20 256 Taps 30
3 dB Bandwidth
40
50
1.5 2 2.5 3 Frequency Frequency Response,
dB Raised Cosine Frequency Response
Symbol Rate = 4
0 48 Taps 10 64 Taps
128 Taps 20
30 256 Taps 40
50 6 dB Bandwidth 60
1.5 2 2.5 3 3.5 4 Frequency Fig 19 – Spectrum of a root raised and a raised cosine signal. (a) After the first root
raised cosine at the transmitter, (b) after the second root raised filter at receiver Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 17 0
20
40
60
80
100
120
0 2 4 256 Taps 6 8 128 Taps 10 12 64 Taps 14 16 48 Taps (a) Root raised cosine spectrum
0
20
40
60
80
100
120
140
0 2 4 48 Taps 6 8 64 Taps 10 12 128 Taps 14 16 256 Taps (b) Raised cosine spectrum
Fig 20 – Spectrum of a) root raised and b) raised cosine signal. Sinc equalization of the root raised cosine filter
In the development of raised cosine signaling, we are tacitly assuming that an ideal
sampler is sampling the signal. We assume that we receive one single pulse for a 0 or a 1,
which we then shape into root, raised cosine pulse. But in reality the incoming data may
be analog or digital and may have to be sampled for a variety of reasons such as for
conversion of sampling rates for modulation. Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 18 Pu lse tim e = Ts P ulse with = τ
s(t) m(t) z( t) X y(t )= m (t) s( t) M(f)
B Lowpass filter
B and width = B +B Fig 21  Ideal vs. nonideal sampling can lead to a sinc bias
Let's call the incoming data stream m(t). It has a certain frequency response and has a
bandwidth of B. For a perfect reconstruction, we need to sample it at a sampling
frequency of rate 2B or greater. Which means that each pulse should be no more than
1/2B seconds apart, which defines Ts as the pulse time.
Ts = 1/fs < 1/2B
The Fourier transform of an ideal impulse train is an impulse train in the from of
frequency harmonics located at integer multiples of the sampling frequency as shown in
Fig. 22. So to sample a time domain signal, with a sampling pulse train specified by s(t)
implies that after sampling we get a harmonically repeating response of the message
stream m(t). Then filter with a lowpass filter of bandwidth B to recover the original
signal.
But when the sampling pulses have a finite width, they then have their own frequency
response which gets multiplied by the message signal response. y (t ) = m(t ) s (t )
The Fourier Transform of the two sides gives us the convolution of the Fourier Transform
of the two signals. Y ( f ) = M ( f ) ∗ S( f )
The Fourier Transform of a finite width sampling pulses is S( f ) = τ
Ts ∞ ⎛ nτ ⎞ ⎛
n
⎟ δ⎜f −
⎟⎜
Ts
⎝ s⎠ ⎝ ∑ sin c⎜ T
⎜ n = −∞ ⎞
⎟
⎟
⎠ where Ts ≤ 1
2W The first part is the amplitude at 0; the second part is a sinc function, which is a function
of the duty cycle of the sampler. The last part just makes the whole thing made discrete
by multiplying it by the delta function. The duty cycle is specified as Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering duty cycle = 19 τ
Ts The duty cycle states just how wide the sampling pulse is compared to the symbol time.
A large duty cycle implies a really big (or a square pulse) and a small duty cycle implies
a very narrow pulse.
Using the generic response M(f), for message signal m(t), the convolution of M(f) with
the response of S(f) of sampler impulse train s(t) gives us the following.
Y( f ) = τ
Ts ∞ ⎛ nτ ⎞
⎛
n⎞
⎟ M⎜f − ⎟
⎟
⎜
Ts ⎟
⎝ s⎠
⎝
⎠ ∑ sin c⎜ T
⎜ n = −∞ The first part again is the amplitude, the second is the sinc function and third term is the
response of the message repeated at every integer multiple of the sampling frequency.
The result is that we get a replicating response but its amplitude has been multiplied by
the sinc function. The sinc function rollsoff according to the parameter duty cycle. A
large duty cycle means the sinc function as shown below rolls off faster than when the
pulse width is narrow.
t/ Ts = .1
t = .1
Ts = 1. 0
Puls e w idth, T Pulse tim e, Ts
D uty C yc le, dc = t/ Ts H(f )=t/ Ts (sinc (p t f)) Firs t zero cros sing at
= Ts /dc
= 10 f or dc = .1 Fig. 22  Sampling with PAMike signal leads to a sinc bias
The smaller the duty cycle, the shallower the response since we are approaching the ideal
case of zero width pulse. The first zero crossing which is important occurs at sampling
time divided by the duty cycle. In this figure we see that for a duty cycle of .1, and a
sampling frequency of 1, the first zero crossing is at 10 Hz.
What's the significance of all this? Well the closer this number is to the bandwidth of our
lowpass filter, the worse will be the distortion introduced by this flattop or PAM
sampling. Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering  1/2Bt 20 +1/ 2Bt Sampling I mpuls e t rain of rat e f s > 2Bt t < 1/ 2Bt
Low pass
filt er 2fs fs 1/2Bt +1/ 2Bt fs 2f s
t/Ts= . 3
t = .3
Ts = 1.0 D ist orted receiv ed res ponse
due to finit e s ampling
Sinc is tort ion c aused by s ampling Original desired respons e Sinc correc tion applied
to wav eform prior to sam pling 1/2Bt Firs t zero cros sing at
= Ts /dc
= 3. 33 f or dc = . 3
Predist orted trans mit ted respons e +1/ 2Bt
R eceiv ed af ter sinc equiliz ation
R eceiv ed if not c orrect ed 1/ 2Bt +1/2Bt Fig 23 – Sampling with nonideal impulses
(a) Frequency spectrum of an arbitrary signal which has a lowpass bandwidth of B
(b) Frequency spectrum of an ideal impulse train is also an impulse train repeated at
harmonics of fs.
(c) Multiplying the two together gives us the replicating spectrum of message signal.
This can be filtered to recover the signal. Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 21 (d) Now we use a nonideal sampling pulse train with duty cycle = .3.
(e) The Fourier Transform of this sampler is a sinc function with first zero at 3.33 Hz.
This distorts the spectrum of the message signal. Instead of getting the original
response, we get a depressed response.
(f) Now if we premultiply the signal with the inverse sinc function, then this effect
is nulled out and
(g) We can recover the message signal despite nonideal sampling.
Once the signal is sampled by a flattop sampler, it can be recovered by using a low pass
filter. But there is some energy loss, particularly in the higher frequencies due to the
downward sloping bias of the sinc faction. This distortion can be significant in two cases,
a. when the duty cycle is large, say over .2 and b. when the roll off factor is small. The
effect of large duty cycle is that there is inband distortion. However for Duty Cycles less
than .2, the distortion is quite minimal and can be ignored. But anything above that needs
to be corrected if we are to make raised cosine pulse perform as it should. Since the first
zero crossing occurs at Ts/dc, then a large dc gives us a closein zero crossing, hence
causes a lot of distortion.
The interaction of rolloff factor with this effect is that a smaller rolloff factor response
is approaching a brick wall spectrum and has large spectrum content in higher
frequencies which are affected more by the distortion. A larger roll factor is less affected
but then it is not so desired either because it needs a larger frequency bandwidth.
The figure below shows the amount of correction (or equalization) required for various
roll off factor. Any rolloff factor below .4 definitely requires sinc equalization. α = .2 With sinc equiliz ation
Without sinc e quiliza tion 1 α = .4
.5 α = .8 0 1 2 3 4 5 Fig 24  Sinc equalization affects low rolloff signals a lot more
We can precorrect for this distortion by multiplying the desired response by the inverse
sinc function. See the precorrected response as opposed to uncorrected response in Fig
24. The signal is then sampled and returned to the desired spectrum as shown in Fig 23
(f). Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 22 The frequency response of a sinc corrected raised cosine spectrum is given by the
following equation.
⎧ π fTs
⎪ sin(π fT )
s
⎪
⎪ π fTs ⎧ 2 π Ts
H( f ) = ⎨
⎨cos
2α
⎪ sin(π fTs ) ⎩
⎪
⎪0
⎩ for f ≤
⎛
(1 − α ) ⎞⎫
⎜f−
⎟⎬
⎜
2Ts ⎟⎭
⎝
⎠
for f > (1 − α ) 2Ts
(1 + α )
(1 − α )
for
≤f≤
2Ts
2Ts
(1 + α )
2Ts Where the rootraised response at the transmitter and the receiver is given by the
following equations. Note that only the transmitter has a sinc correction.
Transmit filter response
⎧ π fTs
⎪ sin(π fT )
s
⎪
⎪ π fTs ⎧ π Ts
H XMT ( f ) = ⎨
⎨cos
sin(π fTs ) ⎩
2α
⎪
⎪
⎪0
⎩ for f ≤
⎛
(1 − α ) ⎞⎫
⎜f−
⎟⎬
⎜
2Ts ⎟⎭
⎝
⎠
for f > (1 − α ) 2Ts
(1 + α )
(1 − α )
for
≤f≤
2Ts
2Ts
(1 + α )
2Ts The receive filter response (note has no sinc correction)
⎧
⎪1
⎪
⎪⎧ π T
H RCV ( f ) = ⎨⎨cos s
2α
⎪⎩
⎪
⎪0
⎩ for f ≤
⎛
(1 − α ) ⎞⎫
⎜f−
⎟⎬
⎜
2Ts ⎟⎭
⎝
⎠ (1 − α ) 2Ts
(1 + α )
(1 − α )
for
≤f≤
2Ts
2Ts
(1 + α )
for f >
2Ts In frequency domain we are transmitting the distorted shape and not the ones that are
shown in solid lines in Fig 24.
There are other ways to mitigate ISI such as with duobinary or partial response
signaling. These might be a topic later on.
Charan Langton Copyright 2002 Charan Langton www.complextoreal.com Inter Symbol Interference(ISI) and Rootraised Cosine (RRC) filtering 23 Copyright 1998, 2002 Charan Langton
I can be contacted at
[email protected]
Other tutorials at
www.complextoreal.com Copyright 2002 Charan Langton www.complextoreal.com ...
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This note was uploaded on 02/07/2011 for the course EEE EE567 taught by Professor Tutorials during the Spring '11 term at Birla Institute of Technology & Science, Pilani  Hyderabad.
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