The presence of upsamplers and downsamplers in the diagram of Figure 2 from "Introduction and Motivation"
implies that a basic knowledge of multirate signal processing is
indispensible to an understanding of sub-band analysis/synthesis.
This section provides the required background.
- Modulation:
Figure 1 illustrates modulation using a complex exponential
of frequency ωo.
In the time domain,
y(n)=x(n)ejωon.y(n)=x(n)ejωon.
(1)
In the z-domain,
Y(z)=∑ny(n)z-n=∑nx(n)ejωonz-n=∑nx(n)e-jωoz-n=Xe-jωoz.Y(z)=∑ny(n)z-n=∑nx(n)ejωonz-n=∑nx(n)e-jωoz-n=Xe-jωoz.
(2)
We can evaluate the result of modulation in the frequency domain by
substituting z=ejωz=ejω.
This yields
Y(ω)=∑ny(n)e-jωn=X(ω-ωo).Y(ω)=∑ny(n)e-jωn=X(ω-ωo).
(3)
Note that X(ω-ωo)X(ω-ωo) represents a shift of X(ω)X(ω)up by ωo radians, as in Figure 2.
- Upsampling:
Figure 3 illustrates upsampling by factor N.
In words, upsampling means the insertion of N-1N-1 zeros between
every sample of the input process.
Formally, upsampling can be expressed in the time domain as
y(n)=x(n/N)whenn=mNform∈Z0else.y(n)=x(n/N)whenn=mNform∈Z0else.
(4)
In the z-domain, upsampling causes
Y(z)=∑ny(n)z-n=∑mx(m)z-mN=XzN,Y(z)=∑ny(n)z-n=∑mx(m)z-mN=XzN,
(5)
and in the frequency domain,
Y(ω)=∑ny(n)e-jωn=XNω.Y(ω)=∑ny(n)e-jωn=XNω.
(6)
As shown in
Figure 4, upsampling shrinks
X(ω)X(ω) by a factor of N along the ω axis.
- Downsampling:
Figure 5 illustrates downsampling by factor N.
In words, the process of downsampling keeps every NthNth sample
and discards the rest.
Formally, downsampling can be written as
y(m)=x(mN).y(m)=x(mN).
(7)
In the z domain,
Y(z)=∑my(m)z-m=∑mx(mN)z-m=∑nx˜(n)z-n/N,Y(z)=∑my(m)z-m=∑mx(mN)z-m=∑nx˜(n)z-n/N,
(8)
where
x˜(n)=x(n)whenn=mNform∈Z0else.x˜(n)=x(n)whenn=mNform∈Z0else.
(9)
The neat trick
1N∑p=0N-1ej2πNnp=1whenn=mNform∈Z0else1N∑p=0N-1ej2πNnp=1whenn=mNform∈Z0else
(10)
(which is not difficult to prove) allows us to rewrite x˜(n)x˜(n) in terms
of x(n)x(n):
Y(z)=∑nx(n)1N∑p=0N-1ej2πNnpz-n/N=1N∑p=0N-1∑nx(n)e-j2πNpz1/N-n=1N∑p=0N-1Xe-j2πNpz1/N.Y(z)=∑nx(n)1N∑p=0N-1ej2πNnpz-n/N=1N∑p=0N-1∑nx(n)e-j2πNpz1/N-n=1N∑p=0N-1Xe-j2πNpz1/N.
(11)
Translating to the frequency domain,
Y(ω)=1N∑p=0N-1Xω-2πpN.Y(ω)=1N∑p=0N-1Xω-2πpN.
(12)
As shown in Figure 6, downsampling expands
each 2π2π-periodic repetition of X(ω)X(ω) by a factor of N along
the ω axis.
Note the spectral overlap due to downsampling, called “aliasing.”
- Downsample-Upsample Cascade:
Downsampling followed by upsampling (of equal factor N) is
illustrated by Figure 7.
This structure is useful in understanding analysis/synthesis filterbanks
that lie at the heart of sub-band coding schemes.
This operation is equivalent to zeroing all but the mNthmNth samples
in the input sequence, i.e.,
y(n)=x(n)whenn=mNform∈Z0else.y(n)=x(n)whenn=mNform∈Z0else.
(13)
Using trick Equation 10,
Y(z)=∑ny(n)z-n=∑nx(n)1N∑p=0N-1ej2πNnpz-n=1N∑p=0N-1∑nx(n)e-j2πNpz-n=1N∑p=0N-1Xe-j2πNpz,Y(z)=∑ny(n)z-n=∑nx(n)1N∑p=0N-1ej2πNnpz-n=1N∑p=0N-1∑nx(n)e-j2πNpz-n=1N∑p=0N-1Xe-j2πNpz,
(14)
which implies
Y(ω)=1N∑p=0N-1Xω-2πpN.Y(ω)=1N∑p=0N-1Xω-2πpN.
(15)
The downsampler-upsampler cascade causes the appearance
of 2π/N2π/N-periodic copies of the baseband spectrum of X(ω)X(ω).
As illustrated in Figure 8, aliasing may result.