Method and system for baseband predistortion linearization in multi-channel wideband communication systems
An efficient baseband predistortion linearization method for reducing the spectral regrowth and compensating memory effects in wideband communication systems using effective multiplexing modulation technique such as wideband code division multiple access and orthogonal frequency division multiplexing is disclosed. The present invention is based on the method of piecewise pre-equalized lookup table based predistortion, which is a cascade of a lookup table predistortion and piecewise pre-equalizers, to reduce the computational complexity and numerical instability for desired linearity performance with memory effects compensation for wideband transmitter systems.
1. A method of reducing adjacent channel power ratio and compensating memory effects of multi-channel wideband communication systems using multiplexing modulation techniques comprising the steps of
generating an address from samples of a baseband input signal of a communication system;
retrieving from a memoryless lookup table an entry in accordance with the address;
pre-equalizing the baseband input signal using the following equation:
z
(
n
)
=
∑
k
=
0
K
-
1
W
k
m
(
u
(
n
)
)
·
x
(
n
-
k
)
==
∑
k
=
0
K
-
1
W
k
m
(
u
(
n
)
)
·
u
(
n
-
k
)
·
F
m
(
u
(
n
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k
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)
,
wherein W k m (|u(n)|) is the k-th tap and m-th indexed coefficient corresponding to the magnitude of the input signal, u(n); and
multiplying the pre-equalized baseband input signal and the lookup table entry.
2. The method of claim 1 wherein the entries in the lookup table are complex coefficients.
3. The method of claim 1 wherein the pre-equalizing step includes piecewise equalization.
4. The method of claim 3 wherein said the piecewise pre-equalizers use a finite impulse response filter rather than an infinite impulse response filter.
5. The method of claim 1 wherein the pre-equalizing step uses finite impulse response filtering.
6. The method of claim 1 further including updating the entries using an indirect learning method.
7. The method of claim 6 wherein the indirect learning method uses a least mean squares algorithm.
8. The method of claim 1 wherein the retrieving step is performed by determining the following equation:
m =round(| u ( n )|· N ),
wherein u(n) is the input signal and the round function returns the nearest integer number which is the index (m) and N is the LUT size.
9. The method of claim 1 wherein the multiplying step is performed by the following equation:
x ( n )= u ( n )· F m (| u ( n )|),
wherein F m (|u(n)|) is the complex coefficient of the memoryless LUT.
10. The method of claim 1 further comprising performing a second pre-equalizing step using the following equation:
W m (| u ( n+ 1)|)= W m (| u ( n )|)+μ·( y FI ( n ) T )*· E ( n )
wherein y FI (n) is the input of the multiple equalizers in the feedback path, E(n) the error signal, p the step size, and * the complex conjugate.
11. A system for reducing adjacent channel power ratio and compensating memory effects of multi-channel wideband communication systems using multiplexing modulation techniques comprising an address generator for generating an address form samples of a baseband input signal of a communication system;
a memoryless lookup table having therein coefficients addressable according to the address;
a multiplier for combining the baseband input signal and the coefficients; lookup table entry; and
an equalizer for pre-equalizing the multiplier to compensate for memory effects in a power amplifier of the communications system, wherein pre-equalizing comprises using the following equation:
z
(
n
)
=
∑
K
=
0
K
-
1
W
k
m
(
u
(
n
)
)
·
x
(
n
-
k
)
==
∑
K
=
0
K
-
1
W
k
m
(
u
(
n
)
)
·
u
(
n
-
k
)
·
F
m
(
u
(
n
-
k
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)
,
wherein W k m (|u(n)|) is the k-th tap and m-th indexed coefficient corresponding to the magnitude of the input signal, u(n).