Linearization method for amplifier, and amplifier arrangement

Information

  • Patent Grant
  • 6741663
  • Patent Number
    6,741,663
  • Date Filed
    Friday, October 27, 2000
    23 years ago
  • Date Issued
    Tuesday, May 25, 2004
    20 years ago
Abstract
The invention relates to a linearization method for an RF amplifier and an arrangement implementing the method. A difference between an output signal of the amplifier and an unpredistorted input signal supplied to the amplifier is formed from baseband, quadrature components by means of a complex LMS algorithm in adaptation means. On the basis of the signal difference, the non-linearity of the amplifier is adaptively corrected before a quadrature modulator by changing the values of the complex quadrature components of the baseband signal by means of digital predistortion coefficients retrieved from a memory.
Description




FIELD OF THE INVENTION




The invention relates to correcting non-linear operation of amplifiers operating on radio frequencies. The invention particularly relates to a linearization method for an RF amplifier, in which method a digital input signal is divided into complex, baseband quadrature components employed by quadrature modulation, and the digital input signal is quadrature-modulated into a radio frequency signal and amplified.




The invention further relates to a linearized RF amplifier arrangement comprising a quadrature modulator arranged to quadrature-modulate a digital input signal into a radio frequency signal, which an amplifier is arranged to amplify.




BACKGROUND OF THE INVENTION




The operating range of radio-frequency power amplifiers is wider than that of small-signal amplifiers. Hence, the power amplifiers are non-linear, which results in amplitude distortion and phase distortion. These non-linearities generate frequencies in the output signal that did not exist in the original signal. For example, a base station in a cellular radio system receives and amplifies signals of different frequencies of a plurality of terminals simultaneously, in which case, at worst, a non-linear amplifier makes a radio signal to be transmitted to spread within the frequency range to the range used by the adjacent terminal. It has been the aim of the prior art solutions to correct signal distortion caused by power amplifier intermodulation by feedforwarding or predistorting. In feedforward solutions, two control loops provided with a main amplifier and for the actual signal and a distortion amplifier for signal distortion are typically applied. Distortion feedforwarding is thus used for correcting the actual signal.




In the prior art solution using predistortion, an estimate is made of the manner in which an amplifier will distort a signal. The signal to be amplified by means of the estimate is predistorted by a distortion transformation opposite to the amplifier distortion, in other words the aim is to find out the inverse function of the distortion caused by the amplifier. The amplifier then, while amplifying the signal, simultaneously compensates for the predistortion, yielding an undisturbed, ‘linearized’ signal.




In the prior art solutions, predistortion is performed either analogically or digitally. In analogue predistortion, it is difficult to detect changes in amplifier distortion; hence, digital predistortion is more preferable. Digital predistortion enables distortion to be corrected extremely efficiently. A typical digital predistortion is performed by using look-up tables that, most preferably, are to be updated in order to achieve adaptability, since amplifier distortion is affected by the amplifier's age, temperature, and changes in the signal fed to the amplifier, for instance. U.S. Pat. No. 5,049,832, which is incorporated herein by reference, discloses such a solution. In the solution of the publication, predistortion information is stored in a memory in rectangular coordinate form, which aims to reduce the amount of information to be stored; hence, an attempt is made to quicken the adaptability of the solution in changing circumstances. Particularly in view of the algorithm, the prior art solutions of this type are not, however, sufficiently stable in the changing circumstances, which causes the amplified signal to be harmfully distorted.




BRIEF DESCRIPTION OF THE INVENTION




An object of the invention is thus to provide a method and an arrangement implementing the method so as to solve the above problems.




This can be achieved by a method of the type described in the introduction, which is characterized by forming, from the baseband quadrature components, a difference between an output signal of the amplifier and the unpredistorted input signal supplied to the amplifier by means of an LMS algorithm or the like, forming a digital predistortion coefficient on the basis of the signal difference, and adaptively correcting the non-linearity of the amplifier before the quadrature modulation by changing the values of the complex quadrature components of the baseband input signal by means of a digital predistortion coefficient.




The amplifier arrangement of the invention is characterized in that it comprises adaptation means for forming a difference between an output signal of the amplifier and the unpredistorted input signal supplied to the amplifier from the baseband quadrature components by means of an LMS algorithm or the like, predistortion means for adaptively correcting the non-linearity of the amplifier before the quadrature modulator by changing the values of the complex quadrature components of the baseband input signal by means of a digital predistortion coefficient.




Several advantages can be achieved by the method and arrangement of the invention. Predistortion becomes more stable, and amplifier distortion is reduced.











BRIEF DESCRIPTION OF THE DRAWINGS




The invention will now be described in closer detail in connection with the preferred embodiments with reference to the accompanying drawings, in which





FIG. 1

shows a transceiver,





FIG. 2

shows an amplifier arrangement,





FIG. 3A

shows how delay is generated, and





FIG. 3B

shows an FIR filter.











DETAILED DESCRIPTION OF THE INVENTION




The solution of the invention is particularly suited for amplifying a radio-frequency signal in a transmitter of a radio system. Cellular radio systems to which the solution of the invention can be applied to include the GSM (Global System for Mobile Communication), DCS-1800 (Digital Cellular System), CDMA (Code Division Multiple Access) and WCDMA (Wideband CDMA).




First, let us generally examine a typical transceiver of a radio system, which can be a terminal or a base station. Let us first discuss signal reception. A signal is received by an antenna


20


from which it propagates to a duplex filter


18


. The duplex filter


18


separates the transmitter side and the receiver side. The received signal propagates from the duplex filter


18


to an actual receiver part


10


, in which the signal is usually demodulated and decoded for detecting transmitted data. Let us now discuss signal transmission. Data to be transmitted is first received by a channel coder


12


which encodes, and usually also interleaves, the signal against fadings and interference occurring in the channel. The encoded signal propagates to a modulator


14


, which, particularly in the solution of the invention, quadrature-modulates the signal. Furthermore, the modulator


14


converts the signal into a radio frequency one. Next, the signal is further amplified in a power amplifier


16


and conveyed to the duplex filter


18


. The signal transmitted from the duplex filter


18


passes to the antenna


20


and spreads in the environment as electromagnetic radiation.




First, let us view the operation of a quadrature modulator


102


and a quadrature demodulator


118


by means of FIG.


2


. Data transmitted in quadrature modulation is divided into two parts in a digital modulator


98


. The first data part Ipd is multiplied by a carrier coming from a carrier generator


110


, and the second data part Qpd is multiplied by a phase-shifted carrier. As shown in block


102


, the sum of these parts thus yields a signal supplied to an amplifier


104


. In the quadrature modulator


118


, in turn, the output signal of the amplifier


104


is multiplied both by the carrier without phase shift and by the phase-shifted carrier. Without phase shift, multiplying by the carrier can be expressed, for instance, in such a manner that the data is multiplied by a cosine carrier, which is of the form cos(ω


C


t). Multiplying by the phase-shifted carrier can be expressed in such a manner that the signal is multiplied by a sine carrier, which is of the form sin(ω


C


t). Hence, carriers having a π/2 phase shift between them are used in multiplying the signals. Since the different parts of the signal are orthogonal with respect to each other owing to the π/2 phase shift, the data parts can be expressed by using a complex way of expression. Hence, a data signal U to be transmitted, for instance, can be expressed in the form U=I+jQ, where I (Inphase) is the first data part, Q (Quadrature) the second part, and j an imaginary unit. The prior art quadrature modulators allow the wave form of both I and Q data parts to be modified before the multiplication by the carrier. In the CDMA technique, I and Q data parts are also multiplied by a spreading code before multiplying by the carrier.




Let us now take a closer look at the operation of the amplifier arrangement of the invention by means of

FIG. 2. A

signal Uin to be amplified is first converted from a serial-mode signal into two parallel signal components in the digital modulator


98


. This conversion divides the signal into two parts (in and Qin, which is the aim in quadrature modulation. Predistortion is generated in predistortion means


100


as a multiplication of a complex input signal Uin=Iin+jQin and a complex predistortion coefficient F=Fi+jFq, whereby predistorted, baseband signal components Ipd and Qpd obtained are:








Ipd=Fi*Iin−Fq*Qin












Qpd=Fi*Qin+Fq*Iin.








Hence, predistorted signal Upd is Upd=Ipd+jQpd. Next, the signal components are quadrature-modulated in the IQ modulator


102


, amplified in the RF amplifier


104


, and transmitted via an antenna


116


. In the solution of the invention, an output signal Ufe of the amplifier


104


, which comprises a complex component Ufe=Ife+jQfe, is fed back by a directional coupler


105


before the antenna


116


, and quadrature-demodulated into a baseband one in the IQ modulator


118


. The feedback, baseband and complex signal Ufe is compared with the baseband, unpredistorted input signal Uin in adaptation means


120


. The input signal Uin must be delayed in delaying means


114


to enable the timing of the digital symbols of the input signal Uin and the output signal Ufe to correspond to each other. The delaying process is controlled by a control block


121


of delay and phase, which compares the input signal Uin and the demodulated signal Ufe. The adaptation means


120


change the complex coefficient F=Fi+jFq modelling the inverse function of the distortion of the amplifier


104


such that the difference between the input signal Uin and the output signal Ufe is minimized. This can be performed by minimizing the squared error, for instance. A common LSE (Least Square Error) problem can be solved by using a Kalman algorithm, a modified Kalman algorithm (Extended Kalman Algorithm), an RLS (Recursive Least Square) algorithm or an LMS (Least Mean Square) algorithm in the adaptation means


120


. The adaptation means


120


preferably implement the minimizing algorithm. Lets us take a closer look at an LMS algorithm based on minimizing the mean square of such a difference, i.e. error. The function for difference e(n) at a moment corresponding to sample n is:








e


(


n


)


Uin


(


n


)−


Ufe


(


n


).






This difference e(n) is used for forming complex predistortion coefficients F=Fi+jFq in a following, iterative manner:








F


(


k


+1)=


F


(


k


)−μ∇


e




2


(


n


),






where k is the iteration index. Thus, predistortion coefficient F obtained is:








F


(


k


+1)=


F


(


k


)+2


μe


(


n


)


{overscore (Uin(


n


))},








where {overscore (Uin(n))} is the complex conjugate of the input signal. The iterated predistortion coefficients F are stored in a memory


108


, in which case they replace the previous predistortion values. In principle, the memory can include any number, for example a real


1


, stored in it as initial values for the predistortion coefficients F. Weighting coefficient μ determines the converging rate of the adaptation and the magnitude of the remaining difference. In view of stability, 0<μ<2/Ptot is valid for weighting coefficient μ, where Ptot is the total power of the input signal Uin.




The predistortion coefficients F are retrieved from the memory on the basis of the input signal Uin. However, the input signal Uin as such cannot be used as the address of the memory


108


, but the address is formed in address calculation means


106


. The address in the predistortion table


108


is formed by means of the amplitude of the input signal Uin. Depending on the type of the amplifier


104


, the address can be calculated in the calculation means


106


either as the sum of the squares of input signals:






address=round((


k


−1)*(


Iin




2




+Qin




2


)/2+1, or






as the square root of the sum of the squares of the input signal:






address=round((


k


−1)*sqrt((


Iin




2




+Qin




2


)/sqrt(2)+1,






where k is the size of the predistortion table, round is the rounding to the nearest integer number, and sqrt refers to the square root. In these formulas, Iin and Qin are normalized on a unit circle such that their values vary between [−1, 1]. When an amplifier is non-linear mainly at high input signal power levels, the address to be preferably used is the sum of squares since there is a greater number of addresses at high values. When an amplifier is non-linear at low input signal power levels as well, it is preferable to use the square root of the sum of the squares as the address. Hence, the predistortion coefficient F, which is of the form F(k+1)=F(k)+2μe(n)Uin(n), is the output of the table memory


108


. The predistortion coefficients thus are:








Fi


(


k


+1)


Fi


(


k


)+μ{(


Iin




2




+Qin




2




−Iin*Ife−Qin*Qfe}












Fq


(


k


+1)=


Fq


(


k


)+μ{


Qin*Ife−Iin*Qfe}.








Hence, also weighting coefficient μ is calculated separately for each address range in such a manner that:






μ
<


0.5


Iin
2

+

Qin
2



.











Delay control in the delaying means


114


must be estimated with sufficient accuracy. The delay is estimated by transmitting and receiving a pseudo noise sequence of the M sequence type, for instance. Other sequences with sufficiently good autocorrelation characteristics can also be used as pseudo noise sequences. An advantage of the M sequences is that they can be readily generated by means of a shift register, and their autocorrelation is a narrow peak. The delay result is estimated in the control means


121


by calculating the correlation between a transmitted and a received sequence. The delaying means


114


delay the input signal by a length corresponding to the calculated delay result. A correlation of this kind allows the delay to be calculated with an accuracy of entire samples. Even more accurately than one sample, the delay can be calculated as a fractional delay for instance in a following manner:







fraction
=


NCorr
-
PCorr


NCorr
+
PCorr
+
MaxCorr
-

3
*
min






(

NCorr
,
MaxCorr
,
PCorr

)





,










where MaxCorr is the highest value of the correlation, Ncorr the next value to the maximum correlation, and Pcorr the value preceding the maximum value. Mathematically, the correlation C(τ) for functions x(t) and y(t) is formed for instance in the following manner:








C






(
t
)


=



a
b



x






(
τ
)






y






(

τ
+
t

)








τ




,










where a and b represent the calculation period of the correlation. Digitally, correlation row C is calculated as a cross product for sequences X and Y in the following manner:








C






(
n
)


=




i
=
1

N







x






(
i
)






y






(

n
+
i

)




,










where each C(n) corresponds to an element of correlation row C. When Y is sequence X delayed in the transmitter, the delay of the transmitter can be defined. A fractional value thus formed is used in a digital fractional value filter, which delays the signal sufficiently. Preferably, the input signal Uin is actively and continuously delayed, in which case the transmitter, to keep the delay optimal, recurrently transmits a pseudo-random sequence through the amplifier


104


.

FIG. 3A

shows the implementation of such a fractional delay as a arrow structure. The input signal Uin and the fractional result formed serve as the inputs of the Farrow structure. The input signal Uin is fed into four FIR (Finite Impulse Response) filters


300


,


302


,


304


and


306


. The output of the FIR filter


300


and the fractional result are multiplied in a multiplier


308


, after which the input is added to the output of the next FIR filter in a summer


310


. The sum signal is multiplied by the fractional result in a multiplier


312


. Next, the input is added to the output of the FIR filter


304


in a summer


314


, and the sum is multiplied by the fractional result in- a multiplier


316


. This input, in turn, is added to the output of the FIR filter


306


in a summer


318


, whereby the output signal of the summer


318


is a signal delayed in a desired manner. A Farrow structure of this kind is a part of a delay block


114


. The blocks


106


,


108


,


114


,


120


and


121


form an adaptation part


130


of the inventive solution.





FIG. 3B

shows a general block diagram of an FIR (Finite Impulse Response) filter. The FIR filter comprises delay elements


3001


to


3003


, weighting coefficient blocks


3004


and a summer


3005


. The FIR filters


300


to


306


of

FIG. 3A

are as shown in FIG.


3


B. An input signal Uin is delayed in each delay element


3001


to


3003


, and the delayed signals are weighted by an appropriate weighting coefficient in the weighting coefficient blocks


3004


. The delayed and weighted signals are summed in the summer


3005


. The solution of the invention is provided with an almost limitless number of delay and weighting coefficient combinations to effect a desired fractional delay in the input signal in the Farrow structure. As an example can be given for instance a solution which uses an 8-tap FIR filter. Consequently, there are eight delay elements and eight weighting coefficient blocks. The weighting coefficients can all be 1, and the delay can be the same particular delay in all delay elements


3001


to


3003


.




Another essential block in the inventive solution is the block


112


of phase adjustment. Consequently, the input signal and the signal amplified by the amplifier are measured in the solution of the invention. By comparing these signals, the phase adjustment block


112


is controlled to keep the up- and down-converter carriers phase-synchronized in the IQ modulators


102


and


118


. Phase adjustment can also be performed in the baseband parts by means of digital signal processing by changing the phase angle of the complex input and/or feedback signal. Phase adjustment is most preferably performed in the delay and phase block


121


, which controls the phase adjustment block


112


. This monitoring of the carrier phases is also most preferably actively performed in the solution of the invention, in other words signal phases are continuously monitored and, if necessary, changed.




In the solution of the invention, adaptation is thus performed in the adaptation means


120


and the memory


108


. Particularly for digital signal processing, the solutions of the invention can be implemented for instance by ASIC (Application-Specific Integrated Circuit) or VLSI (Very Large Scale Integration) circuits. Functions to be performed are preferably implemented as software-based microprosessor technique.




Although the invention is described above with reference to an example in accordance with the accompanying drawings, it is obvious that the invention is not restricted thereto but it can be modified in various ways within the scope of the inventive idea disclosed in the attached claims.



Claims
  • 1. A linearization method for an RF amplifier, in which method a digital input signal is divided into complex baseband quadrature components employed by quadrature modulation, and in which method the digital input signal is quadrature-modulated into a radio frequency signal and amplified, the method comprising:forming, from the baseband quadrature components, a signal difference between an output signal of the amplifier and an unpredistorted input signal supplied to the amplifier by means of an LMS algorithm; forming a digital predistortion coefficient based on the signal difference; adaptively correcting non-linearity of the amplifier before the quadrature modulation by changing values of the complex quadrature components of the unpredistorted input signal by means of the digital predistortion coefficient; and delaying the unpredistorted input signal by means of a correlation between the unpredistorted input signal and the output signal, wherein the step of delaying is arranged to form a delay as a fractional delay as follows: fraction=NCorr-PCorrNCorr+PCorr+MaxCorr-3*min⁢ ⁢(NCorr,MaxCorr,PCorr),where MaxCorr is a highest value of the correlation between the unpredistorted input signal and the output signal, Ncorr is a value following the highest value, and Pcorr is a value preceding the highest value.
  • 2. The method as claimed in claim 1, further comprising actively correcting a time difference between the unpredistorted input signal and a feedback output signal from the amplifier by delaying the unpredistorted input signal.
  • 3. The method as claimed in claim 1, further comprising storing the predistortion coefficient in a table memory,retrieving the predistortion coefficient from the table memory by means of the unpredistorted input signal, and predistorting the unpredistorted input signal by the predistortion coefficient.
  • 4. The method as claimed in claim 1, further comprising iterating the predistortion coefficient F(k) as follows:F(k+1)=F(k)+2μe(n){overscore (Uin(n))}, where, for sample n, μ is a weighting coefficient, k is an index of iteration, e is a difference Uin(n)−Ufe(n) between the unpredistorted input signal Uin and the output signal Ufe, {overscore (Uin(n))} is a complex conjugate of input signal, and F(k+1) is a new predistortion coefficient stored in a table memory.
  • 5. The method as claimed in claim 3, further comprising expressing the unpredistorted input signal as complex components employed by the quadrature modulation as follows:Uin=Iin+jQin, wherein Iin is a real I component of the digital input signal, Qin is an imaginary Q component of the digital input signal, and j is an imaginary unit, and wherein the digital input signal Iin+jQin is predistorted by predistortion coefficient F=Fi+jFq as follows: Ipd=Fi*Iin−Fq*Qin Qpd=Fi*Qin+Fq*Iin, wherein Ipd is a distorted I component of the digital input signal, Qpd is a distorted Q component of the digital input signal, Fi is a distortion coefficient in an Inphase part of the digital input signal, and Fq is a distortion coefficient in a Quadrature part of the digital input signal.
  • 6. The method as claimed in claim 4, further comprising calculating the weighting coefficient μ such that it is valid when: μ<0.5Ptot,wherein Ptot is total power of the digital input signal received.
  • 7. The method as claimed in claim 3, further comprising calculating predistortion coefficients substantially as follows:Fi(k+1)=Fi(k)+μ{(Iin2+Qin2−Iin*Ife−Qin*Qfe}Fq(k+1)=Fq(k)+μ{Qin*Ife−Iin*Qfe}, and calculating weighting coefficient μ such that it is substantially valid when: μ<0.5Iin2+Qin2;wherein Fi is a distortion coefficient in an Inphase part of the digital input signal, Fq is a distortion coefficient in a Quadrature part of the digital input signal, k is an index of iteration, Ife is a feedback of an Inphase signal, Qfe is a feedback of a Quadrature signal, Iin is a real I component of the digital input signal, and Qin is an imaginary Q component of the digital input signal.
  • 8. The method as claimed in claim 1, further comprising quadrature-demodulating a feedback output signal of the amplifier, and actively maintaining phase synchronization between an input signal quadrature modulation and an output signal quadrature demodulation.
  • 9. The method as claimed in claim 1, further comprising retrieving the predistortion coefficient from a table memory based on a sum of squares of the quadrature components of the unpredistorted input signal.
  • 10. The method as claimed in claim 3, further comprising retrieving the predistortion coefficient from the table memory based on a square root of a sum of squares of the quadrature components of the unpredistorted input signal.
  • 11. A linearized RF amplifier arrangement comprising a quadrature modulator arranged to quadrature-modulate a digital input signal into a radio frequency signal and an amplifier arranged to amplify, the amplifier arrangement comprising:adaptation means for forming a difference between an output signal of the amplifier and an unpredistorted input signal supplied to the amplifier from baseband quadrature components by means of an LMS algorithm; predistortion means for adaptively correcting non-linearity of the amplifier before the quadrature modulator by changing values of complex quadrature components of the unpredistorted input signal by means of a digital predistortion coefficient; and delaying means for actively correcting a time difference between a baseband unpredistorted input signal and a feedback output signal from the amplifier by delaying the unpredistorted input signal, wherein the delaying means are arranged to delay the unpredistorted input signal by means of a correlation between the unpredistorted input signal and the output signal and wherein the delaying means are arranged to form the delay as a fractional delay as follows: fraction=NCorr-PCorrNCorr+PCorr+MaxCorr-3*min⁢ ⁢(NCorr,MaxCorr,PCorr),where MaxCorr is a highest value of the correlation between the unpredistorted input signal and the output signal, Ncorr is a value following the highest value, and Pcorr is a value preceding the highest value.
  • 12. The amplifier arrangement as claimed in claim 11, wherein the amplifier arrangement comprises a table memory in which the predistortion coefficient is stored, wherein the amplifier arrangement is arranged to retrieve a predistortion value from the table memory by means of the unpredistorted input signal, and wherein the predistortion means distort the unpredistorted input signal by the predistortion coefficient.
  • 13. The amplifier arrangement as claimed in claim 11, wherein the adaptation means are arranged to iterate the predistortion coefficient F(k) as follows:F(k+1)=F(k)+2μe(n){overscore (Uin(n))}, where, for sample n, μ is a weighting coefficient, k is an index of iteration, e is a difference Uin(n)−Ufe(n) between the unpredistorted input signal Uin and the feedback output signal Ufe, {overscore (Uin(n))} a complex conjugate of the unpredistorted input signal, and F(k+1) is a new predistortion coefficient.
  • 14. The amplifier arrangement as claimed in claim 13, wherein the unpredistorted input signal is expressed as complex components employed by quadrature modulation as follows:Uin=Iin+jQin, where Iin is a real I component of the digital input signal, Qin is an imaginary Q component of the digital input signal, and j is an imaginary unit, and wherein the digital input signal Iin+jQin is predistored by predistortion coefficient F=Fi+jFq as follows: Ipd=Fi*Iin−Fq*Qin Qpd=Fi*Qin+Fq*Iin, where Ipd is a distorted I component of the digital input signal, Qpd is a distorted Q component of the digital input signal, Fi is a distortion coefficient in an Inphase part of the digital input signal, and Fq is a distortion coefficient in a Quadrature part of the digital input signal.
  • 15. The amplifier arrangement as claimed in claim 13, wherein the adaptation means are arranged to use the weighting coefficient μ which is valid when: μ<0.5Ptot,where Ptot is total power of the digital input signal received.
  • 16. The amplifier arrangement as claimed in claim 13, wherein the adaptation means are arranged to form the predistortion coefficient substantially as follows:Fi(k+1)Fi(k)+μ{(Iin2+Qin2−Iin*Ife−Qin*Qfe)}Fq(k+1)=Fq(k)+μ{Qin*Ife−Iin*Qfe}, wherein Iin is a real I component of the digital input signal, Qin is an imaginary Q component of the digitial input signal, Ife is a feedback of an inphase signal, Qfe is a feedback of a quadrature signal, k is an index of iteration, Fi is a distortion coefficient in an Inphase part of the digital input signal, Fq is a distortion coefficient in a Quadrature part of the digital input signal, and the weighting coefficient μ is calculated such that it is substantially valid when μ<0.5Iin2+Qin2.
  • 17. The amplifier arrangement as claimed in claim 11, wherein the amplifier arrangement comprises a quadrature demodulator which is arranged to quadrature demodulate the feedback output signal of the amplifier and wherein the amplifier arrangement comprises phase adjustment means for actively maintaining phase synchronization between the digital input signal of the quadrature modulator and an output signal of the quadrature demodulator.
  • 18. The amplifier arrangement as claimed in claim 12, wherein the amplifier arrangement is arranged to retrieve the predistortion coefficient from the table memory based on a sum of squares of quadrature components of the unpredistorted input signal.
  • 19. The amplifier arrangement as claimed in claim 12, wherein the amplifier arrangement is arranged to retrieve the predistortion coefficient from the table memory based on a square root of a sum of the square of quadrature components of the predistortion input signal.
Priority Claims (1)
Number Date Country Kind
980967 Apr 1998 FI
Parent Case Info

This application is a continuation of international application serial number PCT/FI99/00352, filed Apr. 28, 1999.

US Referenced Citations (4)
Number Name Date Kind
5113414 Karam et al. May 1992 A
5923712 Leyendecker et al. Jul 1999 A
6075411 Briffa et al. Jun 2000 A
6141390 Cova Oct 2000 A
Continuations (1)
Number Date Country
Parent PCT/FI99/00352 Apr 1999 US
Child 09/702922 US