Multi-band wide band power amplifier digital predistortion system

• US 8,903,337 B2
• Filed: 05/15/2013
• Issued: 12/02/2014
• Est. Priority Date: 12/21/2009
• Status: Active Grant

• Current Assignee: Dali Systems Co., Ltd.
• Original Assignee: Dali Systems Co., Ltd.
• Inventors: Kim, Wan-Jong, Cho, Kyoung-Joon, Stapleton, Shawn Patrick
• Primary Examiner(s): LE, NHAN T
• Application Number:
  US13/894,987
• Publication Number:
  US 20130251066A1
• Time in Patent Office: 566 Days
• Field of Search: 455/114.3, 455/126, 455/127.1, 455/127.2, 455/260, 455/550.1, 375/296, 375/297, 375/376
• US Class Current: 455/114.3
• CPC Class Codes: H03F 1/3247 using feedback acting on predistortion circuits H03F1/3264 takes precedence
• CPC Class Codes: H03F 2200/111 the amplifier being a dual or triple band amplifier, e.g. 900 and 1800 MHz, e.g. switched or not switched, simultaneously or not
• CPC Class Codes: H03F 2200/451 the amplifier being a radio frequency amplifier
• CPC Class Codes: H04B 1/0475 with means for limiting noise, interference or distortion H04B1/0483 takes precedence
• CPC Class Codes: H04B 1/62 for providing a predistortion of the signal in the transmitter and corresponding correction in the receiver, e.g. for improving the signal/noise ratio
• CPC Class Codes: H04L 27/2626 Arrangements specific to the transmitter only
• CPC Class Codes: H04L 27/368 adaptive predistortion

Abstract

A high performance and cost effective method of RF-digital hybrid mode power amplifier systems with high linearity and high efficiency for multi-frequency band wideband communication system applications is disclosed. The present disclosure enables a power amplifier system to be field reconfigurable and support multiple operating frequency bands on the same PA system over a very wide bandwidth. In addition, the present invention supports multi-modulation schemes (modulation agnostic), multi-carriers and multi-channels.

Claims

1. A digital predistortion system comprising:

a multi-band input signal;

at least one power amplifier for providing an amplified output including a distortion characteristic;

a feedback signal derived from the amplified output, the feedback signal including a representation of at least a portion of the distortion characteristic; and

predistortion logic responsive to an aliased representation of the feedback signal for generating predistortion coefficients for linearizing the amplified output of the power amplifier, wherein a sampling rate of the aliased representation of the feedback signal is less than twice a maximum bandwidth of the feedback signal.

2. The digital predistortion system of claim 1 wherein the sampling rate of the feedback signal is less than a sampling rate of the multi-band input signal.

3. The digital predistortion system of claim 1 wherein the predistortion logic is responsive to a sampled representation of the multi-band input signal.

4. The digital predistortion system of claim 1 further comprising a digital predistorter that receives the multi-band input signal, the digital predistorter effecting the predistortion coefficients derived by the predistortion logic.

5. The digital predistortion system of claim 1 wherein the digital predistorter utilizes an adaptive polynomial-based digital predistortion system, the polynomial-based digital predistortion system utilizing the predistortion coefficients generated by the predistortion logic.

6. The digital predistortion system of claim 5 wherein the digital predistorter utilizes a look-up-table-based digital predistortion system with finite impulse response filters, wherein coefficients for the finite impulse response filters comprise the predistortion coefficients generated by the predistortion logic.

7. The digital predistortion system of claim 1 further comprising alignment logic that aligns the feedback signal relative to the RF input signal.

8. The digital predistortion system of claim 1 wherein the aliased representation of the feedback signal has a frequency in a Nyquist zone.

9. The digital predistortion system of claim 1 wherein the predistortion coefficients are derived using a Direct Learning adaptive algorithm.

10. The digital predistortion system of claim 1 wherein the predistortion coefficients are derived using an Indirect Learning adaptive algorithm.

11. The digital predistortion system of claim 1 wherein the predistortion coefficients are derived to account for memory effects due to one or more of self-heating, bias networks and frequency dependencies of active devices in the digital predistortion system.

12. A method for amplifying signals, the method comprising:

receiving an RF input signal;

detecting an amplified output from a power amplifier, the output being responsive to the RF signal and including a distortion characteristic;

deriving a feedback signal from the amplified output, the feedback signal including a representation of at least a portion of the distortion characteristic; and

generating, via predistortion logic responsive to an aliased representation of the feedback signal, predistortion coefficients for linearizing the amplified output of the power amplifier, wherein a sampling rate of the aliased representation of the feedback signal is less than twice a maximum bandwidth of the feedback signal.

13. The method of claim 12 wherein the sampling rate of the feedback signal is less than a sampling rate of the RF input signal.

14. The method of claim 12 wherein the predistortion logic is responsive to a sampled representation of the RF input signal.

15. The method of claim 12 further comprising:

receiving a second RF input signal; and

predistorting, using a digital predistortor, the second RF input signal using the predistortion coefficients derived by the predistortion logic.

16. The method of claim 12 wherein predistorting the second RF input signal comprises utilizing an adaptive polynomial-based digital predistortion system, the polynomial-based digital predistortion system utilizing the predistortion coefficients derived by the predistortion logic.

17. The method of claim 12 further comprising aligning the feedback signal relative to the RF input signal.

18. The method of claim 12 wherein the aliased representation of the input signal has a frequency in a Nyquist zone.

19. The method of claim 12 wherein the predistortion coefficients are derived using an Direct Learning adaptive algorithm.

20. The method of claim 12 wherein the predistortion coefficients are derived using an Indirect Learning adaptive algorithm.