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Limited By:	Subject = Linearization;

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1-b Observation for Direct-Learning-Based Digital Predistortion of RF Power Amplifiers (2017)

Wang, Haoyu; Li, Gang; Zhou, Chongbin; Zhu, Anding; et al.

1-b Observation for Direct-Learning-Based Digital Predistortion of RF Power Amplifiers (2017)

Wang, Haoyu; Li, Gang; Zhou, Chongbin; Zhu, Anding; et al.

Abstract:

In this paper, we propose a low-cost data acquisition approach for model extraction of digital predistortion (DPD) of RF power amplifiers. The proposed approach utilizes only 1-bit resolution analog-to-digital converters (ADCs) in the observation path to digitize the error signal between the input and output signals. The DPD coefficients are then estimated based on the direct learning architecture using the measured signs of the error signal. The proposed solution is proved to be feasible in theory and the experimental results show that the proposed algorithm achieves equivalent performance as that using the conventional method. Replacing high resolution ADCs with 1- bit comparators in the feedback path can dramatically reduce the power consumption and cost of the DPD system. The 1-bit solution also makes DPD become practically implementable in future broadband systems since it is relatively straightforward to achieve an ultra-high sampling speed in data conversion by using only sim...

http://hdl.handle.net/10197/8381

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Band-Limited Volterra Series-Based Digital Predistortion for Wideband RF Power Amplifiers (2017)

Yu, Chao; Guan, Lei; Zhu, Erni; Zhu, Anding

Band-Limited Volterra Series-Based Digital Predistortion for Wideband RF Power Amplifiers (2017)

Yu, Chao; Guan, Lei; Zhu, Erni; Zhu, Anding

Abstract:

The continuously increasing demand for wide bandwidth creates great difficulties in employing digital predistortion (DPD) for radio frequency (RF) power amplifiers (PAs) in future ultra-wideband systems because the existing DPD system requires multiple times the input signal bandwidth in the transmitter and receiver chain, which is sometimes almost impossible to implement in practice. In this paper, we present a novel band-limited digital predistortion technique in which a band-limiting function is inserted into the general Volterra operators in the DPD model to control the signal bandwidth under modeling, which logically transforms the general Volterra series-based model into a band-limited version. This new approach eliminates the system bandwidth constraints of the conventional DPD techniques, and it allows users to arbitrarily choose the bandwidth to be linearized in the PA output according to the system requirement without sacrificing performance, which makes the DPD system des...

http://hdl.handle.net/10197/8643

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Dual-loop Model Extraction for Digital Predistortion of Wideband RF Power Amplifiers (2017)

Guan, Lei; Zhu, Anding

Dual-loop Model Extraction for Digital Predistortion of Wideband RF Power Amplifiers (2017)

Guan, Lei; Zhu, Anding

Abstract:

A dual-loop parameter characterization structure is proposed in order to improve the accuracy of the model extraction in digital predistortion systems. In this concept, a model reference loop is used in conjunction with a model inverse structure for fine tuning the model parameters. This model extraction process does not increase much of the complexity of system implementation but experimental results show that linearization performance can be significantly improved by employing the proposed structure for wideband RF power amplifiers.
Science Foundation Ireland

http://hdl.handle.net/10197/8647

Marked Mark

Low Complexity Stochastic Optimization-Based Model Extraction for Digital Predistortion of RF Power Amplifiers (2017)

Kelly, Noel; Zhu, Anding

Low Complexity Stochastic Optimization-Based Model Extraction for Digital Predistortion of RF Power Amplifiers (2017)

Kelly, Noel; Zhu, Anding

Abstract:

This paper introduces a low-complexity stochastic optimization-based model coefficients extraction solution for digital predistortion of RF power amplifiers (PAs). The proposed approach uses a closed-loop extraction architecture and replaces conventional least squares (LS) training with a modified version of the simultaneous perturbation stochastic approximation (SPSA) algorithm that requires a very low number of numerical operations per iteration, leading to considerable reduction in hardware implementation complexity. Experimental results show that the complete closed-loop stochastic optimization-based coefficient extraction solution achieves excellent linearization accuracy while avoiding the complex matrix operations associated with conventional LS techniques.
European Commission - European Regional Development Fund
Science Foundation Ireland

http://hdl.handle.net/10197/8389

Marked Mark

Output-Controllable Partial Inverse Digital Predistortion for RF Power Amplifiers (2017)

Yu, Chao; Allegue-Martínez, Michel; Guo, Yan; Zhu, Anding

Output-Controllable Partial Inverse Digital Predistortion for RF Power Amplifiers (2017)

Yu, Chao; Allegue-Martínez, Michel; Guo, Yan; Zhu, Anding

Abstract:

In this paper, an output-controllable digital predistortion (DPD) technique is proposed to partially inverse the nonlinear behavior of RF power amplifiers (PAs). Compared to the existing DPD, the proposed method changes the goal that the PA output must be exactly the same as the original input to a new one that the PA output can be arbitrarily controlled according to user's demand. The proposed approach largely expands the capability of DPD and thus provides more flexibility for system designers to effectively use DPD to manipulate the PA output in order to handle more application scenarios and objectively conduct further system optimization. Various application cases have been tested. The experimental results demonstrate that the proposed approach has great potential in future wireless communication system design.
Science Foundation Ireland

http://hdl.handle.net/10197/8416

Marked Mark

Single-Model Single-Feedback Digital Predistortion for Concurrent Multi-band Wireless Transmitters (2017)

Yu, Chao; Xia, Jing; Zhu, Xiao-Wei; Zhu, Anding

Single-Model Single-Feedback Digital Predistortion for Concurrent Multi-band Wireless Transmitters (2017)

Yu, Chao; Xia, Jing; Zhu, Xiao-Wei; Zhu, Anding

Abstract:

In this paper, a novel single-model single-feedback digital predistortion (DPD) technique is proposed to linearize concurrent multi-band wireless transmitters. By employing carrier relocation and band-limiting functions in digital signal processing, DPD model complexity is significantly reduced and only one narrowband feedback loop is required for data acquisition. In the new system, the linearization bandwidth can be arbitrarily reconfigured, which provides considerable flexibility for DPD system design in wideband concurrent operations. Experimental tests were conducted to validate various cases including a concurrent quad-band scenario that is reported for the first time to date. Excellent performance demonstrates that the proposed approach provides an effective solution for reducing DPD system implementation complexity and cost in both digital and analog domains for future wideband concurrent multi-band transmitters.
Science Foundation Ireland

http://hdl.handle.net/10197/8401