| 1. |
- Andersson, Christer, 1982, et al.
(författare)
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A 1-3-GHz Digitally Controlled Dual-RF Input Power-Amplifier Design Based on a Doherty-Outphasing Continuum Analysis
- 2013
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Ingår i: IEEE Transactions on Microwave Theory and Techniques. - 0018-9480 .- 1557-9670. ; 61:10, s. 3743-3752
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a linear multi-harmonic analysis method to evaluate the performance of digitally controlled dual RF-input power amplifiers (PAs). The method enables, due to its low computational cost, optimization of PA efficiency and bandwidth in a complex design space involving two independent inputs. Under the idealized assumption of short-circuited higher harmonics, the analysis is used to prove the existence of a Doherty-outphasing continuum, featuring high average efficiency over 100% fractional bandwidth. With this result as a foundation, a combiner incorporating microwave transistor parasitics is analyzed without assuming short-circuited higher harmonics, showing that high average efficiencies are also achievable under more realistic conditions. A PA is straightforwardly designed from these calculation results using two 15-W GaN HEMTs. The simulated layout-ready (large-signal transistor model) PA average drain efficiency exceeds 50% over 1.1-3.7 GHz for a 6.7-dB peak-to-average power-ratio WCDMA signal. The measured PA has a maximum output power of 44 +/- 0.9 dBm and a 6-dB output power back-off (OPBO) power-added efficiency (PAE) of 45% over 1-3 GHz. After applying digital pre-distortion, excellent linearity is demonstrated when transmitting the WCDMA signal, resulting in an adjacent channel leakage power ratio lower than -57 dBc with corresponding average PAE of 50% and 40% at 1.2 and 2.3 GHz, respectively. This is, to the authors' knowledge, the most wideband OPBO efficiency enhanced PA reported to date, proving the effectiveness of employing linear multi-harmonic analysis in dual-input PA design.
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| 2. |
- Chani Cahuana, Jessica, 1988, et al.
(författare)
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A new variant of the indirect learning architecture for the linearization of power amplifiers
- 2015
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Ingår i: 2015 European Microwave Conference (EuMIC). - 9782874870408 ; , s. 444-447
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Konferensbidrag (refereegranskat)abstract
- The indirect learning architecture (ILA) is the most commonly used technique for the identification of digital pre-distorters for power amplifiers (PA). A critical issue in ILA is the selection of the normalization gain used to synthesize the predistorter function. In this paper, we investigate the effects that the normalization gain has on the average output power and linearity of PAs. Moreover, we propose a new variant of the ILA that eliminates the need of a normalization gain inside the iterative loop. Experimental results show that the selection of the normalization gain affects the average output power and consequently the linearity performance of the linearized PA. If the normalization gain is not chosen correctly, the average output power of the linearized PA will differ from the average output power obtained before DPD. It is experimentally shown that the proposed ILA variant can maintain the same average output power before and after DPD. Consequently the proposed ILA variant simplifies the linearization process and allows proper evaluation of the DPD performance.
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| 3. |
- Chani Cahuana, Jessica, 1988
(författare)
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Digital Compensation Techniques for Power Amplifiers in Radio Transmitters
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Power amplifiers (PAs) are vital components in radio transmitters because they are responsible to amplify the low power communication signals to power levels suitable for transmission. Important requirements of PAs are high efficiency and linearity. Unfortunately, there is a tradeoff between efficiency and linearity. In order to satisfy both requirements, designers prefer to prioritize the efficiency in the design process while the linearity is taken care of later using external linearization techniques. Among the linearization techniques proposed in the literature, digital predistortion (DPD) has drawn a large attention of the industrial and academic sectors because it can provide a good compromise between linearity, implementation complexity and efficiency. This thesis treats different aspects related to the compensation of PA nonlinear distortion through DPD.One issue in the synthesis of DPD is that the optimal output from a predistorter is unknown. To overcome this problem, the concept of iterative learning control (ILC) for the linearization of PAs is introduced. An ILC scheme is derived that is able to identify the optimal predistorted signal that linearizes a PA. Based on the ILC framework, a novel approach to derive model structures for digital predistorters is proposed.Techniques to identify the parameters of digital predistorters have been developed. Three parameter identification techniques based on ILC have been proposed: an offline technique that can be used for research purposes to select proper models for predistorters, an adaptive technique that is able to achieve better performance than conventional identification techniques used in DPD, and an identification technique that allows us to estimate the predistorter parameter using only one of the in-phase/quadrature (IQ) components of the PA output signal. The issue of gain normalization in ILA has been investigated. A variant to ILA that eliminates the need for a normalization gain and simplifies the DPD synthesis is proposed.Performance limits on PA linearization has also been investigated and an expression for the lower bound for the normalized mean square error (NMSE) performance has been derived.The improved linearity performance achieved through the techniques developed in this thesis can enable a better utilization of the potential performance of existing and emerging highly efficiency PAs, and are therefore expected to have an impact in future wireless communication systems.
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| 4. |
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| 5. |
- Chani Cahuana, Jessica, 1988
(författare)
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Digital Predistortion for the Linearization of Power Amplifiers
- 2015
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- High efficiency and linearity are indispensable requirements of power amplifiers. Unfortunately they are difficult to obtain simultaneously, since high efficiency PAs are nonlinear and linear PAs may have low efficiency. In order to satisfy the efficiency and linearity requirements, designers preferred to prioritize the efficiency of PAs in the design process and to later recover the linearity using external linearization techniques or architectures. Among the linearization techniques proposed in the literature, digital predistortion (DPD) has drawn the most attention of the industrial and academic sectors because it can provide a good compromise between linearity performance and implementation complexity. This thesis investigates digital predistortion techniques to suppress nonlinear distortion in radio transmitters.The first part of this thesis provides a short introduction to the behavioral modeling of PAs, which includes a review of the most commonly known behavioral models, parameter estimation techniques, and performance evaluation criteria.The second part provides an introduction to digital predistortion linearization and reviews different parameter identification techniques for digital predistorters. A variant to the indirect learning architecture (ILA), which is the most commonly used parameter identification technique, is proposed to simplify the DPD synthesis. The concept of iterative learning control (ILC) for the linearization of PAs is introduced and a new parameter identification technique based on ILC is proposed.The third and final part of this thesis focuses on the linearization of dual-input transmitter architectures. Such architectures, which are currently attracting large research interest in the PA hardware community can offer greater efficiency and linearity than conventional PAs. The varactor-based dynamic load modulation PA architecture and dual-input Doherty PAs are discussed. A review of different linearization schemes especially designed for these kind of architectures is presented. Finally the linearization of dual-input Doherty PAs is discussed and a new linearization scheme that provides better linearity performance than existing schemes has been proposed.The improved linearity performance achieved through the techniques and methods developed in this thesis can enable a better utilization of the potential performance of existing and emerging highly efficiency PAs, and are therefore expected to have an impact in future wireless communication systems.
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| 6. |
- Chani Cahuana, Jessica, 1988, et al.
(författare)
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Digital Predistortion Parameter Identification for RF Power Amplifiers Using Real-Valued Output Data
- 2017
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Ingår i: IEEE Transactions on Circuits and Systems II: Express Briefs. - 1549-7747 .- 1558-3791. ; 64:10, s. 1227-1231
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Tidskriftsartikel (refereegranskat)abstract
- This brief presents a novel digital predistortion (DPD) parameter identification technique that requires only the acquisition of either the in-phase (I) or the quadrature (Q) component of the power amplifier (PA) output signal. To this end, an approach that allows us to estimate the parameters of a model using only one of the IQ components of the model output is presented. Based on experimental results, it is shown that the proposed real-valued measurements based technique can offer similar linearization capabilities as its complex-valued counterparts. The experimental results also indicate that the proposed technique can be used in combination with other techniques that focus on reducing the speed of analog-to-digital converters (ADCs)
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| 7. |
- Chani Cahuana, Jessica, 1988, et al.
(författare)
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Iterative Learning Control for RF Power Amplifier Linearization
- 2016
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Ingår i: IEEE Transactions on Microwave Theory and Techniques. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9480 .- 1557-9670. ; 64:9, s. 2778-2789
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Tidskriftsartikel (refereegranskat)abstract
- This paper proposes a new technique to identify the parameters of a digital predistorter based on iterative learning control (ILC). ILC is a well-established control theory technique that can obtain the inverse of a system. Instead of focusing on identifying the predistorter parameters, the technique proposed here first uses an iterative learning algorithm to identify the optimal power amplifier (PA) input signal that drives the PA to the desired linear output response. Once the optimal PA input signal is identified, the parameters of the predistorter are estimated using standard modeling approaches, e.g., least squares. To this end, in this paper, we present a complete derivation of an ILC scheme suitable for the linearization of PAs, which includes convergence conditions and the derivation of two learning algorithms. The proposed ILC scheme and parameter identification technique were demonstrated experimentally and compared with the indirect learning architecture (ILA) and direct learning architecture (DLA). The experimental results show that, even for the most difficult cases, the proposed ILC scheme can successfully linearize the PA. The experimental results also indicate that the proposed parameter identification technique is more robust to measurement noise than ILA and can provide better linearity performance when the PA nonlinearities are strong. In addition, the proposed parameter identification technique can achieve similar or better linearity performance than DLA but with a simpler identification process.
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| 8. |
- Chani Cahuana, Jessica, 1988, et al.
(författare)
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Linearization of dual-input Doherty power amplifiers
- 2014
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Ingår i: International Workshop on Integrated Nonlinear Microwave and Millimetre-Wave Circuits, INMMiC 2014. ; , s. Art. no. 6815085-
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Konferensbidrag (refereegranskat)abstract
- This paper studies the linearity of dual-input Doherty power amplifiers. We propose a linearization scheme that uses a combination of an efficiency-optimized static splitter and a vector-switched digital predistorter. The performance of the proposed linearization scheme is evaluated on a dual-input Doherty power amplifier operating at 2.0 GHz with 42 dBm peak output power. Experimental results show that the proposed linearization scheme achieves a normalized mean square error of-43.7 dB and an adjacent channel power ratio of-55.8 dBc with a power added efficiency of 42.4%.
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| 9. |
- Chani Cahuana, Jessica, 1988, et al.
(författare)
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Lower Bound for the Normalized Mean Square Error in Power Amplifier Linearization
- 2018
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Ingår i: IEEE Microwave and Wireless Components Letters. - 1558-1764 .- 1531-1309. ; 28:5, s. 425-427
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Tidskriftsartikel (refereegranskat)abstract
- The normalized mean square error (NMSE) is a performance criteria commonly used in power amplifier (PA) linearization to quantify the amount of in-band distortion encountered at the output of a PA. This letter presents a closed-form expression for the minimum NMSE that could be obtained in a linearization scenario. The derived expression is verified through numerical simulations and is used to compare the performance of different digital predistortion linearization schemes proposed in the literature.
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| 10. |
- Chani Cahuana, Jessica, 1988, et al.
(författare)
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Structured Digital Predistorter Model Derivation Based on Iterative Learning Control
- 2016
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Ingår i: 2016 46th European Microwave Conference. - 2325-0305. - 9782874870439 ; , s. 178-181
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Konferensbidrag (refereegranskat)abstract
- A novel approach to derive model structures for digital predistorters based on iterative learning control (ILC) is presented. ILC is a technique used to identify the optimal PA input signal/predistorted signal that drives a PA to a desired output response. The ILC concept is used to derive an analytical expression of the predistorted signal and to identify basis functions for predistorter models. The proposed approach is used to derive a predistorter model structure from the memory polynomial model. Experimental results show that the predistorter model derived with the proposed approach can obtain better linearity performance than conventional models used in digital predistortion.
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