Prediction of the Optimal Phase Shift between Control Signals in Dual-Input Power Amplifiers

Guillena, Estefania; Li, Wantao; Gilabert, Pere L.; Montoro, Gabriel

doi:10.1109/inmmic46721.2020.9160227

Cited by 4 publications

(15 citation statements)

References 3 publications

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“…In this paper, the LMBA presented in [ 5 ] is used as device-under-test (DUT), as in [ 20 ]. Its block diagram is shown in Figure 2 .…”

Section: Multiple-input Power Amplifier Architecturesmentioning

confidence: 99%

“…As will be described in the following, with one of the parameters it is possible to prevent the signal from dropping to zero, while with the other it is possible to control the shape of input–output characteristic. In particular, following the same approach as in [ 20 ], the CSP signal

is defined as

where

is the relative phase between the BPA and the CSP signals; and the signal after the shaping function

is described as follows,

with

and where the amplitude relation between the main and control signals is determined as follows,

with p being the degree of the root (

root), and the lower bound

is defined as

where

is the offset percentage, defining the threshold for the detroughing function. The input–output characteristics of the shaping function when sweeping the parameters

and p are depicted in Figure 4 c,d.…”

Section: Description Of the Dual-input Pa Auto-tuning Approachmentioning

confidence: 99%

“…Machine learning strategies were applied to a dual-input Doherty PA in [ 11 ] to optimize configuration parameters, such as: bias voltages, input signal phases, and power splitting ratios taking into account a user-defined cost function. Particularizing now for dual-input LMBAs, the effect on linearity of certain configuration parameters (while trying to keep power efficiency values as high as possible) are explored in [ 20 , 21 ]. In [ 20 ], for example, a method for predicting the optimum (in terms of linearity) relative phase shift between the two input modulated signals to the LMBA was proposed, assuming certain fixed values for the rest of the free-parameters influencing the linearity versus power efficiency trade-off.…”

Section: Introductionmentioning

confidence: 99%

“…Particularizing now for dual-input LMBAs, the effect on linearity of certain configuration parameters (while trying to keep power efficiency values as high as possible) are explored in [ 20 , 21 ]. In [ 20 ], for example, a method for predicting the optimum (in terms of linearity) relative phase shift between the two input modulated signals to the LMBA was proposed, assuming certain fixed values for the rest of the free-parameters influencing the linearity versus power efficiency trade-off. Moreover, although the linearisation of LMBAs has been already addressed in the literature, e.g., [ 18 , 22 ], only modulated signals with moderate bandwidths (i.e., several tenths of MHz) have been considered.…”

Section: Introductionmentioning

confidence: 99%

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Machine-Learning Assisted Optimisation of Free-Parameters of a Dual-Input Power Amplifier for Wideband Applications

Wang

Quaglia

et al. 2021

Sensors

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This paper presents an auto-tuning approach for dual-input power amplifiers using a combination of global optimisation search algorithms and adaptive linearisation in the optimisation of a multiple-input power amplifier. The objective is to exploit the extra degrees of freedom provided by dual-input topologies to enhance the power efficiency figures along wide signal bandwidths and high peak-to-average power ratio values, while being compliant with the linearity requirements. By using heuristic search global optimisation algorithms, such as the simulated annealing or the adaptive Lipschitz Optimisation, it is possible to find the best parameter configuration for PA biasing, signal calibration, and digital predistortion linearisation to help mitigating the inherent trade-off between linearity and power efficiency. Experimental results using a load-modulated balanced amplifier as device-under-test showed that after properly tuning the selected free-parameters it was possible to maximise the power efficiency when considering long-term evolution signals with different bandwidths. For example, a carrier aggregated a long-term evolution signal with up to 200 MHz instantaneous bandwidth and a peak-to-average power ratio greater than 10 dB, and was amplified with a mean output power around 33 dBm and 22.2% of mean power efficiency while meeting the in-band (error vector magnitude lower than 1%) and out-of-band (adjacent channel leakage ratio lower than −45 dBc) linearity requirements.

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“…In this paper, the LMBA presented in [ 5 ] is used as device-under-test (DUT), as in [ 20 ]. Its block diagram is shown in Figure 2 .…”

Section: Multiple-input Power Amplifier Architecturesmentioning

confidence: 99%

is defined as

where

is the relative phase between the BPA and the CSP signals; and the signal after the shaping function

is described as follows,

with

and where the amplitude relation between the main and control signals is determined as follows,

with p being the degree of the root (

root), and the lower bound

is defined as

where

is the offset percentage, defining the threshold for the detroughing function. The input–output characteristics of the shaping function when sweeping the parameters

and p are depicted in Figure 4 c,d.…”

Section: Description Of the Dual-input Pa Auto-tuning Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Machine-Learning Assisted Optimisation of Free-Parameters of a Dual-Input Power Amplifier for Wideband Applications

Wang

Quaglia

et al. 2021

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…Therefore, the additional degrees of freedom offered by the separate inputs can be used to optimize the performance on the same or larger bandwidth, or to improve other performance metrics such as linearity and average efficiency. In [8], for example, the authors propose the use of machine learning techniques to optimize the configuration parameters of a dualinput Doherty PA. Particularizing for dual-input LMBAs, the configuration of certain key free-parameters influencing the inherent linearity versus power efficiency trade-off is explored in [9], [10]. Among the different degrees of freedom that can be considered to optimize the LMBA performance, in [9] the authors proposed a method for predicting the optimum relative phase shift between the two input modulated signals to the LMBA that maximize linearity levels.…”

Section: Introductionmentioning

confidence: 99%

Reconfigurable DPD Based on ANNs for Wideband Load Modulated Balanced Amplifiers Under Dynamic Operation From 1.8 to 2.4 GHz

Guillena

Montoro

et al. 2022

IEEE Trans. Microwave Theory Techn.

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This paper proposes a methodology to ensure linear amplification of a load modulated balanced amplifier (LMBA) while keeping the power efficiency as high as possible over a frequency band ranging from 1.8 to 2.4 GHz and where the transmitted signals can present different bandwidth configurations. The proposed reconfigurable linearization methodology consists of, in a first step, tuning some free-parameters (with dependence on the signal bandwidth and frequency of operation) of the load modulated balanced amplifier (LMBA) to trade-off linearity and power efficiency. In a second step, two multi-purpose adaptive digital predistortion (DPD) linearizers are considered, properly combined with crest factor reduction (CFR) techniques, to meet the required linearity specifications. Either a DPD based on artificial neural networks or a DPD based on polynomials can be selected taking into account the compromise between computational complexity and linearization performance. Experimental results will validate the proposed methodology to guarantee the linearity levels (ACPR<-45 dBc and EVM<1%) with high power efficiency in an LMBA under dynamic transmission, where both the signal bandwidth (from 20 MHz and up to 200 MHz instantaneous bandwidth) and frequency of operation (in the range of 1.8 to 2.4 GHz) change.Index Terms-artificial neural network (ANN), digital predistortion (DPD), load-modulated balanced amplifiers (LMBA), power efficiency.

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Load Modulated Balanced Amplifier Design Method Based on Complex Impedance Trajectories

et al. 2022

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This paper presents a design methodology for a load modulated balanced amplifier (LMBA) focusing on AMPM distortion mitigation. By introducing second harmonic control as a degree of design freedom, a complex load trajectory can be selected to compensate for AMPM nonlinearities in the device without substantially affecting efficiency. A mathematical derivation is accompanied by a design procedure based on closed-form equations to fabricate an LMBA based solely on load-pull data. The theory is validated through the measured comparison of three different designs operating at 2.4 GHz in a pseudo-RF-input Doherty-like LMBA configuration, with class-J, -B, and -J* main PAs. The class-J prototype outperforms the other designs with 54% and 49% drain efficiency at peak output power and 6-dB back-off, respectively, and only 4 degrees of AM-PM across this power range. When driven with a 10-MHz, 8.6-dB PAPR LTE signal, 40.5% average efficiency is achieved with better than −40.5 dBc ACLR without digital predistortion.INDEX TERMS Class J, Doherty power amplifier, gallium nitride, load modulated balanced amplifier, power amplifiers.This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.

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Prediction of the Optimal Phase Shift between Control Signals in Dual-Input Power Amplifiers

Cited by 4 publications

References 3 publications

Machine-Learning Assisted Optimisation of Free-Parameters of a Dual-Input Power Amplifier for Wideband Applications

Machine-Learning Assisted Optimisation of Free-Parameters of a Dual-Input Power Amplifier for Wideband Applications

Reconfigurable DPD Based on ANNs for Wideband Load Modulated Balanced Amplifiers Under Dynamic Operation From 1.8 to 2.4 GHz

Load Modulated Balanced Amplifier Design Method Based on Complex Impedance Trajectories

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