A digital predistorted class-F power amplifier （PA） using Cree GaN HEMT CGH40010 operating at 2. 12 GHz is presented to obtain high efficiency and excellent linearity for wideband code-division multiple access （ WC...A digital predistorted class-F power amplifier （PA） using Cree GaN HEMT CGH40010 operating at 2. 12 GHz is presented to obtain high efficiency and excellent linearity for wideband code-division multiple access （ WCDMA ） applications. Measurement results with the continuous wave （CW） signals indicate that the designed class-F PA achieves a peak power-added efficiency （PAE） of 75. 2% with an output power of 39.4 dBm. The adjacent channel power ratio （ACPR） of the designed PA after digital predistortion （DPD） decreases from -28. 3 and -27. 5 dBc to -51.9 and -54. 0 dBc, respectively, for a 4-carrier 20 MHz WCDMA signal with 7. 1 dB peak to average power ratio （PAPR）. The drain efficiency （DE） of the PA is 37. 8% at an average output power of 33. 3 dBm. The designed power amplifier can be aoolied in the WCDMA system.展开更多
This paper presents a dual-nonlinear branch linearizer for reducing the corrected amplitude overshoot of conventional single nonlinear branch linearizer. Theoretical analysis is carried out, the analysis is verified b...This paper presents a dual-nonlinear branch linearizer for reducing the corrected amplitude overshoot of conventional single nonlinear branch linearizer. Theoretical analysis is carried out, the analysis is verified by simulation, and a prototype of Ka band 25.28~26.08 GHz dual nonlinear branch linearizer is achieved. It indicates that the corrected amplitude overshoot is less than 0.5 dB, the C/I3 improvement is more than 10 dB related to a single carrier IBO 9 dB, when it is linked and tested for 50 W spacebrone Travelling Wave Tube Amplifier(TWTA).展开更多
To compensate for nonlinear distortion introduced by RF power amplifiers （PAs） with memory effects, two correlated models, namely an extended memory polynomial （EMP） model and a memory lookup table （LUT） model, ...To compensate for nonlinear distortion introduced by RF power amplifiers （PAs） with memory effects, two correlated models, namely an extended memory polynomial （EMP） model and a memory lookup table （LUT） model, are proposed for predistorter design. Two adaptive digital predistortion （ADPD） schemes with indirect learning architecture are presented. One adopts the EMP model and the recursive least square （RLS） algorithm, and the other utilizes the memory LUT model and the least mean square （LMS） algorithm. Simulation results demonstrate that the EMP-based ADPD yields the best linearization performance in terms of suppressing spectral regrowth. It is also shown that the ADPD based on memory LUT makes optimum tradeoff between performance and computational complexity.展开更多
RF power amplifiers (PAs) are usually considered as memoryless devices in most existing predistortion techniques. Nevertheless, in wideband communication systems, PA memory effects can no longer be ignored and memoryl...RF power amplifiers (PAs) are usually considered as memoryless devices in most existing predistortion techniques. Nevertheless, in wideband communication systems, PA memory effects can no longer be ignored and memoryless predistortion cannot linearize PAs effectively. After analyzing PA memory effects, a novel predistortion method based on wavelet networks (WNs) is proposed to linearize wideband RF power amplifiers. A complex wavelet network with tapped delay lines is applied to construct the predistorter and then a complex backpropagation algorithm is developed to train the predistorter parameters. The simulation results show that compared with the previously published feed-forward neural network predistortion method, the proposed method provides faster convergence rate and better performance in reducing out-of-band spectral regrowth.展开更多
A robust digital predistortion(DPD)technique utilizing negative feedback iteration is introduced for linearizing power amplifiers(PAs)in long term evolution(LTE)/5G systems.Different from the conventional direct learn...A robust digital predistortion(DPD)technique utilizing negative feedback iteration is introduced for linearizing power amplifiers(PAs)in long term evolution(LTE)/5G systems.Different from the conventional direct learning and indirect learning structure,the proposed DPD suggests a two-step method to identify the predistortion.Firstly,a negative feedback based iteration is used to estimate the optimal DPD signal.Then the corresponding DPD parameters are extracted by forward modeling with the input signal and optimal DPD signal.The iteration can be applied to both single-band and dual-band PAs,which will achieve superior linear performance than the conventional direct learning DPD while having a relatively low computational complexity.The measurement is carried out on a broadband Doherty PA(DPA)with a 200 MHz bandwidth LTE signal at 2.1 GHz,and on a 5G DPA with two 10 MHz LTE signals at 3.4/3.6 GHz for validation in dual-band scenarios.展开更多
RF power amplifiers （PAs） are usually considered as memoryless devices in most existing predistortion techniques. However, in broadband communication systems, such as WCDMA, the PA memory effects are significant, an...RF power amplifiers （PAs） are usually considered as memoryless devices in most existing predistortion techniques. However, in broadband communication systems, such as WCDMA, the PA memory effects are significant, and memoryless predistortion cannot linearize the PAs effectively. After analyzing the PA memory effects, a novel predistortion method based on the simplified Volterra series is proposed to linearize broadband RF PAs with memory effects. The indirect learning architecture is adopted to design the predistortion scheme and the reeursive least squares algorithm with forgetting factor is applied to identify the parameters of the predistorter. Simulation results show that the proposed predistortion method can compensate the nonlinear distortion and memory effects of broadband RF PAs effectively.展开更多
Digital PreDistortion(DPD)is a very useful method to improve the linearity of Power Amplifiers(PAs)for LTE and upcoming 5 G networks.As the spectrum resources are becoming more and more crowded,and the communications ...Digital PreDistortion(DPD)is a very useful method to improve the linearity of Power Amplifiers(PAs)for LTE and upcoming 5 G networks.As the spectrum resources are becoming more and more crowded,and the communications bandwidth are broader,the ACPR(Adjacent Channel Leakage Ratio)is very important to communication systems.DPD is one of the useful means for PA to reduce ACPR.This article demonstrates what DPD is and how DPD is achieved,the measurement of the Digital Distortion of a PA using a vector generator and vector analyzer,and the measurement results has been discussed.展开更多
At present what are the key points focused in the research of loop-delay estimation for the digital predistorter in the radio frequency （RF） power amplifier system is reducing its complexity of engineering realizati...At present what are the key points focused in the research of loop-delay estimation for the digital predistorter in the radio frequency （RF） power amplifier system is reducing its complexity of engineering realization and improving anti-jamming ability and computational speed. Besides, opening up its application scope should be contained. For these targets, a novel method including integer loop delay estimation and fractional part is proposed. The integer part applies amplitude-difference summation function and the fractional one adopts the method of finite impulse response （FIR） linear interpolation. The algorithm finds wide applications. What is more, strong anti-jamming ability and low complexity are also its merits. Simulation results support the above opinion. Digital predistortion （DPD） system based on this algorithm achieves good performance.展开更多
This paper proposes that a radio frequency power amplifier is suitable for a 5G millimeter wave.It adopts a three-stage single-ended structure at 28GHz.An analog predistortion lmearization method is used to improve th...This paper proposes that a radio frequency power amplifier is suitable for a 5G millimeter wave.It adopts a three-stage single-ended structure at 28GHz.An analog predistortion lmearization method is used to improve the linearity of the power amplifier(PA).As a result,there is a significant improvement in power-added efficiency(PAE)and linearity is achieved.The Ka-band PA is implemented in TSMC 65nm CMOS process.At 1.2V supply voltage,the PA proposed in this paper achieves a saturated output power of 15.9dBm and a PAE of 16%.After linearization,the output power at the ldB compression point is increased by 2dBm,with efficient gain compensation performance.展开更多
Plug-in Hybrid Electric Vehicles(PHEVs)represent an innovative breed of transportation,harnessing diverse power sources for enhanced performance.Energy management strategies(EMSs)that coordinate and control different ...Plug-in Hybrid Electric Vehicles(PHEVs)represent an innovative breed of transportation,harnessing diverse power sources for enhanced performance.Energy management strategies(EMSs)that coordinate and control different energy sources is a critical component of PHEV control technology,directly impacting overall vehicle performance.This study proposes an improved deep reinforcement learning(DRL)-based EMSthat optimizes realtime energy allocation and coordinates the operation of multiple power sources.Conventional DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action spaces.They often fail to strike an optimal balance between exploration and exploitation,and their assumption of a static environment limits their ability to adapt to changing conditions.Moreover,these algorithms suffer from low sample efficiency.Collectively,these factors contribute to convergence difficulties,low learning efficiency,and instability.To address these challenges,the Deep Deterministic Policy Gradient(DDPG)algorithm is enhanced using entropy regularization and a summation tree-based Prioritized Experience Replay(PER)method,aiming to improve exploration performance and learning efficiency from experience samples.Additionally,the correspondingMarkovDecision Process(MDP)is established.Finally,an EMSbased on the improvedDRLmodel is presented.Comparative simulation experiments are conducted against rule-based,optimization-based,andDRL-based EMSs.The proposed strategy exhibitsminimal deviation fromthe optimal solution obtained by the dynamic programming(DP)strategy that requires global information.In the typical driving scenarios based onWorld Light Vehicle Test Cycle(WLTC)and New European Driving Cycle(NEDC),the proposed method achieved a fuel consumption of 2698.65 g and an Equivalent Fuel Consumption(EFC)of 2696.77 g.Compared to the DP strategy baseline,the proposed method improved the fuel efficiency variances(FEV)by 18.13%,15.1%,and 8.37%over the Deep QNetwork(DQN),Double DRL(DDRL),and original DDPG methods,respectively.The observational outcomes demonstrate that the proposed EMS based on improved DRL framework possesses good real-time performance,stability,and reliability,effectively optimizing vehicle economy and fuel consumption.展开更多
To reduce the number of digital predistortion coefficients, a step memory polynomial （SMP）predistorter is presented. The number of predistortion coefficients is decreased by adjusting the maximum nonlinear order for...To reduce the number of digital predistortion coefficients, a step memory polynomial （SMP）predistorter is presented. The number of predistortion coefficients is decreased by adjusting the maximum nonlinear order for different memory orders in the traditional memory polynomial （MP）predistorter. The proposed SNIP predistorter is identified by an offline learning structure on which the coefficients can be extracted directly from the sampled input and output of a PA. Simulation results show that the SMP predistorter is not tied to a particular PA model and is, therefore, robust. The effectiveness of the SMP predistorter is demonstrated by simulations and experiments on an MP model, a parallel Wiener model, a Wiener-Hammerstein model, a sparsedelay memory polynomial model and a real PA which is fabricated based on the Freescale LDMOSFET MRF21030. Compared with the traditional MP predistorter, the SMP predistorter can reduce the number of coefficients by 60%.展开更多
基金The National Natural Science Foundation of China(No.60702163)the National Science and Technology Major Project(No.2010ZX03007-002-01,2011ZX03004-003)
文摘A digital predistorted class-F power amplifier （PA） using Cree GaN HEMT CGH40010 operating at 2. 12 GHz is presented to obtain high efficiency and excellent linearity for wideband code-division multiple access （ WCDMA ） applications. Measurement results with the continuous wave （CW） signals indicate that the designed class-F PA achieves a peak power-added efficiency （PAE） of 75. 2% with an output power of 39.4 dBm. The adjacent channel power ratio （ACPR） of the designed PA after digital predistortion （DPD） decreases from -28. 3 and -27. 5 dBc to -51.9 and -54. 0 dBc, respectively, for a 4-carrier 20 MHz WCDMA signal with 7. 1 dB peak to average power ratio （PAPR）. The drain efficiency （DE） of the PA is 37. 8% at an average output power of 33. 3 dBm. The designed power amplifier can be aoolied in the WCDMA system.
文摘This paper presents a dual-nonlinear branch linearizer for reducing the corrected amplitude overshoot of conventional single nonlinear branch linearizer. Theoretical analysis is carried out, the analysis is verified by simulation, and a prototype of Ka band 25.28~26.08 GHz dual nonlinear branch linearizer is achieved. It indicates that the corrected amplitude overshoot is less than 0.5 dB, the C/I3 improvement is more than 10 dB related to a single carrier IBO 9 dB, when it is linked and tested for 50 W spacebrone Travelling Wave Tube Amplifier(TWTA).
文摘To compensate for nonlinear distortion introduced by RF power amplifiers （PAs） with memory effects, two correlated models, namely an extended memory polynomial （EMP） model and a memory lookup table （LUT） model, are proposed for predistorter design. Two adaptive digital predistortion （ADPD） schemes with indirect learning architecture are presented. One adopts the EMP model and the recursive least square （RLS） algorithm, and the other utilizes the memory LUT model and the least mean square （LMS） algorithm. Simulation results demonstrate that the EMP-based ADPD yields the best linearization performance in terms of suppressing spectral regrowth. It is also shown that the ADPD based on memory LUT makes optimum tradeoff between performance and computational complexity.
基金Project (No. 60372026) supported by the National Natural ScienceFoundation of China
文摘RF power amplifiers (PAs) are usually considered as memoryless devices in most existing predistortion techniques. Nevertheless, in wideband communication systems, PA memory effects can no longer be ignored and memoryless predistortion cannot linearize PAs effectively. After analyzing PA memory effects, a novel predistortion method based on wavelet networks (WNs) is proposed to linearize wideband RF power amplifiers. A complex wavelet network with tapped delay lines is applied to construct the predistorter and then a complex backpropagation algorithm is developed to train the predistorter parameters. The simulation results show that compared with the previously published feed-forward neural network predistortion method, the proposed method provides faster convergence rate and better performance in reducing out-of-band spectral regrowth.
基金National Key R&D Program of China under Grant No.2018YFB1801603 and No.2017YFF0206201National Sci⁃ence and Technology Major Project under Grant 2017ZX03001024,NSFC under Grant No.61801259 and Beijing National Research Center for Infor⁃mation Science and Technology(BNRist).
文摘A robust digital predistortion(DPD)technique utilizing negative feedback iteration is introduced for linearizing power amplifiers(PAs)in long term evolution(LTE)/5G systems.Different from the conventional direct learning and indirect learning structure,the proposed DPD suggests a two-step method to identify the predistortion.Firstly,a negative feedback based iteration is used to estimate the optimal DPD signal.Then the corresponding DPD parameters are extracted by forward modeling with the input signal and optimal DPD signal.The iteration can be applied to both single-band and dual-band PAs,which will achieve superior linear performance than the conventional direct learning DPD while having a relatively low computational complexity.The measurement is carried out on a broadband Doherty PA(DPA)with a 200 MHz bandwidth LTE signal at 2.1 GHz,and on a 5G DPA with two 10 MHz LTE signals at 3.4/3.6 GHz for validation in dual-band scenarios.
基金the National Natural Science Foundation of China (60671037).
文摘RF power amplifiers （PAs） are usually considered as memoryless devices in most existing predistortion techniques. However, in broadband communication systems, such as WCDMA, the PA memory effects are significant, and memoryless predistortion cannot linearize the PAs effectively. After analyzing the PA memory effects, a novel predistortion method based on the simplified Volterra series is proposed to linearize broadband RF PAs with memory effects. The indirect learning architecture is adopted to design the predistortion scheme and the reeursive least squares algorithm with forgetting factor is applied to identify the parameters of the predistorter. Simulation results show that the proposed predistortion method can compensate the nonlinear distortion and memory effects of broadband RF PAs effectively.
基金supported by Shenzhen Strategic Emerging Industry Development Fund Project——Public service platform for 5G key components testing(20170921165224440)
文摘Digital PreDistortion(DPD)is a very useful method to improve the linearity of Power Amplifiers(PAs)for LTE and upcoming 5 G networks.As the spectrum resources are becoming more and more crowded,and the communications bandwidth are broader,the ACPR(Adjacent Channel Leakage Ratio)is very important to communication systems.DPD is one of the useful means for PA to reduce ACPR.This article demonstrates what DPD is and how DPD is achieved,the measurement of the Digital Distortion of a PA using a vector generator and vector analyzer,and the measurement results has been discussed.
基金supported by the Circuit and System Foremost Discipline of Zhejiang Province under Grant No. ZZ050103-11
文摘At present what are the key points focused in the research of loop-delay estimation for the digital predistorter in the radio frequency （RF） power amplifier system is reducing its complexity of engineering realization and improving anti-jamming ability and computational speed. Besides, opening up its application scope should be contained. For these targets, a novel method including integer loop delay estimation and fractional part is proposed. The integer part applies amplitude-difference summation function and the fractional one adopts the method of finite impulse response （FIR） linear interpolation. The algorithm finds wide applications. What is more, strong anti-jamming ability and low complexity are also its merits. Simulation results support the above opinion. Digital predistortion （DPD） system based on this algorithm achieves good performance.
文摘This paper proposes that a radio frequency power amplifier is suitable for a 5G millimeter wave.It adopts a three-stage single-ended structure at 28GHz.An analog predistortion lmearization method is used to improve the linearity of the power amplifier(PA).As a result,there is a significant improvement in power-added efficiency(PAE)and linearity is achieved.The Ka-band PA is implemented in TSMC 65nm CMOS process.At 1.2V supply voltage,the PA proposed in this paper achieves a saturated output power of 15.9dBm and a PAE of 16%.After linearization,the output power at the ldB compression point is increased by 2dBm,with efficient gain compensation performance.
文摘Plug-in Hybrid Electric Vehicles(PHEVs)represent an innovative breed of transportation,harnessing diverse power sources for enhanced performance.Energy management strategies(EMSs)that coordinate and control different energy sources is a critical component of PHEV control technology,directly impacting overall vehicle performance.This study proposes an improved deep reinforcement learning(DRL)-based EMSthat optimizes realtime energy allocation and coordinates the operation of multiple power sources.Conventional DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action spaces.They often fail to strike an optimal balance between exploration and exploitation,and their assumption of a static environment limits their ability to adapt to changing conditions.Moreover,these algorithms suffer from low sample efficiency.Collectively,these factors contribute to convergence difficulties,low learning efficiency,and instability.To address these challenges,the Deep Deterministic Policy Gradient(DDPG)algorithm is enhanced using entropy regularization and a summation tree-based Prioritized Experience Replay(PER)method,aiming to improve exploration performance and learning efficiency from experience samples.Additionally,the correspondingMarkovDecision Process(MDP)is established.Finally,an EMSbased on the improvedDRLmodel is presented.Comparative simulation experiments are conducted against rule-based,optimization-based,andDRL-based EMSs.The proposed strategy exhibitsminimal deviation fromthe optimal solution obtained by the dynamic programming(DP)strategy that requires global information.In the typical driving scenarios based onWorld Light Vehicle Test Cycle(WLTC)and New European Driving Cycle(NEDC),the proposed method achieved a fuel consumption of 2698.65 g and an Equivalent Fuel Consumption(EFC)of 2696.77 g.Compared to the DP strategy baseline,the proposed method improved the fuel efficiency variances(FEV)by 18.13%,15.1%,and 8.37%over the Deep QNetwork(DQN),Double DRL(DDRL),and original DDPG methods,respectively.The observational outcomes demonstrate that the proposed EMS based on improved DRL framework possesses good real-time performance,stability,and reliability,effectively optimizing vehicle economy and fuel consumption.
基金The National High Technology Research and Development Program of China (863 Program) (No.2008AA01Z211)the Project of Industry-Academia-Research Demonstration Base of Education Ministry of Guangdong Province (No.2007B090200012)
文摘To reduce the number of digital predistortion coefficients, a step memory polynomial （SMP）predistorter is presented. The number of predistortion coefficients is decreased by adjusting the maximum nonlinear order for different memory orders in the traditional memory polynomial （MP）predistorter. The proposed SNIP predistorter is identified by an offline learning structure on which the coefficients can be extracted directly from the sampled input and output of a PA. Simulation results show that the SMP predistorter is not tied to a particular PA model and is, therefore, robust. The effectiveness of the SMP predistorter is demonstrated by simulations and experiments on an MP model, a parallel Wiener model, a Wiener-Hammerstein model, a sparsedelay memory polynomial model and a real PA which is fabricated based on the Freescale LDMOSFET MRF21030. Compared with the traditional MP predistorter, the SMP predistorter can reduce the number of coefficients by 60%.
