NEW IDENTIFICATION PROCEDURE FOR CONTINUOUS-TIME RADIO FREQUENCY POWER AMPLIFIER MODEL

International audienceIn this paper, we present a new method for characterization of radio frequency Power Amplifier (PA) in the presence of nonlinear distortions which affect the modulated signal in Radiocommunication transmission system. The proposed procedure uses a gray box model where PA dynamics are modeled with a MIMO continuous filter and the nonlinear characteristics are described as general polynomial functions, approximated by means of Taylor series. Using the baseband input and output data, model parameters are obtained by an iterative identification algorithm based on Output Error method. Initialization and excitation problems are resolved by an association of a new technique using initial values extraction with a multi-level binary sequence input exciting all PA dynamics. Finally, the proposed estimation method is tested and validated on experimental data

Robust linearization of RF amplifiers using nonlinear internal model control method

International audienceIn the present paper, the nonlinear Internal Model Control (IMC) method is introduced and applied to linearize high frequency Power Amplifiers (PAs). The IMC is based on the description of a process model and of a controller. It is shown that baseband frequency descriptions are suitable for the model and the controller. Their description parameters are derived from input and output modulation signals processed in Cartesian form. Simulation results are given to illustrate the design procedure and to demonstrate the performances of the IMC linearizer

A power amplifier envelope distortion model using direct calculation of polynomial parameters and delay taps

International audienceThis paper presents a power amplifier (PA) cascade model, using two polynomial functions for amplitude and phase variations and multiple delay taps. This model allows an accurate modeling of the output envelope distortion and spectral asymmetries. To extract the model coefficients and delays for each non linearity order, an analytical method is developed. This method uses the Fourier transform of the output gain and phase to calculate all the parameters. To demonstrate the performances of this modeling approach, comparison between measured and simulated data has been performed

On-line memory polynomial predistortion based on the adapted kalman filtering algorithm

International audienceA new adaptive technique for digital predistortion is presented. The proposed method uses the real-time digital processing of baseband signals to compensate the nonlinearities and memory effects in radio-frequency power amplifier. Kalman filtering algorithm with sliding time-window is adapted to track the changes in the PA characteristics. Simulation and measurement results, using digital signal processing, are presented for multicarrier signals to demonstrate the effectiveness of this new approach

Mixed time and frequency-domain identification of Radio Frequency Power Amplifiers

International audienceThis paper presents a modeling and identification procedure for Radio Frequency Power Amplifier (PA) in continuous time representation. The proposed method is based on a combined approach using time and frequency domain. The microwave PA dynamics are described by the continuous Hammerstein model. The distortion function coefficients were estimated using Least Mean Squares (LMS) method that minimizes the squared error based on baseband output data. The coefficients of dynamic block are extracted using an iterative instrumental variable applied to experimental PA frequency responses. To demonstrate the feasibility of the identification method in experimental results we used a standard mobile PA at 1.85GHz

Linearization of RF Power Amplifiers Using Adaptive Kalman Filtering Algorithm

International audienceIn this paper, a new linearization algorithm of Power Amplifier, based on Kalman filtering theory is proposed for obtaining fast convergence of the adaptive digital predistortion. The proposed method uses the real-time digital processing of baseband signals to compensate the nonlinearities and memory effects in radio-frequency Power Amplifier. To reduce the complexity of computing in classical Kalman Filtering, a sliding time-window has been inserted which combines off-line measurement and on-line parameter estimation with high sampling time to track the changes in the PA characteristics. We evaluated the performance of the proposed linearization scheme through simulation and experiments. Using digital signal processing, experimental results with commercial power amplifier are presented for multicarrier signals to demonstrate the effectiveness of this new approach

Optimization of Band Pass Delta Sigma modulators using parameters identification

International audienceIn this paper, a method to study and characterize a single-loop, cascaded and 1-bit band-pass delta sigma (BPΔΣ) modulator for digital transmitter is presented. This technique is based on a combination of digital filter simulation and nonlinear optimization of signal-to-quantization noise. The optimal coefficients of BPΔΣ structure are achieved by minimization of a quadratic criterion based on prediction error between desired digital filter and noise transfer model. To demonstrate the effectiveness of this approach, simulated results for a 6th order cascaded structure for WCDMA band-1 standard are presented

Modeling and identification of continuous-time system for RF amplifiers

International audienceIn this paper, we present a new identification procedure for radio frequency power amplifier (PA) in the presence of nonlinear distortion and memory effects. The proposed procedure uses a continuous-time model where PA dynamics are modeled with a multivariable filter and a general polynomial function. Using the baseband input and output data, model parameters are obtained by an iterative identification algorithm. Finally, the proposed estimation method is tested and validated on experimental data by comparison of the quadrature IQ signals in time domain

Characterization of BandPass Delta Sigma Modulators in Wireless Transceivers Using Parameter Identification

International audienceIn this paper, a method to study and characterize a single-loop, cascaded and 1-bit Band-Pass Delta Sigma modulator for digital transmitter is presented. This technique is based on a combination of digital filter simulation and nonlinear optimization of signal-to-quantization noise. The optimal coefficients of modulator structure are achieved by minimization of a quadratic criterion based on prediction error between desired digital filter and noise transfer model. To demonstrate the effectiveness of this approach, simulated results for a sixth order cascaded structure for WCDMA Band-1 standard are presented. Spurious and ACLR improvement could be achieved for this standard with the proposed characterization technique

Kalman filtering algorithm for on-line memory polynomial predistortion

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