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Mostrando ítems 1-5 de 5
Artículo
On the Optimum Number of Coefficients of Sparse Digital Predistorters: A Bayesian Approach
(IEEE, 2020-12)
This work presents insights on the application of the Bayesian information criterion (BIC) to fix the optimum number of coefficients in the Volterra series applied to the modeling and linearization of power amplifiers ...
Artículo
A Doubly Orthogonal Matching Pursuit Algorithm for Sparse Predistortion of Power Amplifiers
(IEEE, 2018-08)
This letter presents a new method for the digital predistortion (DPD) of power amplifiers (PAs) based on sparse behavioral models. The Gram-Schmidt orthogonalization is synergistically integrated into the orthogonal matching ...
Artículo
Sparse identification of volterra models for power amplifiers without pseudoinverse computation
(Institute of Electrical and Electronics Engineers Inc., 2021)
We present a new formulation of the doubly orthogonal matching pursuit (DOMP) algorithm for the sparse recovery of Volterra series models. The proposal works over the covariance matrices by taking advantage of the orthogonal ...
Artículo
An Upgraded Dual-Band Digital Predistorter Model for Power Amplifiers Linearization
(IEEE, 2021-01)
Digital predistortion (DPD) based on Volterra models is commonly employed to counteract the nonlinear distortion of power amplifiers. However, when concurrent dual-band signals are transmitted, 2-D DPD models are required. ...
Artículo
Transmitter Linearization Adaptable to Power-Varying Operation
(IEEE, 2017-10)
This paper presents the design of a power-scalable digital predistorter (DPD) for transmitter architectures. The target is to accomplish the joint compensation of impairments due to the I/Q modulator and nonlinearities ...