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Content Provider | IET Digital Library |
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Author | González, Juan Antonio Becerra Ayora, María José Madero Tosina, Javier Reina Cadenas, Carlos Crespo |
Abstract | Digital predistortion has become an attractive technique for power amplifier linearisation whose limiting factor for using Volterra series as the underlying model is its computational complexity, since the number of components rapidly grows with the non-linear order and memory. Based on a previous reference algorithm, which consists on applying the orthogonal matching pursuit for the sorting of the model components and a Bayesian information criterion for the selection of the optimum number of components, a new technique to reduce the size of the support set taking into account the structural information within a model is presented. Experimental results of the predistortion of a commercial power amplifier are given as a proof of its capabilities, showing equivalent performance to the pruning with the reference algorithm while further reducing the number of components. |
Starting Page | 89 |
Ending Page | 91 |
Page Count | 3 |
ISSN | 00135194 |
Volume Number | 53 |
e-ISSN | 1350911X |
Issue Number | Issue 2, Jan (2017) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/el/53/2 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/el.2016.3879 |
Journal | Electronics Letters |
Publisher Date | 2016-12-08 |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Amplifiers Bayes Method Bayesian Information Criterion Compressed Sensing Computational Complexity Digital Predistortion Interpolation And Function Approximation Iterative Method Limiting Factor Numerical Analysis Orthogonal Matching Pursuit Algorithm Power Amplifier Power Amplifier Linearisation Statistics Structured Compressed-sensing Volterra Series Time-frequency Analysis Volterra Series |
Content Type | Text |
Resource Type | Article |
Subject | Electrical and Electronic Engineering |
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