An Adaptive Fuzzy Logic System for the Compensation of Nonlinear Distortion in Wireless Power Amplifiers
- Submitting institution
-
The University of Westminster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 9z712
- Type
- D - Journal article
- DOI
-
10.1007/s00521-017-2849-3
- Title of journal
- Neural Computing and Applications
- Article number
- -
- First page
- 2539–255
- Volume
- 30
- Issue
- 8
- ISSN
- 0941-0643
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Linearization of power amplifiers is essential, considering requirements of nowadays wireless communication systems. Although linearization can be achieved in various ways, this paper, influenced by the control theory, adopted the principle of an inverse model. The significance of this paper is the development of a neurofuzzy inverse model, using a novel defuzzification technique used for power amplifier linearization with digital pre-distortion. Experimental results revealed a clear advantage over neural networks, currently used as a state of the art method, indicating thus the potential of introducing such hybrid schemes in this challenging, in significance, technological area.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
