Abstract
Power amplifiers in a communication system are inherently nonlinear.
Digital predistorters can compensate these nonlinearity effects. In this
paper, two memory polynomial predistorters including direct and indirect
learning architectures are compared with each other. To the best of our
knowledge, no similar comparisons have been published. Both of these
architectures are special cases of the self-tuning control. We have modeled
predistorters and analysed nonlinear effects of a power amplifier and their
digital compensation by using Matlab. Simulation results show that the memory
polynomial model has convergence problems at large amplitudes and also
problems of accuracy of representation. We observed that the results of the
compensation depend also on the amplitude, not only on the frequency. The
results of the linearisation show that the direct learning architecture
achieves a better performance in almost all cases.
| Original language | English |
|---|---|
| Title of host publication | 2008 IEEE International Symposium on Wireless Communication Systems |
| Publisher | IEEE Institute of Electrical and Electronic Engineers |
| Pages | 309-313 |
| ISBN (Electronic) | 978-1-4244-2489-4 |
| ISBN (Print) | 978-1-4244-2488-7 |
| Publication status | Published - 30 Dec 2008 |
| MoE publication type | A4 Article in a conference publication |
Keywords
- predistortion
- power amplifier
- constellation diagram
- polynomials
- nonlinear distortion
- quadrature amplitude modulation