
doi: 10.1049/smt2.12041
Abstract The noise is an inherent part of a transceiver system, which becomes more severe on low‐cost systems. The power amplifier (PA) further enhances this noise and the signal to be propagated to the receiver. The conventional approach of digital predistortion (DPD) assumes an ideal transceiver system while extracting data for the predistortion function generation. As a result, performance limitation arises due to residual signal–noise interaction. This study presents the accuracy and implementation issues of DPD on a low‐cost transceiver having lower bit resolution in the presence of transceiver noise. Different model architectures, as well as processing algorithms, are compared in terms of numerical stability of the solution (condition number of observation matrix), efficient field‐programmable gate array (FPGA) implementation (dispersion of coefficients, in‐band model performance (normalised mean square error), and out‐of‐band model performance (adjacent channel power ratio). The simulation results are tested on FPGA and direct conversion transceiver‐based platform using PA. A long‐term evolution signal with 64 quadrature amplitude modulation is used for performance evaluation. The suitability of the various polynomial models for fixed‐point implementation and the required memory size for implementing the DPD model is further established.
Modulation and coding methods, Mobile radio systems, Interpolation and function approximation (numerical analysis), Electrical engineering. Electronics. Nuclear engineering, Amplifiers, Logic circuits, TK1-9971
Modulation and coding methods, Mobile radio systems, Interpolation and function approximation (numerical analysis), Electrical engineering. Electronics. Nuclear engineering, Amplifiers, Logic circuits, TK1-9971
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
