Minimizing Training Signal Length for Power Amplifier Characterization and Linearization

Wireless communication faces a significant challenge in meeting latency and power consumption requirements due, in large part, to the nonlinear behavior of power amplifiers (PAs) requiring digital predistortion (DPD). Calculating the parameters for DPD can be computationally demanding, especially with multiple transmitter paths in multiple-input–multiple-output (MIMO) systems. This research formulates a novel optimized training signal for DPD (OTS-DPD) that minimizes the number of samples needed to implement DPD while maintaining optimum PA linearization performance. Experimental validation of the DPD performance for the novel OTS-DPD signal demonstrates it outperforms a standard 5G orthogonal frequency division multiplexing (OFDM) signal and uses significantly fewer samples.