Attention mechanism based bidirectional LSTM model for broadband power amplifier linearization

In this letter, a novel digital predistortion (DPD) model for broadband power amplifier (PA) linearization is proposed, namely Attention Mechanism based Bidirectional Long Short‐term Memory Network (AM‐BiLSTM) model. In order to verify the linearization performance of the AM‐BiLSTM model in digital predistortion process, a 100 MHz bandwidth 5G new radio (5G NR) signal is employed to test a sub‐6G PA operating at 2.6‐GHz. The experimental results show that the adjacent channel power ratio (ACPR) of the PA with AM‐BiLSTM model can be improved by 24 dB which is 6 dB and 3 dB better than the generalized memory polynomial (GMP) model and the Chebyshev polynomials LSTM (CP‐LSTM) model in ref [1], repspectively. Therefore, the proposed AM‐BiLSTM model is very effective for the DPD linearization of broadband PAs. In this letter, a novel model for broadband power amplifier (PA) linearization is proposed, namely Attention Mechanism based Bidirectional Long Short‐term Memory network (AM‐BiLSTM). In order to verify the linearization performance of the AM‐BiLSTM model, a 100 MHz bandwidth 5G new radio (5G NR) signal is employed to test the sub‐6G PA operating at 2.6‐GHz.the proposed AM‐BiLSTM is very effective for the linearization of broadband PA.