Impact of feedback noise on digital predistortion with intuitive direct learning

The impact of feedback noise on digital predistortion with intuitive direct learning is investigated. The noise leads to an extra NMSE, which is NMSE_η = 1/Gp(1-|1-θ|²). σ_n²/P_y. Processing gain G_p is the ratio of block size to the number of coefficients, θ is the approximation of the first order derivative for PA functions and p_y/σ_n² is the SNR of feedback path. For processing gain 22.5 dB, our experiments show noise of 35 dB SNR almost has no impact on linearization. If we consider 12 dB PAPR (8 dB PAPR + 4 dB margin), an 8-ENOB ADC could support DPD systems with intuitive direct learning.