The lookup-table-based digital adaptive predistortion (DAPD-LUT) approaches are low cost and effective for power amplifier (PA) linearization in wireless applications. However, most existing DAPD-LUT schemes are sub-optimum because they adopt uniformly spaced LUTs regardless of the system state information (SSI), i.e., the PA characteristics and the input signal statistics. Other existing DAPD-LUT schemes assume either full or partial knowledge of the SSI to optimize and then to freeze the LUT spacing. Without prior knowledge of the SSI, we propose an SSI-learning low-complexity procedure to optimize the LUT spacing for a DAPD-LUT scheme. The proposed procedure is capable of online adapting the LUT spacing for PAs with various nonlinear characteristics, for input signals with various statistics, and for wireless environments with various time-varying properties.
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Lin et al. (2006) studied this question.
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