Pre-compensation method and pre-compensation circuit thereof

A pre-compensation circuit, coupled to a power amplifier, comprising:

• a digital pre-distortion actuator, configured for performing pre-distortion according to at least one parameter or at least one hyperparameter to convert a first input signal received by the digital pre-distortion actuator into a first pre-distortion output signal;
• and
• a training module, configured for updating the at least one parameter or the at least one hyperparameter according to Causal Bayesian Optimization or Dynamic Causal Bayesian Optimization,
• wherein the digital pre-distortion actuator performs pre-distortion according to the at least one parameter updated or the at least one hyperparameter updated to convert a second input signal received by the digital pre-distortion actuator into a second pre-distortion output signal;
• wherein a plurality of independent variable optimal values are found together from a plurality of independent variables according to the Causal Bayesian Optimization or the Dynamic Causal Bayesian Optimization;
• wherein the plurality of independent variable optimal values comprises the at least one parameter or the at least one hyperparameter;
• wherein a causal structure of a causal graph and a plurality of causal variables of the causal graph are determined together;
• wherein the plurality of causal variables comprise a loss function and the plurality of independent variables;
• wherein the loss function is a function of an output signal output by the power amplifier corresponding to the first pre-distortion output signal or a label corresponding to the output signal;
• wherein a plurality of posterior probabilities of assigning a plurality of subdata of grounding data to a plurality of observation functions and the causal structure of the causal graph are maximized to generate the causal graph;
• wherein one of the plurality of posterior probabilities is proportional to
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• where Wi,t denotes one of the plurality of subdata, which is corresponding to one of the plurality of causal variables, at a time instant t, St−1 denotes at least one state at a time instant t−1, C denotes the causal structure, ƒi denotes a corresponding one of the observation functions, T denotes a current time instant, and γ is a real number.