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The polynomial model is commonly used in predistorter design. However, the conventional polynomial model exhibits numerical instabilities when high-order terms are included. We introduce a novel set of orthogonal polynomial basis functions for predistorter modeling. Theoretically, the conventional and the orthogonal polynomial models are "equivalent", and thus should have the same performance. In practice, however, the two approaches can perform quite differently in the presence of quantization noise and with finite precision processing. Simulation results show that the orthogonal polynomials can alleviate the numerical instability problem associated with the conventional polynomials and generally yield better predistortion linearization performance.