Estimation of crossover DPD using orthogonal polynomials in fixed point arithmetic

Abstract This paper deals with the fixed point implementation of crossover digital predistortion (DPD). The implementation of digital predistortion linearization technique on DSPs poses major challenges, regarding cost, power consumption, speed, precision and volume. Depending on resource availability and design restrictions, fixed-point DSPs may be considered as a suitable solution. Least squares estimation of crossover DPD for multiple-input, multiple-output (MIMO) applications using conventional polynomial models face numerical instability for fixed-point processing. Orthogonal polynomials on the other hand are robust to matrix inversion. Fixed point matrix inversion was implemented using LU decomposition and triangular matrix inversion. This paper examines crossover DPD design for MIMO applications, while using fixed-point arithmetic. It also compares the linearization of 2 × 2 MIMO transmitters in the presence of radio frequency crosstalk using both orthogonal and memory polynomial models. The performance of the two crossover DPDs has been evaluated using a 3GPP standard: orthogonal crossover DPD decreased the measured adjacent channel power ratio of the signal from −42 dBc to −52 dBc.

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