Upgrading Behavioral Models for the Design of Digital Predistorters

Sensors

María José Madero-Ayora¹  Carlos Crespo-Cadenas¹  Juan A. Becerra¹ 

[1] Departamento de Teoría de la Señal y Comunicaciones, Escuela Técnica Superior de Ingeniería, Universidad de Sevilla, Camino de los Descubrimientos, s/n, 41092 Seville, Spain;

关键词: behavioral modeling;    digital predistortion;    nonlinear model identification;    power amplifier linearization;    Volterra series;   

DOI  :  10.3390/s21165350

来源: DOAJ

【 摘 要 】

This work presents a strategy to upgrade models for power amplifier (PA) behavioral modeling and digital predistortion (DPD). These incomplete structures are the consequence of nonlinear order and memory depth model truncation with the purpose of reducing the demand of the limited computational resources available in standard processors. On the other hand, the alternative use of model structures pruned a priori does not guarantee that every significant term is included. To improve the limited performance of an incomplete model, a general procedure to augment its structure by incorporating significant terms is demonstrated. The sparse nature of the problem allows a successive search incorporating additional terms with higher nonlinear order and memory depth. This approach is investigated in the modeling and linearization of a commercial class AB PA operating at a compression point of about 6 dB, and a class J PA operating near saturation. Results highlight the capabilities of this upgrading procedure in the improvement of linearization capabilities of DPDs.

【 授权许可】

Unknown