Novel adaptive digital predistortion based on the hybrid indirect learning algorithm

Zhang, F.; Wang, Yong; Ai, Bo

doi:10.1109/bmsb.2014.6873578

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Cited by 3 publications

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“…In Fig. 6, compared with the indirect learning architecture and the hybrid indirect learning [8], the composite architecture proposed in this paper can more effectively improve the constellation dispersion.…”

Section: Simulation Resultsmentioning

confidence: 99%

Composite Adaptive Digital Predistortion with Improved Variable Step Size LMS Algorithm

Gu¹,

Gu²,

Mao³

et al. 2016

Proceedings of the 2nd Information Technology and Mechatronics Engineering Conference (ITOEC 2016TOEC 2016)

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Abstract. This paper presents a composite learning (CL) architecture. The CL can make use of the advantages of both direct and indirect learning. By an appropriate threshold, the indirect learning can be switched into direct learning. In order to further improve the performance of direct learning, an improved variable step size LMS algorithm is proposed. The proposed algorithm has the lower normalized mean-square error (NMSE) with low computation complexity. The outstanding performance is confirmed by simulation results.

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Section: Simulation Resultsmentioning

confidence: 99%