Reduction on Model Operations Complexity of Simplified Volterra in Digital Predistortion for Wireless Communications

被引:0
|
作者
Choo, Hong Ning [1 ]
Hashim, Shaiful Jahari [2 ]
Latiff, Nurul Adilah Abdul [3 ]
Rokhani, Fakhrul Zaman [4 ]
Yusoff, Zubaida [5 ]
Varahram, Pooria [6 ]
机构
[1] Universiti Putra Malaysia, Selangor, Seri Kembangan,43400, Malaysia
[2] Computer and Communications Systems Engineering Department, Faculty of Engineering and Institute for Mathematical Research (INSPEM), Universiti Putra Malaysia, Selangor, Seri Kembangan,43400, Malaysia
[3] School of Ocean Engineering, Universiti Malaysia Terengganu, Terengganu, Kuala Terengganu,21300, Malaysia
[4] Computer and Communications Systems Engineering Department, Faculty of Engineering, Universiti Putra Malaysia, Selangor, Seri Kembangan,43400, Malaysia
[5] Faculty of Engineering, Multimedia University, Selangor, Cyberjaya,63100, Malaysia
[6] Research and Development Principal Engineer of Benetel Limited, Dublin,D08, Ireland
关键词
Linearization;
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学科分类号
摘要
The evolution of Digital Predistortion (DPD) for Power Amplifier (PA) linearization in wireless communications has seen a natural progression towards increasingly complex DPD models. This complexity directly correlates with improved accuracy in modeling PAs, thereby enhancing the linearization performance of DPD systems. As the demand for bandwidth and PA operation frequencies continues to rise, there is a growing trend towards achieving higher accuracy at the expense of increased complexity. This trend poses challenges for DPD design, necessitating the introduction of more complex algorithms to ensure effective PA linearization. This phenomenon is especially apparent in Volterra Series DPD algorithms, which are widely used for modelling nonlinear systems like PAs. This paper showcases the steps of reducing the modelling operations complexity of the Simplified Volterra (SV) method. The treated SV method presented in this paper is compared against the original SV method through simulation. The DPD model operations complexity is evaluated using the number of required multiplication operations. The DPD PA linearization performance is evaluated with respective model’s Normalized Mean Square Error (NMSE). A 57% reduction on the number of multiplication operations is observed in the treated SV against the original SV. Measured NMSE is similar for both models, indicating the treated SV model achieves this reduction in complexity without sacrificing linearization performance. © (2024) International Association of Engineers. All rights reserved.
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页码:801 / 812
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