Progress for Behavioral Challenges: A Summary of Time-domain Behavioral Modeling of RF and Microwave Subsystems

Ngoya, Edouard; Mons, Sébastien

doi:10.1109/mmm.2014.2332853

Cited by 26 publications

(6 citation statements)

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“…During the DPD training phase and following the indirect learning architecture (ILA) [45], we measure, down-convert and process the length-N signals x and ỹ, respectively, the PA undistorted input and NL output. In the ILA, the DPD training postdistorter, placed after the PA, estimates directly the inverse model, by interchanging the roles of the signals above, i.e., using ũ = ỹ/G P A as the post-inverse normalized input (G P A is the PA linear gain) and minimizing the least squares error between x and the modelled post-inverse output x, i.e., x − x 2 2 , where • 2 is the Euclidean norm [46]. After the training phase is completed, the postdistorter inverse model is copied to the DPD predistorter [1].…”

Section: A Estimation Techniquesmentioning

confidence: 99%

Sparse Flexible Reduced-Volterra Model for Power Amplifier Digital Pre-Distortion

Hemsi

Panazio

2022

IEEE Access

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The Volterra framework plays an important role in digital pre-distortion (DPD) for power amplifier (PA) linearization. In practice, the full-Volterra (FV) model is avoided due to the so-called curse of dimensionality, which has motivated several Volterra pruning techniques in the literature. However, choosing the pruned-Volterra structure with a given complexity that most accurately describes a PA or DPD with unknown characteristics often requires trial and error. The motivation of this article is to propose a reduced-Volterra model that extends traditional memory polynomials, e.g., the generalized memory polynomial (GMP), by including higher-dimensional terms in a flexible and controlled way, avoiding the curse of dimensionality of the Volterra model and resulting in a model that can apply to a wide range of PA and DPD. Furthermore, the article investigates the parsimonious sizing of the proposed model using least absolute shrinkage and selection operator (LASSO) and sparse-group LASSO (SGL) convex optimization, significantly reducing the model's running cost, while preserving its performance. In our experimental validation, the sparse versions of the proposed model achieved 3 dB better adjacent channel power ratio (ACPR) than the conventional GMP model for the same or lower DPD running cost, at the expense of a more costly estimation, which is performed off-line.

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Section: A Estimation Techniquesmentioning

confidence: 99%

Sparse Flexible Reduced-Volterra Model for Power Amplifier Digital Pre-Distortion

Hemsi

Panazio

2022

IEEE Access

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“…It can be seen from Table , using SCERNE not only capable for bilateral modeling of component's block, but also it has the possibility of concurrently simulation in time domain and mixed time‐frequency domains (transient, envelope‐transient, and continuous wave (CW) analysis). In addition, SCERNE simulation is based on envelope transient simulation concept, which it helps to create bilateral blocks in the system chain including mixers …”

Section: Advanced System‐level Simulation In Scernementioning

confidence: 99%

Advanced system‐level simulation paradigm for ultra‐wideband systems using SCERNE platform

Ojaroudi

Bila

Ngoya

et al. 2019

Int J RF Microw Comput Aided Eng

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In this article, a progressive system‐level simulation framework is developed based on Simulation de Chaînes d'Emission/Réception Nouvelle gEnération (SCERNE) platform to simulate an ultra‐wideband (UWB) impulse radar transmitter and accurately predict its performance. With the purpose of demonstrating the usefulness of the SCERNE ability in system‐level modeling, we present and simulate a simplified structure of UWB impulse radar transmitter. First, after simulation each component in different circuit‐level tools such as ADS, CST, and HFSS, each part has been modeled by using different modeling methods to transfer their data into MATLAB environment. Then, we duplicate the transmitter structure in SCERNE toolbox to validate the results. The advantage conferred by the proposed SCERNE toolbox is that fast and accurate bilateral modeling method is available at multi‐medium structures in contrast with conventional unilateral modeling, and so a lower memory and higher accuracy of the behavioral model is achieved. It can also be beneficial when the user is looking for system‐level, as the increased components amounts can help as a surrogate model. The system model can be easily extended to other UWB radar systems by simply changing the input pulse shape, UWB channel environment, transceiver topology, etc. Various effects such as signal quality, and pulse shape that can easily investigate and re‐optimize for high performance are using the developed model. To validate the practicality of the proposed paradigm, the simulations and predictions through model results are being outlined.

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“…The input-output relationship of a two-port network with perfectly matched impedance could be expressed as an implicit nonlinear dynamic equation. 9 Considering that the PA is a two-port network of causality, stability, continuity, and fading memory, the implicit equation can be extended to a finite impulse response digital filter form. Then, using the Taylor series to approximate the implicit equation, the real-valued Volterra series model can be obtained:…”

Section: Dynamic Dual-band Baseband Equivalent Volterra Modelsmentioning

confidence: 99%

Volterra series-based model for concurrent dual-band power amplifier using dynamic memory depth

Peng

You

et al. 2018

Int J RF Microw Comput Aided Eng

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In this article, a dynamic dual‐band baseband equivalent Volterra (DDBE) model is proposed to compensate the nonlinear distortions of the concurrent dual‐band power amplifier (PA). The DDBE model is obtained by improving the discretized dual‐band baseband equivalent Volterra model which can describe the output characteristics of concurrent dual‐band PA completely in theory but is lack of practicability. Three simplification rules are proposed in the article, and the relevance between in‐band intermodulation and in‐band cross modulation is employed to simplify the establishment complexity of the model. Then the dynamic kernels are categorized into three groups, and based on this, DDBE models with different level dynamical kernels are derived. In addition, draw on the experience of single‐band PA behavioral model, even‐order kernels are introduced into DDBE models. Digital predistortion performances of a wideband PA, which works in concurrent dual‐band mode, are evaluated to verify the feasibility and advantages of the proposed model.

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Progress for Behavioral Challenges: A Summary of Time-domain Behavioral Modeling of RF and Microwave Subsystems

Cited by 26 publications

References 50 publications

Sparse Flexible Reduced-Volterra Model for Power Amplifier Digital Pre-Distortion

Sparse Flexible Reduced-Volterra Model for Power Amplifier Digital Pre-Distortion

Advanced system‐level simulation paradigm for ultra‐wideband systems using SCERNE platform

Volterra series-based model for concurrent dual-band power amplifier using dynamic memory depth

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