Modeling Nonlinear Power Amplifiers in OFDM Systems from Subsampled Data: A Comparative Study Using Real Measurements

Santamarı́a, Ignacio; Ibáñez, J.; Lázaro, Marcelino; Pantaleón, C.; Vielva, Luis

doi:10.1155/s1110865703306067

Cited by 17 publications

(10 citation statements)

References 20 publications

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“…Volterra models have been used for modeling RF PAs but typically only up to nonlinear order 3 and memory lengths of 1 [5,8], since the number of parameters becomes too large. A time-discrete Volterra model of order 9 and with memory depth of 4 (5) samples would have 11,875 (40,116) complex parameters (see [5]), and could not be practically used.…”

Section: Discussionmentioning

confidence: 99%

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A parameter-reduced volterra model for dynamic RF power amplifier modeling based on orthonormal basis functions

Isaksson

Rönnow

2007

Int J RF and Microwave Comp Aid Eng

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A nonlinear dynamic behavioral model for radio frequency power amplifiers is presented. It uses orthonormal basis functions, Kautz functions, with complex poles that are different for each nonlinear order. It has the same general properties as Volterra models, but the number of parameters is significantly smaller. Using frequency weighting the out-of-band model error can be reduced. Using experimental data it was found that the optimal poles were the same for different input powers and for the different nonlinear orders. The optimal poles were also the same for direct and inverse models, which could be explained theoretically to be a general property of nonlinear systems with negligible linear memory effects. The model can be used as either a direct or inverse model with the same model error for power amplifiers with negligible linear memory effects.

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Section: Discussionmentioning

confidence: 99%

“…Volterra models of PAs have been reported in [5,8]. These models have the drawback that the number of parameters increases rapidly with nonlinear order and memory depth, i.e.…”

Section: Introductionmentioning

confidence: 99%

A parameter-reduced volterra model for dynamic RF power amplifier modeling based on orthonormal basis functions

Isaksson

Rönnow

2007

Int J RF and Microwave Comp Aid Eng

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“…In practice, many amplifiers also exhibit some memory in their nonlinear distortion characteristics [43,45,51,52,[54][55][56][57][58][59][60]. At the modeling level, this can be incorporated by introducing linear filtering effects combined with previous instantaneous nonlinear mappings.…”

Section: Nonlinearitiesmentioning

confidence: 99%

RF Impairment Compensation for Future Radio Systems

Hueber

Staszewski²

2010

Multi‐Mode/Multi‐Band RF Transceivers for Wireless Communications

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“…Good examples of such waveforms are, e.g., orthogonal frequency division multiplexing (OFDM)-type multicarrier signals. Another important aspect in this context is power amplifier memory, implying that the induced distortion characteristics are frequency-dependent [1], [11], [12], [23], [27], [28]. This is seen very important in emerging radio communications systems, such as IMT-Advanced, with radio and waveform bandwidths in the order of 10-100 MHz [29], [30].…”

Section: Introductionmentioning

confidence: 99%

Steady-State Performance Analysis and Step-Size Selection for LMS-Adaptive Wideband Feedforward Power Amplifier Linearizer

Gokceoglu¹,

ghadam²,

Valkama³

2012

IEEE Trans. Signal Process.

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Balancing between power amplifier (PA) linearity and power efficiency is one of the biggest implementation challenges in radio communication transmitters. Among various linearization methods, the feedforward linearization technique is a fairly established principle offering a good tradeoff between linearity and power-efficiency even under wideband operation. Moreover, adaptive techniques for such linearizer have been proposed in literature to track parameter changes in the main PA and other circuitry. Among those, least mean squares (LMS) method for adapting signal cancellation loop (SCL) and error cancellation loop (ECL) coefficients is an attractive low-complexity alternative. In this paper, we carry out extensive closed-form performance analysis of the achievable intermodulation distortion (IMD) reduction of the overall LMS-adaptive feedforward linearizer, as a function of the used step-sizes and essential waveform statistics. Such analysis is currently missing from the state-of-the-art literature. Both memoryless nonlinearities and Wiener-Hammerstein type PA memory models are studied for which IMD suppression expressions are derived. Comprehensive computer simulations are also provided to illustrate the accuracy of the analysis when practical OFDM waveforms are used. Design examples are given as well where the analysis results are used to choose proper linearizer step-sizes to meet given transmitter spectral mask specifications. Index Terms-Feedforward linearizer, intermodulation distortion (IMD), LMS, power amplifier (PA), step-size, Wiener-Hammerstein.

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Modeling Nonlinear Power Amplifiers in OFDM Systems from Subsampled Data: A Comparative Study Using Real Measurements

Cited by 17 publications

References 20 publications

A parameter-reduced volterra model for dynamic RF power amplifier modeling based on orthonormal basis functions

A parameter-reduced volterra model for dynamic RF power amplifier modeling based on orthonormal basis functions

RF Impairment Compensation for Future Radio Systems

Steady-State Performance Analysis and Step-Size Selection for LMS-Adaptive Wideband Feedforward Power Amplifier Linearizer

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