Linearization of RF Power Amplifiers in Wideband Communication Systems by Adaptive Indirect Learning Using RPEM Algorithm

The baseband digital pre‐distortion (DPD) signal processing technique is the most cost‐effective linearisation method among other techniques to address the nonlinearity effect of the power amplifier. For communication systems containing DPD and power amplifier, it is difficult to acquire performance metrics closed‐forms for any DPD architecture since there was no mathematical expression for each DPD coefficient. Usually, researchers look for more efficient DPD algorithms for DPD coefficients (compared to the existing ones) in terms of computational complexity, delay, power consumption etc. Consequently, performance is evaluated through intensive simulation. In this paper, it is shown how one can exploit the results of the recent work to mathematically model the indirect learning architecture DPD and efficiently derive important measures in communication systems. Expressions of the normalised mean square error (NMSE) and achievable rate for the OFDM communication system are derived. The DPD is modelled mathematically by exploiting the DPD coefficients closed‐form expressions. The derived expressions of the NMSE and achievable rate are verified through numerical simulations. Furthermore, closed‐form expressions for the NMSE and achievable rate bounds for the OFDM communication system are derived. The performance measures bounds are found assuming a perfect linearisation scenario. The analytical expressions are validated through numerical simulations.

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“…Therefore var(z ) can be obtained by substituting Equation (28) in Equation ( 27), and we can obtain 𝜎 2 n q by substituting in Equation ( 7):…”

Section: Var(n Q )mentioning

confidence: 99%

“…Also in ref. [28], adaptive ILA‐DPD using a recursive prediction error minimisation (RPEM) algorithm is proposed, and the simulation results show the performance improvement in terms of both EVM and ACPR. ACLR is an important metric in cases where the leakage of the signal (outside the band) is violating spurious emission limit [29].…”

Section: Introductionmentioning

confidence: 99%

Performance of digital predistorter in system with analogue to digital converter

Elaskary¹,

Mehana

Fahmy

et al. 2022

IET Communications

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“…The P1dB makes a comparative performance in the linear region and the saturation zone of the nonlinear device [16,17]. In this work, the weighted memory polynomial model (W-MPM) is proposed as an adaptive technique that takes into account the electrical variation of a nonlinear device under test corrected by a indirect learning approach (ILA) linearization scheme [18]. The variations in time of a device as RF-PA are generated by the impedances and parasitic capacitances within the device; unfortunately, during the amplification process, the devices are brought to the saturation zone, and it is precisely in this region where it behaves as highly nonlinear.…”

Section: Introductionmentioning

confidence: 99%

“…Then, the post-distorter is estimated based on the least square error (LSE) method, and the result is placed before the RF-PA. Unlike DLA, it is required to define an RF-PA model then, and finally, the total linearization is just the inverse result of this model [18,20,21]. Some linearization works related to compensation of nonlinear systems use a compensation model to update the coefficients of a system, such as nonlinear applications of the global system for mobile communication (GSM) [22]; in addition, models derived from Volterra Series such as MPM to compensate for the characteristics of the short-wave PA are presented, where IMD3 to overcome the nonlinear behavior are reduced [23].…”

Section: Introductionmentioning

confidence: 99%

A Weighted Linearization Method for Highly RF-PA Nonlinear Behavior Based on the Compression Region Identification

et al. 2021

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In this paper, we present an adaptive modeling and linearization algorithm using the weighted memory polynomial model (W-MPM) implemented in a chain involving the indirect learning approach (ILA) as a linearization technique. The main aim of this paper is to offer an alternative to correcting the undesirable effect of spectral regrowth based on modeling and linearization stages, where the 1-dB compression point (P1dB) of a nonlinear device caused by memory effects within a short time is considered. The obtained accuracy is tested for a highly nonlinear behavior power amplifier (PA) properly measured using a field-programmable gate array (FPGA) system. The adaptive modeling stage shows, for the two PAs under test, performances with accuracies of −32.72 dB normalized mean square error (NMSE) using the memory polynomial model (MPM) compared with −38.03 dB NMSE using the W-MPM for the (i) 10 W gallium nitride (GaN) high-electron-mobility transistor (HEMT) radio frequency power amplifier (RF-PA) and of −44.34 dB NMSE based on the MPM and −44.90 dB NMSE using the W-MPM for (ii) a ZHL-42W+ at 2000 MHz. The modeling stage and algorithm are suitably implemented in an FPGA testbed. Furthermore, the methodology for measuring the RF-PA under test is discussed. The whole algorithm is able to adapt both stages due to the flexibility of the W-MPM model. The results prove that the W-MPM requires less coefficients compared with a static model. The error vector magnitude (EVM) is estimated for both the static and adaptive schemes, obtaining a considerable reduction in the transmitter chain. The development of an adaptive stage such as the W-MPM is ideal for digital predistortion (DPD) systems where the devices under test vary their electrical characteristics due to use or aging degradation.

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Closed-form analysis for indirect learning digital pre-distorter for wideband wireless systems

Elaskary¹,

Mehana

Fahmy

et al. 2022

Physical Communication

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Linearization of RF Power Amplifiers in Wideband Communication Systems by Adaptive Indirect Learning Using RPEM Algorithm

Cited by 4 publications

References 22 publications

Performance of digital predistorter in system with analogue to digital converter

Performance of digital predistorter in system with analogue to digital converter

A Weighted Linearization Method for Highly RF-PA Nonlinear Behavior Based on the Compression Region Identification

Closed-form analysis for indirect learning digital pre-distorter for wideband wireless systems

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