Low Complexity Distributed Model for the Compensation of Direct Conversion Transmitter’s Imperfections

Aziz, Mohsin; Rawat, Meenakshi; Ghannouchi, Fadhel M.

doi:10.1109/tbc.2014.2343071

Cited by 11 publications

(8 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where 𝑑 𝑘 (𝑛) denotes the FIR filter coefficients vector and its order are equal to the number of FIR filter taps. So, the final joint pre-distortion model formulation is written as (17).…”

Section: Proposed Digital Pre-distorter Model Of Pa and Iq Modulatormentioning

confidence: 99%

“…As shown in the plot, for the OFDM 16 QAM signal, the condition number has improved more than 80 dB in comparison to the MP model, and the dispersion coefficient parameter has a reduction of around 10-20 dB, which causes a considerable reduction in complexity. To calculate the number of required FLOPs, we have driven two relations based on the method used in [17,25] for the Chebyshev DPD (based on the recursive equation in ( 2)) and the MP DPD (based on equation ( 1)). According to the results shown in Table 1, for a joint DPD with 33 complex-valued coefficients (𝐾 = 1, 𝑄 = 2 and 𝑃 = 3), we require 356 FLOPs at every step of the computation to implement the model.…”

Section: Numerical Stability and Complexity Analysismentioning

confidence: 99%

“…The proposed model improved the numerical instability problem of DPD by a reduction in the number of coefficients and so reduced the dispersion coefficients and condition number. In [17] a distributed model using conventional memory polynomials was presented. The proposed model used a two-block structure for DPD, the first block was a memory polynomial model to reduce the nonlinear effects of the PA, and the second one was a mild nonlinear model with memory to compensate the modulator's impairments.…”

Section: Introductionmentioning

confidence: 99%

“…It was claimed that by distributing nonlinearity and memory depth, a considerable reduction in matrix conditioning and coefficients dispersion was obtained. The obtained numerical stability due to the reduction in the number of pre-distortion coefficients in [16], [17], is very fragile and as the nonlinear order of the system intensify, the number of pre-distortion coefficients inevitably increase, resulting in the changes in the matrix conditioning and numerical instability arise. An orthogonal polynomial model was introduced by Wang et al in [18] by using the combined least-mean-square (LMS) and recursive least square (RLS) algorithm to model the nonlinearity of PA with memory effect.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Joint digital pre-distortion model based on Chebyshev expansion

Majdinasab

Jannesari

2022

IJECE

View full text Add to dashboard Cite

<span>In this paper, a new low complexity model is proposed for the joint digital pre-distortion of in-phase/quadrature-phase (I/Q) imbalance, local oscillator (LO) leakage, and power amplifier nonlinearity in direct-conversion transmitters (DCTs). In this structure, we proposed a set of orthogonal basis functions based on Chebyshev expansion to attenuate the problem of numerical instability created during the conventional model identification method. This robust joint digital pre-distortion (DPD) utilized the indirect learning architecture and updated the coefficients vector based on the recursive least square (RLS) algorithm. To verify the operation and efficiency of the proposed model, an extensive simulation in MATLAB was carried out. The results showed a significant reduction in the conditional number and the coefficient dispersion of the observation matrix. Furthermore, the power of the signal in the adjacent channel decreased by more than 16 dB for the orthogonal frequency division multiplexing (OFDM), 16 QAM input signal. In comparison to the previous digital pre-distorter models, the proposed DPD builds strong numerical stability with the least coefficients.</span>

show abstract

Section: Proposed Digital Pre-distorter Model Of Pa and Iq Modulatormentioning

confidence: 99%

Section: Numerical Stability and Complexity Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Joint digital pre-distortion model based on Chebyshev expansion

Majdinasab

Jannesari

2022

IJECE

View full text Add to dashboard Cite

show abstract

“…Apparently, in the literature, several models such as, Volterra series-based model, neural network-based models, and variations of memory polynomial models, have been proposed, which successfully model and mitigate the impairments introduced by modulator and power amplifiers [13,14,15,16,17,18]. However, this comes at the cost of complexity and higher processing rates.…”

Section: Introductionmentioning

confidence: 99%

Forward Behavioral Modeling of a Three-Way Amplitude Modulator-Based Transmitter Using an Augmented Memory Polynomial

Chatrath

Aziz

Helaoui

2018

Sensors

Self Cite

View full text Add to dashboard Cite

Reconfigurable and multi-standard RF front-ends for wireless communication and sensor networks have gained importance as building blocks for the Internet of Things. Simpler and highly-efficient transmitter architectures, which can transmit better quality signals with reduced impairments, are an important step in this direction. In this regard, mixer-less transmitter architecture, namely, the three-way amplitude modulator-based transmitter, avoids the use of imperfect mixers and frequency up-converters, and their resulting distortions, leading to an improved signal quality. In this work, an augmented memory polynomial-based model for the behavioral modeling of such mixer-less transmitter architecture is proposed. Extensive simulations and measurements have been carried out in order to validate the accuracy of the proposed modeling strategy. The performance of the proposed model is evaluated using normalized mean square error (NMSE) for long-term evolution (LTE) signals. NMSE for a LTE signal of 1.4 MHz bandwidth with 100,000 samples for digital combining and analog combining are recorded as −36.41 dB and −36.9 dB, respectively. Similarly, for a 5 MHz signal the proposed models achieves −31.93 dB and −32.08 dB NMSE using digital and analog combining, respectively. For further validation of the proposed model, amplitude-to-amplitude (AM-AM), amplitude-to-phase (AM-PM), and the spectral response of the modeled and measured data are plotted, reasonably meeting the desired modeling criteria.

show abstract

A robust digital predistorter based on complex hermite polynomial for direct conversion transmitter linearization

Majdinasab

Jannesari²

2023

Analog Integr Circ Sig Process

View full text Add to dashboard Cite

Low Complexity Distributed Model for the Compensation of Direct Conversion Transmitter’s Imperfections

Cited by 11 publications

References 30 publications

Joint digital pre-distortion model based on Chebyshev expansion

Joint digital pre-distortion model based on Chebyshev expansion

Forward Behavioral Modeling of a Three-Way Amplitude Modulator-Based Transmitter Using an Augmented Memory Polynomial

A robust digital predistorter based on complex hermite polynomial for direct conversion transmitter linearization

Contact Info

Product

Resources

About