Inverse Covariance Matrix Estimation for Low-Complexity Closed-Loop DPD Systems: Methods and Performance

Campo, Pablo Pascual; Anttila, Lauri; Lampu, Vesa; Allén, Markus; Guo, Yan; Wang, Neng; Valkama, Mikko

doi:10.1109/tmtt.2021.3124226

Cited by 3 publications

(7 citation statements)

References 47 publications

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“…In the first category, the model parameterization is allowed to access the iterative procedure until the optimal convergence. It becomes more challenging during recalculating the basis function matrix in the case when a signal direction is modified in real-world transmission [105]. While the second and third operations are the most resource-intensive categories, the model's output signal calculations will be affected by the number of model coefficients and training samples in terms of FLOPs.…”

Section: • Complexity Discussionmentioning

confidence: 99%

“…While the second and third operations are the most resource-intensive categories, the model's output signal calculations will be affected by the number of model coefficients and training samples in terms of FLOPs. To avoid such an intensive computation, it is advisable to divide the vector components of the DPD input data symbols into a covariance matrix that constitutes an efficient inverse matrix properties [105], [106].…”

Section: • Complexity Discussionmentioning

confidence: 99%

“…However, dedicated self-orthogonalized learning can also be computationally intensive for the DPD forward path. To avoid such computational efforts, it is advisable, whenever applicable (especially in MMW array linearization), to combine orthogonalization transformation with an inverse covariance matrix to guarantee smooth convergence in the DPD main path [105].…”

Section: • Critical Analysismentioning

confidence: 99%

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Predistortion-Based Linearization for 5G and Beyond Millimeter-Wave Transceiver Systems: A Comprehensive Survey

Haider

You

et al. 2022

IEEE Commun. Surv. Tutorials

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The next-generation (5G/6G) wireless communication aims to leapfrog the currently occupied sub-6 GHz spectrum to the wideband millimeter-wave (MMW) spectrum. However, MMW spectrums with high-order modulation schemes drive the power amplifier (PA) at significant back-off, causing severe nonlinear distortions, thus deteriorating the transceiver's (TRXs) modulation process. Typically, the TRX efficacy is quantified with standardized linearization matrices, which take advantage of different predistortion (PD) schemes to handle deep compression of the PA. In this regard, TRX baseband signals are mostly linearized in the digital domain, where digitally controlled linearization needs higher sampling rates due to increasing MMW bandwidths to compensate for intermodulation (IMD) products, resulting in increased system cost and power consumption. Alternately, the digitally controlled analog-based linearization, i.e., the hybridization of digital predistortion (DPD) and analog predistortion (APD), is highly productive and cost-effective for fulfilling the linearized energy-efficient design vision of MMW networks. Therefore, this paper puts an extensive spotlight on the progress in PD-based linearization for 5G and beyond communications. It first provides background information on the advancements of PD schemes through recent surveys, then classifies the general roadmap of PD waveform processing across the TRX system models as preliminary. After this, we present three prominent PD architectures and their design approaches with intrinsic performance metrics. Finally, we explore four case studies encompassing PD operation under certain nonlinear constraints of different communication schemes. We examine the suitability of PD-based linearization solutions, both existing and proposed till the first quarter of 2022, and identify the potential prospects in this domain.

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Section: • Complexity Discussionmentioning

confidence: 99%

Section: • Complexity Discussionmentioning

confidence: 99%

Section: • Critical Analysismentioning

confidence: 99%

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Predistortion-Based Linearization for 5G and Beyond Millimeter-Wave Transceiver Systems: A Comprehensive Survey

Haider

You

et al. 2022

IEEE Commun. Surv. Tutorials

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“…( 24) can optimize and keep a steady convergence. The error vector is defined as g ¼ ½g 1 ; g 2 ; : : : ; g N T , and the N × N Jacobian matrix J is defined with entries J i;j ¼ ∂g i ∕∂w j , i; j ¼ 1; : : : ; N. Equation ( 24) can then be written as the following matrix form: E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 2 5 ; 1 1 6 ; 5 7 4 wðkÞ ¼ wðk − 1Þ − μðJ T JÞ −1 J T g; (25) where J is the partial derivative matrix, where the ði; jÞ'th element is J i;j ¼ ∂g i ∕∂w j . The adoption of the GN iteration helps to save the cumbersome calculation of the second-order derivative, which can greatly reduce the complexity of the algorithm.…”

Section: Gauss-newton Iterationmentioning

confidence: 99%

“…Aiming at the nonlinear characteristics in the VLC systems, we propose to use the GN iteration to find the solution of the nonlinear problem. With GN method, it is intended to obtain high estimation accuracy and fast convergence, and achieve excellent overall distorting performance during solving the unconstrained nonlinear least squares problems 25 , 26 …”

Section: Implementation Algorithmsmentioning

confidence: 99%

Gauss–Newton iteration method for radial basis function-based postdistortions in visible light communication systems

et al. 2022

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. In visible light communication systems, the inherent nonlinear characteristics of light-emitting diodes (LEDs) are the primary source of signal distortion. To alleviate the nonlinear effect of the LED and improve the system reliability, the polynomial method is used to construct the postdistorter. With strong processing ability and high solution accuracy, radial basis function (RBF) interpolation can also be used to alleviate the nonlinear effect. In terms of the iterative implementations, recursive least squares (RLS) algorithm has been widely adopted, but performance loss exists with the solution since RLS is initially proposed for linear regressions. Aiming at the nonlinear characteristics of post distortions, Gauss–Newton (GN) method is investigated to accomplish the iterations in this paper, where Taylor series expansion is used to approximate the nonlinear regression model. Simulation results show that the RBF can obtain better bit error ratio performance than polynomial, and the proposed GN iterations have significantly better performance compared to RLS in mitigating the nonlinear effect of LED.

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Joint Optimization of Radar and Communications Performance in 6G Cellular Systems

Ashraf

Tan

Moltchanov

et al. 2023

IEEE Trans. on Green Commun. Netw.

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Dual functional radar communication (DFRC) is a promising approach that provides a viable solution for the problem of spectrum sharing between communication and radar applications. This paper studies a DFRC system with multiple communication users (CUs) and a radar target. The goal is to devise beamforming vectors at the DFRC transmitter in such a way that the radar received signal-to-clutter-plus-noise-ratio (SCNR) is maximized while satisfying the minimum data rate requirements of the individual CUs. With regard to clutter, we consider two scenarios based on the possibility of clutter removal. Even though the formulated optimization problems are nonconvex, we present efficient algorithms to solve them using convex optimization techniques. Specifically, we use duality theory and Karush-Kuhn-Tucker conditions to show the underlying structure of optimal transmit precoders. In the proposed solution, it is observed that there is no need to transmit separate probing signal for the radar detection in both the considered scenarios. This results in reduction in the number of optimization variables in the problem. Moreover, we make use of the asymptotic equivalence between Toeplitz matrices and Circulant matrices to further reduce the complexity of the proposed algorithm. Finally, numerical results are presented to demonstrate the effectiveness of the proposed algorithms.

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Inverse Covariance Matrix Estimation for Low-Complexity Closed-Loop DPD Systems: Methods and Performance

Cited by 3 publications

References 47 publications

Predistortion-Based Linearization for 5G and Beyond Millimeter-Wave Transceiver Systems: A Comprehensive Survey

Predistortion-Based Linearization for 5G and Beyond Millimeter-Wave Transceiver Systems: A Comprehensive Survey

Gauss–Newton iteration method for radial basis function-based postdistortions in visible light communication systems

Joint Optimization of Radar and Communications Performance in 6G Cellular Systems

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