Adaptive Modified Versoria Zero Attraction Least Mean Square Algorithms

Bhattacharjee, Sankha Subhra; Ray, Dwaipayan; George, Nithin V.

doi:10.1109/tcsii.2020.2999886

Cited by 20 publications

(9 citation statements)

References 12 publications

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“…These algorithms consider all the previous error terms for objective function formulation, and hence outperforms the existing SGD based approaches. Recently, Versoria criterion [23]- [25] based RFF-KRMVC algorithm is found to outperform the conventional minimum mean square error (MMSE) based RFF-KRLS post-distorter due to the incorporation of order statistics, and lower steady-state misadjustment as has been proved in the literature [22], [25].…”

Section: A Related Workmentioning

confidence: 90%

“…Capitalizing on the derived PDF in (25), next we proceed to derive analytical BER for the proposed algorithm. Using α → 1, and error-variance σ 2 δ ≈ σ 2 RFF-KWS-KRMVC [27] at convergence of the proposed RFF-KWS-KRMVC postdistorter, an analytical BER is derived, which is given by the following theorem.…”

Section: B Ber Analysismentioning

confidence: 99%

“…Using Gauss Hermite numerical integration ∞ −∞ f (t)e −t 2 dt = P p=1 Ω p f (u p ), the PDF of the overall additive distortion ñ is obtained as given in (25).…”

Section: Appendix B Proof Of Theoremmentioning

confidence: 99%

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Kernel Recursive Maximum Versoria Criterion Based Post-Distorter for VLC Using Kernel-Width Sampling

et al. 2022

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Visible light communication (VLC) has emerged as a potential candidate for next generation wireless communication systems. However, nonlinear characteristics of light emitting diode (LED), user-mobility, and DC-bias fluctuations are the major factors that limit the throughput of a VLC link, and makes the overall additive distortion as non-Gaussian distributed. To mitigate this non-Gaussian noise processes encountered in VLC systems due to LED nonlinearity, and user-mobility, recently a random Fourier features (RFF) based kernel recursive maximum Versoria criterion (KRMVC) based post-distortion algorithm is proposed, which delivers better performance as compared to the classical polynomial series, and kernel recursive least squares (KRLS) algorithms due to the incorporation of higher order statistics of error. However, the performance of RFF-KRMVC algorithm is sensitive to the choice of kernel-width, and results in approximation errors due to imperfect choice of kernelwidth. This paper proposes a novel RFF-KRMVC algorithm using a kernel-width sampling (KWS) technique called as RFF-KWS-KRMVC, which implements the post-distortion under a hyperparameter-free finite memory budget. Furthermore, analytical expressions for mean square error, and error rate are quantified for the proposed RFF-KWS-KRMVC post-distorter, and corroborated by Monte-Carlo simulations performed over standard VLC channel models.

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Section: A Related Workmentioning

confidence: 90%

Section: B Ber Analysismentioning

confidence: 99%

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Kernel Recursive Maximum Versoria Criterion Based Post-Distorter for VLC Using Kernel-Width Sampling

et al. 2022

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“…Equation (10) shows that the l 1 -norm reweighted parameter α ar ðk þ 1Þ depends on the next values of three parameters such as Ψðk þ 1Þ, Ωðk þ 1Þ, and Φðk þ 1Þ, which are defined in ( 11)- (13), respectively, when Φðk þ 1Þ ≠ 0. Otherwise, from (13), the term Φðk þ 1Þ ¼ 0, so α ar ðk þ 1Þ ¼ 0 from (10), which means that ĥðk þ 1Þ in (9) behave like a standard NLMS algorithm. It is therefore understood that Φðk þ 1Þ determines the next value of α ar .…”

Section: Proposed Adaptive Za-based Rnlms Algorithmmentioning

confidence: 99%

An improved sparsity‐aware normalized least‐mean‐square scheme for underwater communication

Kumar

2022

ETRI Journal

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Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct‐adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex‐combination method for the identification of sparse structures using a reweighted normalized least‐mean‐square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l1‐norm parameter, a modified sparsity‐aware adaptive zero‐attracting RNLMS (AZA‐RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean‐square‐error expression that proves that the AZA‐RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

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“…However, the presented algorithm does not reject DC‐offset. Bhattacharjee et al [23] have presented the adaptive modified versoria zero attraction LMS algorithm, which is complex and it uses 9 N + 10 multiplication 7 N + 1 addition operations whereas the proposed improved zero attracting quaternion‐valued LMS (IZAQ‐LMS) uses only 3 N + 1 multiplication and 3 N addition operations [23]. Furthermore, Kewat and Singh [11] developed an improved reweighted zero‐attracting quaternion‐valued LMS algorithm for an islanded distributed generation system.…”

Section: Introductionmentioning

confidence: 99%

IZAQ‐LMS‐based control of PV‐battery interfaced microgrid in grid‐connected and autonomous modes

Gupta

Verma

Singh

et al. 2020

IET power electron.

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This study presents a voltage source converter (VSC) control of solar photovoltaic (PV)‐battery‐based three‐phase grid interfaced microgrid. This microgrid is controlled to operate in an autonomous mode and the grid‐connected mode. In grid integrated mode, the control aims to improve the power quality of the grid current and to ensure the unity power factor operation at the grid. Therefore, in the grid‐connected mode, the improved zero attracting quaternion‐valued least mean square (IZAQLMS) control approach with high DC offset rejection capability is used. Owing to this, the reference grid currents become immune to harmonics and DC‐offset. The control strategy takes power management into account and additionally assists several vital functions such as compensation of reactive power, power factor correction, and harmonics mitigation. This control scheme also ensures the stable system operation in autonomous mode following an unexpected incident deprived of collapse owing to the grid failure and discrepancy in the generation and load demand. In off‐grid mode, the microgrid control generates a good quality of voltages and feeds the power to the load using the PV array and the battery. Simulated and test results on a laboratory prototype validates the effectiveness of the system.

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Adaptive Modified Versoria Zero Attraction Least Mean Square Algorithms

Cited by 20 publications

References 12 publications

Kernel Recursive Maximum Versoria Criterion Based Post-Distorter for VLC Using Kernel-Width Sampling

Kernel Recursive Maximum Versoria Criterion Based Post-Distorter for VLC Using Kernel-Width Sampling

An improved sparsity‐aware normalized least‐mean‐square scheme for underwater communication

IZAQ‐LMS‐based control of PV‐battery interfaced microgrid in grid‐connected and autonomous modes

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