Simple and robust analytically derived variable step-size least mean squares algorithm for channel estimation

Filho, A.M. Arraes; Pinto, E.L.; Galdino, Juraci Ferreira

doi:10.1049/iet-com.2009.0038

Cited by 14 publications

(6 citation statements)

References 12 publications

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“…The evaluation of the inner products X(n)W(n) requires N complex multiplication and N complex additions for each iteration [3]. The multiplying the scalar by a vector requires N complex multiplications.…”

Section: Performance Analysis a Computational Complexitymentioning

confidence: 99%

“…Least square (LS) [12,17], Least mean square (LMS) [10], normalized NLMS [15], variable step size LMS(VSS-LMS) [3,4] Recursive least square (RLS), Kalman filter, leaky least mean square [16]variable leaky LMS [1] orthogonal Frequency response filtering are some of the well known techniques. At the same time soft computing approaches such as fuzzy logic, neural network, genetic algorithm and simulated annealing [6] have also been used for channel estimation.…”

Section: Introductionmentioning

confidence: 99%

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FPGA implementation of modified leaky least mean square channel estimation algorithm

Bhoyar¹,

Dethe

Mushrif³

2014

2014 2nd International Conference on Devices, Circuits and Systems (ICDCS)

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Channel estimation is a technique used to reduce channel inference in multipath data transmission. This paper analyses and implemented a suggested new method for channel estimation in MIMO-OFDM system. The proposed modified leaky least mean square channel estimation algorithm (M-LLMS) improves channel estimation accuracy in noisy environment. We compare the results of the proposed method with LMS, RLS and VLLMS channel estimators for SNR (1-35) and over 10,000 itertions.The computational complexities and the Bit Error Rate (BER) are reduced by the proposed algorithm.

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Section: Performance Analysis a Computational Complexitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

FPGA implementation of modified leaky least mean square channel estimation algorithm

Bhoyar¹,

Dethe

Mushrif³

2014

2014 2nd International Conference on Devices, Circuits and Systems (ICDCS)

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“…After identifying an available vulnerability, the imposed attack strategy described here provides an unwittingly 1-dB augmentation for all elements into the SNR adaptive modulation interval-for instance, the evaluated SNR interval for SNR av = 20 dB is L Average spectral efficiency (bps/Hz) 10 15 20 25 Average SNR (dB)…”

Section: Radio Control Attackmentioning

confidence: 99%

“…An example of hardware implementation vulnerability is the introduction of hardware trojans [8] during chip fabrication. Vulnerabilities related to the supply chain [9], like device cloning [10], are also included in this subclass.…”

Section: Introductionmentioning

confidence: 99%

Case Studies of Attacks over Adaptive Modulation Based Tactical Software Defined Radios

Moura

Silva

Galdino

2012

Journal of Computer Networks and Communications

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This paper presents case studies of attacks aimed at tactical software defined radios based on a classification with the most common sources of vulnerabilities, classes of attacks, and types of intrusions that military radio sets may suffer. Besides that, we also describe how attack mitigation strategies can impact the development of SDR infrastructures. By using such approach, we identify several possible sources of vulnerabilities, attacks, intrusions, and mitigation strategies, illustrating them onto typical tactical radio network deployment scenarios, as an initial and necessary step for the definition of realistic and relevant security requirements for military software defined radio applications.

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“…are reported in the literature for power quality improvement in grid-tied PV systems. Apart from the conventional control schemes, adaptive filtering techniques [17][18][19][20][21][22][23] such as recursive least square (RLS) [17], least mean fourth (LMF) [18], variable step size LMS [19], filtered-x LMS algorithm [20] etc., have also been employed in the design of grid-tied PV systems because these algorithms are capable of tracking changes and characteristics of the unknown system. The LMS and LMF algorithms suffer from the problem of drifting [24].…”

Section: Introductionmentioning

confidence: 99%

Modified leaky LMS‐based control strategy for reliable operation of single‐stage three‐phase grid‐tied PV system

Parida

Subudhi

2020

IET Renewable Power Generation

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This study presents development of a modified leaky least mean square (MLLMS)-based control strategy for a singlestage three-phase grid-tied photovoltaic (PV) system. In the proposed MLLMS-based control scheme, the authors employ an incremental conductance maximum power point tracking algorithm for maximum power extraction, MLLMS algorithm for extraction of fundamental active and reactive components of the load current, delivering PV power to the grid, balancing the grid current and compensating harmonics of the connected loads at the point of common coupling. By virtue of a leakage factor and selection of sum of the exponential of the adaptation error in the cost function, the MLLMS algorithm overcomes the problems of drifting, low convergence and oscillations in weights encountered by some popular adaptive algorithms, e.g. least mean square (LMS) and least mean fourth (LMF) algorithms. The proposed control scheme is simulated in MATLAB/Simulink environment under different load and environmental conditions. Subsequently, the proposed control scheme is realised on a prototype gridtied PV system developed in the laboratory. From both the simulation and experimental results, it is observed that the proposed MLLMS algorithm outperforms LMS and LMF algorithms in terms of mean square error, oscillation in weights and total harmonic distortions of the grid currents. * reference grid currents i ga , i gc , i gc actual grid currents

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Simple and robust analytically derived variable step-size least mean squares algorithm for channel estimation

Cited by 14 publications

References 12 publications

FPGA implementation of modified leaky least mean square channel estimation algorithm

FPGA implementation of modified leaky least mean square channel estimation algorithm

Case Studies of Attacks over Adaptive Modulation Based Tactical Software Defined Radios

Modified leaky LMS‐based control strategy for reliable operation of single‐stage three‐phase grid‐tied PV system

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