Wavelet based OFDM system over flat fading channel using NLMS equalization

Sirvi, Sunita; Tharani, Lokesh

doi:10.1109/ccaa.2016.7813951

Cited by 4 publications

(7 citation statements)

References 3 publications

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“…On the other hand, when the value of µ is too high, the adaptive filter becomes unstable. Therefore, it is very important to find a compromise between the speed and stability of the adaptive algorithm convergence [33][34][35].…”

Section: Least Mean Squaresmentioning

confidence: 99%

“…Then, the estimated error value is calculated based on Equation (2). In the last step, the values of the FIR filter weights are updated with respect to the next iteration of Equation 3 [33][34][35].…”

Section: Least Mean Squaresmentioning

confidence: 99%

“…When the input signal consists of high values, it takes more time to reach the lowest possible error value. On the other hand, when the input signal consists of lower values, it will be faster to reach the lowest possible error value [33,36].…”

Section: Normalized Least Mean Squaresmentioning

confidence: 99%

“…Estimation of QR-RLS is determined by Equation (6), where d(n) is a desired signal, − → w T (n) is a weight vector, and x(n) stands for the reference signal. The estimated error e(t) is calculated according to Equation (6) [33,36].…”

Section: Qr Decomposition Based Recursive Least Squaresmentioning

confidence: 99%

“…They concluded that their system reached the highest data rate ever (until 2014) by using a single commercially available RGB-LED in a VLC system. Sirvi and Tharani in 2016 [33] tested NLMS equalization. They concluded that the bit error ratio (BER) was vastly improved by employing NLMS based equalization.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Adaptive Software Defined Equalization Techniques for Indoor Visible Light Communication

Martínek

Danys

Jaroš

2020

Sensors

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This paper focuses on a channel feed-forward software defined equalization (FSDE) of visible light communication (VLC) multistate quadrature amplitude modulation (M-QAM) based system, implemented in the LabVIEW programming environment. A highly modular platform is introduced; the whole experiment is simulated in software and then thoroughly explored and analyzed during practical measurements in the laboratory, simulating real-world situations. The whole platform is based on modified National Instruments software defined radios (NI SDR) and a commercially available Philips light source, often used in Czech government institutions. Three FSDE algorithms were tested: least mean squares (LMS), normalized least mean squares (NLMS), and QR decomposition based RLS (QR-RLS). Based on measurements, QR-RLS provides the best results, improving measured values by up to 10%. The experiments also show that the simulated results are very similar to real measurements, thus proving the validity of the chosen approach. The whole platform manages to improve measured data simply by making changes to the software side of the testing prototype.

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Section: Least Mean Squaresmentioning

confidence: 99%

Section: Least Mean Squaresmentioning

confidence: 99%

Section: Normalized Least Mean Squaresmentioning

confidence: 99%