SANC: Stochastic approach for noise cancellation in GSM signals

Rekha, N. Rukma; Jabeem, Fathima

doi:10.1109/icatcct.2015.7456974

Cited by 2 publications

(3 citation statements)

References 15 publications

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“…The proposed work is a continuation of our prior implementation [34,35] where an enhancement has been carried out by constructing an integrated model in order to emphasize on the noise-related problem over GSM signal. The overall architecture of the proposed system is as follows in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

A novel and integrated architecture for identification and cancellation of noise from GSM signal

Rekha¹,

Jabeen

2019

IJECE

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There are multiple reasons for the evolution as well as the presence of noise over transmitted GSM signal. In spite of various approaches towards noise cancellation techniques, there are less applicable techniques for controlling noise in acoustic GSM signal. Therefore, the proposed manuscript presents an integrated modelling which performs modelling of noise identification that could significantly assist in successful noise cancellation. The proposed system uses three different approach viz. i) stochastic based approach for noise modelling, ii) analytical-based approach where allocated power acts as one of the prominent factors of noise, and iii) wavelet-based approach for effective decomposition of GSM signal for assisting better noise cancellation technique followed by better retention of signal quality. Simulated in MATLAB, the study outcome shows that it offers a cost-effective implementation, A Practical Approach for Noise identification, and Effective Noise Cancellation with Signal quality retention. The proposed system offers approximately 24% of enhancement in noise reduction as compared to any existing digital filters with 1.6 seconds faster in processing speed.

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Section: Introductionmentioning

confidence: 99%

A novel and integrated architecture for identification and cancellation of noise from GSM signal

Rekha¹,

Jabeen

2019

IJECE

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“…He improved the SNR (signal to noise ratio) and found the sensor value, validity and this method could not be used in direct processing. Rekha N and Fathima Jabeem (2015) proposed a stochastic approach for noise cancellation (SANC) in GSM signals. Their study performed cancellation of the noise by incorporating white Gaussian noise and stored it in a matrix format.…”

Section: Introductionmentioning

confidence: 99%

“…The last pattern of the signal values was the matrix form. The SANC was capable of eliminating the noises [24].…”

Section: Introductionmentioning

confidence: 99%

Cloud Based WiFi Multi-Sensor Network

Yoddumnern

Chaisricharoen²,

Yooyativong³

2018

Int. J. Onl. Eng.

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<p class="0abstract">A WiFi technology was the basis of the Internet of Things (IoT) and many popularity of the wireless communication in the social network. A smart device used any kinds of the detectors all of the analog and digital sensor. This study simulates on the scope of the home security system (HSS). There used three types of sensor; a temperature sensor, smoke-CO, and PIR sensor. This study aims to design a multi-sensor node. All of the sensors are connected on a microcontroller unit (MCU) with the general purpose input output (GPIO). After the connection, there got invalid multi-sensor data. This experiment tried to run over ten times. There appeared some invalid when the processor startup. First, the temperature sensor did not work. Second, the smoke-CO sensors read an invalid value there were higher than the actual. This problem can solve the situation by the sensor calibration methodology—to set the calibration time with the dynamic time follow up on the GPIO function of each sensor and self-calibrate by the finite impulse response (FIR) filter in the part of setup portion. When the system was running for a long time this should take the invalid data. There were high and low from the actual and there got the difference value suddenly a swinging value. During the system was running there had some noise and the heat collected on the device. There got the invalid value. This error is solved by the Full Scale Kalman Filter (FSKF) to fill and estimate the right value. Next, there used the OFF-Mode to save the power consumption and do not send sensor data to the Cloud all time. This method helps the device will be run as long time and work in long life. Finally, there got a high-performance WiFi multi-sensor network.</p>

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SANC: Stochastic approach for noise cancellation in GSM signals

Cited by 2 publications

References 15 publications

A novel and integrated architecture for identification and cancellation of noise from GSM signal

A novel and integrated architecture for identification and cancellation of noise from GSM signal

Cloud Based WiFi Multi-Sensor Network

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