FPGA implementation of an indoor broadband power line channel emulator

Dulay, Ann E.; Sze, Ryan; Tan, Aileen; Huang, Yu-Hsiang; Yap, Roderick; Materum, Lawrence

doi:10.1109/infoc.2017.8001678

Cited by 7 publications

(5 citation statements)

References 10 publications

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“…Through this data, modem and other PLC interfacing equipment can be verified and tested. Some of the notable studies on channel emulation and generation are listed in [12], [13], [14], [15], [16], [17], and [18].…”

Section: Basic Conceptsmentioning

confidence: 99%

Weighted-Probability Random Number Generator for PLC Channel Transfer Function Generation

Garcia¹,

Dulay²,

Oseña³

2020

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The concept of randomization shows many realistic scenarios and has enormous applications in everyday life. However, existing random number generators have poor adaptability when representing some of the actual occurrences in natural environment, such as in biology, mobile communications, and even electrical behavior. For PLC channel transfer function generation, biased sampling of the channel is more applicable. This paper proposes a weighted-probability method to generate random numbers to emulate the real-world variations of a power line communications channel. Existing PLC channel emulator can mimic the random behavior of the channel, altered by several parameters such as cable length, cable type, presence of loads, and ejecting different noises. However, the scenario of integrating the effect of changing the state of the loads and channel variation due to time is not well represented in the normal random channel generation. The best concept for this scenario is the weighted random number generator (WRNG). This work developed an algorithm in Matlab and VHDL, implemented it in FPGA and integrated it with an existing PLC channel emulator. The emulator is implemented using Kintex-7 FPGA. In this study, ten different weights corresponding to the probability of occurrence of the actual household appliances and eighty transfer functions were used as inputs to the program. The randomness and periodicity of the WRNG are tested and passed the Runs test. Autocorrelation and histograms are used to determine the correct implementation of the weights.

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Section: Basic Conceptsmentioning

confidence: 99%

Weighted-Probability Random Number Generator for PLC Channel Transfer Function Generation

Garcia¹,

Dulay²,

Oseña³

2020

Self Cite

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“…This was also the reason why numerous errors were seen in which 1 finger raised up in an image displayed a number 4 on the results. For sending the data channel impulse can be used via channel line emulator [30,31,32,33].…”

Section: Analysis Of Datamentioning

confidence: 99%

A Study on Number Gesture Recognition using Neural Network

Africa¹

2019

IJATCSE

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A natural way of counting is with the use of hands. As hand gesture recognition is becoming more recognized through its growing applications, this paper focuses on recognizing the number shown by the hand gesture. The code used in this study is developed by Makeshkha. This system uses an extraction feature which extracts the parts of the image of the hand gesture which is to be used by the system, and a neural network. This system has been trained for numerous iterations with the use of different input images. The network is then used in the recognition of hand number gestures. The system works by first prompting the user for an image to be used for input. The next process is the extraction of the features which goes by the reprocessing of the image through the removal or addition of noise in order to extract the required shape and form of the hand. Lastly, the Artificial Neural Network then scans the database for similarities in the image, with regards to the extracted features, from the input image. The experimental results of the study showed that the system has a considerable percentage of accuracy in the recognition of hand number gestures.

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“…The instructions are written or being programmed into the microcontroller after compilation will be able to let the system respond to the inputs from the user, perform logical operations, and output the corresponding result of the system into a display module. Database monitoring is also important [19,20] This research follows the database configurations in the studies of: [21,22,23].…”

Section: Monitoring Systemmentioning

confidence: 99%

Implementation of Solar Electricity and Water Filtration systems for a Smart House

Africa¹,

Cruz²,

Dilla³

et al. 2019

IJRTE

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Abstract: The use of fossil fuels as a source of energy is one of the problems faced by the government nowadays. These cause harmful effects not only on humans, but also on the environment. Another problem is the supply and sanitation of water. The supply is becoming limited especially in rural areas and the sanitation is not being assured. In this research paper, the uses of solar energy and water as alternative sources are discussed. This research implemented solar electricity and water filtration systems for home use. Through these systems, the user can save a minimum of 20% of specific electricity wattage and save a certain amount of filtered water depending on the amount of rainwater collected. The materials used are Solar Panel, AGM Battery, Grid-tie Inverter, Charge Controller, Reverse Osmosis System, LCD, gizDuino+, ATMEGA 324P, and various components like resistors, transistors, and wires that made up the monitoring system's circuit.

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FPGA implementation of an indoor broadband power line channel emulator

Cited by 7 publications

References 10 publications

Weighted-Probability Random Number Generator for PLC Channel Transfer Function Generation

Weighted-Probability Random Number Generator for PLC Channel Transfer Function Generation

A Study on Number Gesture Recognition using Neural Network

Implementation of Solar Electricity and Water Filtration systems for a Smart House

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