scholarly journals Analysis of different digital filters for received signal strength indicator

2019 ◽  
Vol 8 (3) ◽  
pp. 970-977
Author(s):  
Rafhanah Shazwani Rosli ◽  
Mohamed Hadi Habaebi ◽  
Md. Rafiqul Islam

Due to high demand in Internet of Things applications, researchers are exploring deeper alternative methods to provide efficiency in terms of application, energy, and cost among other factors. A frequently used technique is the Received Signal Strength Indicator value for different Internet of Things applications. It is imperative to investigate the digital signal filter for the Received Signal Strength Indicator readings to interpret it into more reliable data. A contrasting analysis of three different types of digital filters is presented in this paper, namely: Simple Moving Average filter, Alpha Trimmed Mean filter and Kalman filter. There are three criteria used to observe the performance of these digital filters which are noise reduction, data proximity and delays. Based on the criteria, the choice of digital signal processing filter can be determined in accordance with its implementations in [ractice. For example, Alpha-Trimmed Meanfilter is shown to be more efficient if used in the pre-processing of Received Signal Strength Indicator readings for physical intrusion detection due to its high data proximity. Hence, this paper illustrates the possibilities of the use of Received Signal Strength Indicator in different Internet of Things applications given a proper choice of digital signal processing filter.

Author(s):  
Amer T Saeed ◽  
Zaid Raad Saber ◽  
Ahmed M. Sana ◽  
Musa A. Hameed

<p><a name="_Hlk536186602"></a><span style="font-size: 9pt; font-family: 'Times New Roman', serif;">Unwanted signals or noise signals in sound files are considered one of the major challenges and issues for a thousand users. It is impossible to reduce or remove these noise signals without identifying their types and ranges. Therefore, to address one of the big problems in the digital or analogue communication, which is noise signals or unwanted signals, an adaptive selection method and noise signal removal algorithm are proposed in this research. The proposed algorithm is done through specifying the types of undesirable signals, frequency, and time range, then utilizing digital signal processing system which includes design several types of digital filters based on the types and numbers of unwanted signals. Four digital filters are used in this research to remove noise signals from the sound file by implementing the proposed algorithm using Matlab Code. Results show that our proposed algorithm was done successfully and the whole noise signals were removed without any negative consequence in the output sound signal. </span><span style="font-family: 'Times New Roman', serif; font-size: 9pt;">Unwanted signals or noise signals in sound files are considered one of the major challenges and issues for a thousand users. It is impossible to reduce or remove these noise signals without identifying their types and ranges. Therefore, to address one of the big problems in the digital or analogue communication, which is noise signals or unwanted signals, an adaptive selection method and noise signal removal algorithm are proposed in this research. The proposed algorithm is done through specifying the types of undesirable signals, frequency, and time range, then utilizing digital signal processing system which includes design several types of digital filters based on the types and numbers of unwanted signals. Four digital filters are used in this research to remove noise signals from the sound file by implementing the proposed algorithm using Matlab Code. Results show that our proposed algorithm was done successfully and the whole noise signals were removed without any negative consequence in the output sound signal.</span></p>


2020 ◽  
Vol 10 (24) ◽  
pp. 9052
Author(s):  
Pavel Lyakhov ◽  
Maria Valueva ◽  
Georgii Valuev ◽  
Nikolai Nagornov

This paper proposes new digital filter architecture based on a modified multiply-accumulate (MAC) unit architecture called truncated MAC (TMAC), with the aim of increasing the performance of digital filtering. This paper provides a theoretical analysis of the proposed TMAC units and their hardware simulation. Theoretical analysis demonstrated that replacing conventional MAC units with modified TMAC units, as the basis for the implementation of digital filters, can theoretically reduce the filtering time by 29.86%. Hardware simulation showed that TMAC units increased the performance of digital filters by up to 10.89% compared to digital filters using conventional MAC units, but were associated with increased hardware costs. The results of this research can be used in the theory of digital signal processing to solve practical problems such as noise reduction, amplification and suppression of the frequency spectrum, interpolation, decimation, equalization and many others.


2017 ◽  
Vol 36 (1) ◽  
Author(s):  
Wesley Becari ◽  
Rodrigo B. dos Santos ◽  
André B. Carlos ◽  
Rafael A. Biliatto ◽  
Henrique E. M. Peres

2013 ◽  
Vol 684 ◽  
pp. 653-656
Author(s):  
Yu Jian Du ◽  
Zu Bin Chen ◽  
Teng Yu ◽  
Yang Yang

With the information era and the advent of the digital world, digital signal processing has become extremely important in today's one of the disciplines and technical fields.Digital signal processing in seismic signal ,communications, voice, image, automatic control radar, and other fields has been widely used.In this paper,I design several kind of FIR digital filters based on virtual instrument to solve the problem that signal noise reduction.


2019 ◽  
Vol 15 (1) ◽  
pp. 47 ◽  
Author(s):  
Eko Murdyantoro ◽  
Imron Rosyadi ◽  
Hilmi Septian

Dalam sistem Internet of things (IoT), berbagai macam obyek fisik disekitar manusia akan disensor dan direpresentasikan menjadi data digital untuk mendukung produktifitas manusia. Sensor dan aktuator sebagai <em>node</em> akan terhubung satu sama lain untuk diproses oleh sistem cerdas. Ada beberapa pilihan teknologi bagi pengembang sistem IoT untuk mengimplementasikan konektivitas antar <em>node</em> tersebut. Teknologi konektivitas nirkabel tersebut antara lain dengan modul GSM, wifi, bluetooth LE, Zigbee, NB-IoT, Sigfox dan LoRa yang menjadi topik studi ini. Teknologi LoRa dikembangkan terutama diproyeksikan sebagai infrastruktur konektifitas nirkabel pada sistem IoT. Beberapa potensi kelebihan fitur LoRa yang diklaim LoRa Alliance antara lain berdaya rendah; dapat mendukung konektifitas IoT skala luas sampai ribuan <em>node</em> dalam satu sel; dan termasuk dalam kategori jangkauan radio jarak jauh. Studi ini bertujuan untuk menguji performansi jarak jangkauan radio dari modul LoRa OLG01 pada sistem IoT yang dikembangkan pada frekuensi ISM 915MHz di atmosfer Indonesia. Dalam studi ini konfigurasikan <em>node</em> yang terhubung ke <em>gateway</em> agar dapat terhubung ke internet menjadi sistem IoT dengan set SF=7 dan BW= 125 kHz. Pembahasan dibatasi pada pengujian performansi jarak jangkauan dengan parameter RSSI (Received Signal Strength Indicator) dan jarak saat LOS (<em>line of sight</em>) dan non LOS (ada halangan). Jangkauan LoRa saat ini yang berhasil diukur sekitar radius 400m. Jarak jangkauan ini masih belum sesuai dengan spesifikasi yang diharapkan yaitu sampai radius 5 km, sehingga masih perlu dicari solusi dan konfigurasi yang lebih optimal


2021 ◽  
Vol 4 (2(60)) ◽  
pp. 6-11
Author(s):  
Ruslan Petrosian ◽  
Vladyslav Chukhov ◽  
Arsen Petrosian

The object of research is the process of digital signal processing. The subject of research is methods of synthesis of digital filters with a finite impulse response based on a genetic algorithm. Digital filtering is one of the tasks of digital signal processing. FIR filters are always stable and provide a constant group delay. There are various methods for synthesizing digital filters, but they are all aimed at synthesizing filters with a direct structure. One of the most problematic areas of a digital filter with a direct structure in digital processing is the high sensitivity of the filter characteristics to inaccuracies in setting the filter coefficients. Genetic algorithm-based filter synthesis methods use an ideal filter as the approximated filter. This approach has a number of disadvantages: it complicates the search for an optimal solution; computation time increases. The study used random search method, which is the basis of genetic algorithm (used for solving optimization problems); theory of digital filtering in filter analysis; numerical methods for modeling in a Python program. Prepared synthesis method FIR filter with the cascade structure, which is less sensitive to the effect of finite bit width. Computation time was reduced. This is due to the fact that the proposed method searches for the most suitable filter coefficients based on a genetic algorithm and has a number of features, in particular, it is proposed to use a piecewise-linear function as an approximated amplitude-frequency response. This makes it possible to reduce the number of populations of the genetic algorithm when searching for a solution. The synthesis of an FIR filter with a cascade structure based on a genetic algorithm showed that for a 24-order filter it took about 30–40 generations to get the filter parameters close to the optimal values. In comparison with classical methods of filter synthesis, the following advantages are provided: calculations of the coefficients of a filter with a cascade structure directly, the possibility of optimizing coefficients with limited bit depth.


2020 ◽  
Vol 10 (9) ◽  
pp. 2010-2015
Author(s):  
Meisu Zhong ◽  
Yongsheng Yang ◽  
Yamin Zhou ◽  
M. Octavian Postolache ◽  
M. Chandrasekar ◽  
...  

Speech processing subject primarily depends on the digital signal processing (DSP) methods, such as convolution, discrete Fourier transform (DFT), fast Fourier transforms (FFT), finite impulse response (FIR) and infinite impulse response (IIR) filters, FFT recursive and non-recursive digital filters, FFT processing, random signal theory, adaptive filters, upsampling and downsampling, etc. Recursive and non-recursive digital filters are primarily deployed to absorb the signal of interest signals and to block the unwanted signals (noise). Broadly, low-pass, high-pass, band-pass, and band-stop filters are implemented for filtering functions. In frequent, the DSP theories can be used for further biomedical engineering domains like biomedical imaging (MRI, ultrasound, CT, X-ray, PET) and genetic signal analysis-cum-processing too. In this article, the experiments such as voiced/unvoiced detection, formants estimation using FFT and spectrograms, pitch estimation and tracking and yes/no sound classification are used. Also, the analysis of normal/abnormal heart sound signals using simple energy computation and the zero-crossing rate and their results are obtained. For the entire study, the Matlab R2018a tool is used to obtain the simulation results. At last, the criticism, feedbacks, comments, reactions from the student are detailed for the exceptional development of the course.


1998 ◽  
Vol 6 (1) ◽  
pp. 97-104 ◽  
Author(s):  
M. Känsäkoski ◽  
O. Voutilainen ◽  
T. Seppänen

On-line near infrared (NIR) analysers are used widely for quantitative composition measurements in real-time process control systems. The accuracy and repeatability of the measurements are amongst the most important factors when evaluating the total performance of these analysers, but the lower detection limit is often limited by noise in the measurement signal. There are two major alternatives for reducing noise in an optical analyser: prevention of noise contamination and post-processing of the signal by filtering. In the second alternative, the measurement signal can be post-processed by digital filtering techniques, for example, to enhance the desired signal component. Although digital signal processing (DSP) technology offers many advantages for on-line process measurements, the behaviour of the signal must be understood thoroughly before a successful application of this technology can be developed. A digital filtering technique called matched filter was used in an experimental set-up. The performance of this filter was compared to an analog filtering of a pulse shaped signal. Experimental data were collected and filtered with a novel digital spectrometer which consists of a modulated light source, a spectrograph, a linear array detector and the analog and digital signal processing electronics needed to control and filter the signal. In this case the matched filter gave a clear improvement of 2.2–4.6 dB in the signal-to-noise ratio (SNR) relative to an analog lock-in amplifier. Among the other advantages afforded by digital filters are that they are programmable, easy to design, test and implement on a PC and do not suffer from drift. Also digital filters are extremely stable with respect to both time and temperature and versatile in their ability to process signals in a variety of ways.


2012 ◽  
Vol 214 ◽  
pp. 717-720
Author(s):  
Wei Wang

DSP chip is especially fit for digital signal processing. Its main application is realizing all kinds of digital signal processing arithmetic such as clove hitch correlation, all kinds of transforms etc. Realizing digital filters with DSP is an important application. The paper discusses the filter’s software realization based on TMS320C5410 and finished the hardware systems of noise-restraining.The main works accomplished are as following: realization of FIR filter with window function, and realization on TMS320C5410 chip, the result of experiment to make clear.


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