scholarly journals Study of signal-to-noise ratio evaluation method of the Long Term Evolution signal in terms of ideal and non-ideal symbol synchronization

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Vitaly Kazachkov
Keyword(s):  
Evaluation Method ◽  
Signal To Noise Ratio ◽  
Long Term Evolution ◽  
Signal To Noise ◽  
Symbol Synchronization ◽  
Term Evolution ◽  
Noise Ratio

scholarly journals Estimasi Kanal Sistem OFDM pada Kanal Fading Rayleigh dengan Metode Piece-wise Linear

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Walid Maulana Hadiansyah
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Signal To Noise Ratio ◽  
Long Term Evolution ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Signal To Noise ◽  
Term Evolution ◽  
Noise Ratio

Transmisi data kecepatan tinggi menjadi sorotan masyarakat saat ini karena semakin banyak masyarakat menggunakan teknologi nirkabel pita lebar untuk memenuhi kebutuhan sehari-hari. Long Term Evolution (LTE) masih menjadi teknologi eksisting yang memanfaatkan sistem Orthogonal Frequency Division Multiplexing (OFDM) sebagai solusi penghematan bandwidth. Untuk mempertahankan kualitas data dari distorsi, maka dibutuhkan teknik estimasi kanal. Dengan mengetahui hasil estimasi kanal, maka akan didapatkan solusi untuk meminimalisasi efek distorsi. Respon impuls diasumsikan berupa kanal fading Rayleigh. Estimasi kanal yang dipakai adalah metode estimasi Piece-wise Linear dengan 2 slope. Serangkaian penelitian yang bisa dilakukan setelah estimasi kanal adalah estimasi efek doppler, minimalisasi interferensi antar-simbol, dan efisiensi serta optimalisasi sistem. Dari hasil simulasi menggunakan program Matlab dengan 100 kali iterasi, dapat diambil kesimpulan bahwa semakin besar Signal to Noise Ratio (SNR), semakin kecil error yang terjadi. Nilai rata-rata error estimasi dari SNR=9-40 dB adalah 2.4%-38.2%.

scholarly journals Assessing Stability of Crutch Users by Non-Contact Methods

2021 ◽  
Vol 18 (6) ◽  
pp. 3001
Author(s):  
Achilles Vairis ◽  
Suzana Brown ◽  
Maurice Bess ◽  
Kyu Hyun Bae ◽  
Jonathan Boyack
Keyword(s):  
Signal To Noise Ratio ◽  
Time Derivative ◽  
Assistive Devices ◽  
Signal To Noise ◽  
Physically Disabled ◽  
Significant Difference ◽  
Novice Users ◽  
Noise Ratio ◽  
Physically Disabled People

Enhancing gait stability in people who use crutches is paramount for their health. With the significant difference in gait compared to users who do not require an assistive device, the use of standard gait analysis tools to measure movement for temporary crush users and physically disabled people proves to be more challenging. In this paper, a novel approach based on video analysis is proposed as non-contact low-cost solution to the more expensive alternative with the data collected from processed videos, two values are calculated: the Signal to Noise Ratio (SNR) of acceleration, and the Signal to Noise Ratio of the jerk (time derivative of acceleration), to assess the user’s stability while they walk with crutches. The adopted methodology has been tested on a total of 10 participants. Five are temporary users of assistive devices with one being a long-term user and the other four novice users, and five are disabled participants who use those assistive devices permanently. Preliminary results show differences between novice users, long-term users, and physically disabled users. The approach is promising and could improve the assessment of crutch user stability, allowing for the correction of gait for individuals while using an inexpensive non-contact setup and preventing unnecessary falls.

scholarly journals Eficiencia de sistemas multiantena MU–MIMO por simulaciones de radiopropagación

2017 ◽  
Vol 11 (1) ◽  
pp. 55-62
Author(s):  
Javier Enrique Arévalo Peña
Keyword(s):  
Reference Signal ◽  
Long Term Evolution ◽  
Signal To Noise ◽  
3Gpp Lte ◽  
Term Evolution ◽  
Received Power ◽  
La Red

El presente artículo tiene como propósito realizar la descripción de los resultados de simulación de radiopropagación con una antena MU{MIMO (4x4) en una red LTE (del inglés Long Term Evolution), con el fin de establecer su eciencia respecto a una antena estándar. En esta vía, se emplea la herramienta de diseño de redes inalámbricas ICS Designer en la cartografía digital de alta resolución en un escenario urbano de la ciudad de Bogotá D.C., Colombia. Se utiliza el modelo 3GPP LTE en la simulación de la red LTE y se analizan los parametros RSRP (del inglés, Reference Signal Received Power), RSRQ (del inglés, Reference Signal Recieved Quality), SNIR (del inglés, Signal to Noise and Interference Ratio) rendimiento (Throughput) y QCI (del inglés, QoS Class Identier). Se evidencian, como consecuencia de los resultados, ventajas de las antenas MU-MIMO.

scholarly journals BIT ERROR RATE ANALYSIS IN DIFFERENT TERRAINS FOR LTE

2019 ◽  
Vol 7 (7) ◽  
pp. 331-339
Author(s):  
Dilshad Mahjabeen ◽  
Moshiur Rahman Tarafder ◽  
T Saikat Ahmed
Keyword(s):  
Rural Area ◽  
Bit Error Rate ◽  
Error Rate ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Rate Analysis ◽  
Receiving Antenna ◽  
Noise Ratio ◽  
Clear Idea

Focus of this paper is mainly evaluating the performance of Long Term Evolution (LTE) system in different terrains such as urban, suburban and rural area. The performance parameters such as, Bit Error Rate (BER) and the Data Throughput are reported in terms of Signal to Noise Ratio (SNR). The system parameters taken into consideration are signal to noise ratio (SNR), number of receiving antenna (RxAn), reference channel and duplex mode. All of the simulations were performed in MATLAB, version 2014a simulink. The results are presented in table and graph which gives clear idea of the effect of environment on signal and receiver sensitivity. Also bit-error-rate, an important parameter in case of receiving signal, is analyzed with respect to SNR values. A comparative analysis of bit-error-rate is performed between three areas for same conditions which proves that LTE signal is well suited in a rural area than that of a suburban and urban area.

scholarly journals A MODWT-Based Algorithm for the Identification and Removal of Jumps/Short-Term Distortions in Displacement Measurements Used for Structural Health Monitoring

IoT ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 60-72
Author(s):  
Davi V. Q. Rodrigues ◽  
Delong Zuo ◽  
Changzhi Li
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Signal To Noise Ratio ◽  
Structural Condition ◽  
Signal To Noise ◽  
Short Term ◽  
Structural Health ◽  
Noise Ratio ◽  
Displacement Measurements

Researchers have made substantial efforts to improve the measurement of structural reciprocal motion using radars in the last years. However, the signal-to-noise ratio of the radar’s received signal still plays an important role for long-term monitoring of structures that are susceptible to excessive vibration. Although the prolonged monitoring of structural deflections may provide paramount information for the assessment of structural condition, most of the existing structural health monitoring (SHM) works did not consider the challenges to handle long-term displacement measurements when the signal-to-noise ratio of the measurement is low. This may cause discontinuities in the detected reciprocal motion and can result in wrong assessments during the data analyses. This paper introduces a novel approach that uses a wavelet-based multi-resolution analysis to correct short-term distortions in the calculated displacements even when previously proposed denoising techniques are not effective. Experimental results are presented to validate and demonstrate the feasibility of the proposed algorithm. The advantages and limitations of the proposed approach are also discussed.

Automatic Phase‐Picking Method for Detecting Earthquakes Based on the Signal‐to‐Noise‐Ratio Concept

2019 ◽  
Vol 91 (1) ◽  
pp. 334-342
Author(s):  
Jihua Fu ◽  
Xu Wang ◽  
Zhitao Li ◽  
Hao Meng ◽  
Jianjun Wang ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Ratio Method ◽  
Mean Deviation ◽  
Signal To Noise ◽  
Short Term ◽  
Low Snr ◽  
Automatic Phase ◽  
Noise Ratio ◽  
Automatic Phase Picking

Abstract The automatic phase‐picking detection of earthquakes is a challenge under the background of big data and strong noise circumstances. The short‐term average/long‐term average (STA/LTA) ratio is widely used to detect earthquake due to its simplicity and robustness. However, STA/LTA‐based methods may not perform well with noisy data. Based on the signal‐to‐noise‐ratio (SNR) concept, a short‐term power/long‐term power (STP/LTP) ratio method is proposed. The characteristic function and the detection thresholds of the STP/LTP method are given physical meanings. Through a sample analysis, the STP/LTP detection results of both the P and S phases are better than the results of the STA/LTA by means of mean deviation, standard deviations, distributions of detection results, error rate, and missed rate on different SNR levels. In general, the STP/LTP method inherits the simple characteristics of the STA/LTA method, and it is suitable for phase picking of low‐SNR seismic data.

Transfer of heat, fresh water and nutrients through the seasonal thermocline

1975 ◽  
Vol 55 (2) ◽  
pp. 261-274 ◽  
Author(s):  
R. D. Pingree ◽  
Linda Pennycuick
Keyword(s):  
Standard Deviation ◽  
Fresh Water ◽  
Annual Variation ◽  
Signal To Noise Ratio ◽  
Turbulent Transport ◽  
Signal To Noise ◽  
Seasonal Thermocline ◽  
Annual Range ◽  
Noise Ratio

This paper estimates the turbulent transport of heat, fresh water and nutrients through the seasonal thermocline. In order to obtain a representative estimate of the annual variation it is necessary to average data obtained at a single position over a number of years. The number of years of sampling required depends on the particular parameter being studied. This can be seen by comparing the annual variation with the standard deviation, σ, for a specific month. This is analogous to the signal to noise ratio. For example, the annual range of temperature (or signal) is about 8°C for the water of the western English Channel. The variability of temperature in the same area (or noise) is about o.6°C. This figure is the standard deviation for the temperature obtained in a specific month at a fixed depth when data from a large number of different years are available. This variability can be attributed to a number of causes, to list a few; horizontal patchiness, local weather, advection, long term climatic changes. Hence for temperature the signal to noise ratio is about 13 and the annual pattern of events will clearly be established on the basis of monthly values obtained at a position during a single year.

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