scholarly journals Signal-to-noise ratio estimation algorithm for adaptive coding and modulation in advanced digital video broadcasting–radar cross section satellite systems

2012 ◽  
Vol 6 (11) ◽  
pp. 1587 ◽  
Author(s):  
A. Ijaz ◽  
A.B. Awoseyila ◽  
B.G. Evans
Keyword(s):  
Cross Section ◽  
Digital Video ◽  
Signal To Noise Ratio ◽  
Estimation Algorithm ◽  
Radar Cross Section ◽  
Ratio Estimation ◽  
Signal To Noise ◽  
Digital Video Broadcasting ◽  
Satellite Systems ◽  
Video Broadcasting

scholarly journals Improved signal-to-noise ratio estimation algorithm for asymmetric pulse-shaped signals

2015 ◽  
Vol 9 (14) ◽  
pp. 1788-1792 ◽  
Author(s):  
Huaizong Shao ◽  
Wuling Liu ◽  
Di Wu ◽  
Xiaoli Chu ◽  
Yang Li
Keyword(s):  
Signal To Noise Ratio ◽  
Estimation Algorithm ◽  
Ratio Estimation ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Asymmetric Pulse

scholarly journals A Low-Signal-to-Noise Ratio Estimation Algorithm for Multipath Channels

2020 ◽  
Vol 25 (2) ◽  
pp. 253-258
Author(s):  
Baohai Yang ◽  
Quanhui Ren ◽  
Haisheng Li ◽  
Junkang Song
Keyword(s):  
Signal To Noise Ratio ◽  
Estimation Algorithm ◽  
Multipath Channels ◽  
Ratio Estimation ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals Signal-to-Noise Ratio Estimation Algorithm for Advanced DVB-RCS Systems

2012 ◽  
Vol 58 (4) ◽  
pp. 603-608 ◽  
Author(s):  
Ayesha Ijaz ◽  
Adegbenga B. Awoseyila ◽  
Barry G. Evans
Keyword(s):  
Signal To Noise Ratio ◽  
Estimation Algorithm ◽  
Ratio Estimation ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals Signal-to-noise Ratio Study on Pipelined Fast Fourier Transform Processor

2018 ◽  
Vol 7 (2) ◽  
pp. 230-235
Author(s):  
S. L. M. Hassan ◽  
N. Sulaiman ◽  
S. S. Shariffudin ◽  
T. N. T. Yaakub
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Signal To Noise Ratio ◽  
Data Communication ◽  
Digital Signal ◽  
Signal To Noise ◽  
Digital Video Broadcasting ◽  
Video Broadcasting ◽  
Fft Processor ◽  
Noise Ratio

Fast Fourier transform (FFT) processor is a prevailing tool in converting signal in time domain to frequency domain. This paper provides signal-to-noise ratio (SNR) study on 16-point pipelined FFT processor implemented on field-programable gate array (FPGA). This processor can be used in vast digital signal applications such as wireless sensor network, digital video broadcasting and many more. These applications require accuracy in their data communication part, that is why SNR is an important analysis. SNR is a measure of signal strength relative to noise. The measurement is usually in decibles (dB). Previously, SNR studies have been carried out in software simulation, for example in Matlab. However, in this paper, pipelined FFT and SNR modules are developed in hardware form. SNR module is designed in Modelsim using Verilog code before implemented on FPGA board. The SNR module is connected directly to the output of the pipelined FFT module. Three different pipelined FFT with different architectures were studied. The result shows that SNR for radix-8 and R4SDC FFT architecture design are above 40dB, which represent a very excellent signal. SNR module on the FPGA and the SNR results of different pipelined FFT architecture can be consider as the novelty of this paper.

Cross-layer packet scheduler for QoS support over Digital Video Broadcasting-Second Generation broadband satellite systems

2012 ◽  
Vol 27 (10) ◽  
pp. 2063-2082 ◽  
Author(s):  
Elizabeth Rendon-Morales ◽  
Jorge Mata-Díaz ◽  
Juanjo Alins ◽  
Jose L. Muñoz ◽  
Oscar Esparza
Keyword(s):  
Digital Video ◽  
Second Generation ◽  
Cross Layer ◽  
Digital Video Broadcasting ◽  
Satellite Systems ◽  
Video Broadcasting ◽  
Packet Scheduler

Frame-Level Signal-to-Noise Ratio Estimation Using Deep Learning

2020 ◽  
Author(s):  
Hao Li ◽  
DeLiang Wang ◽  
Xueliang Zhang ◽  
Guanglai Gao
Keyword(s):  
Deep Learning ◽  
Signal To Noise Ratio ◽  
Ratio Estimation ◽  
Signal To Noise ◽  
Noise Ratio

Quantization Algorithms in Healthcare Information Telematics Using Wireless Interactive Services of Digital Video Broadcasting.

2020 ◽  
Vol 13 ◽  
Author(s):  
Konstantinos Kardaras ◽  
George I. Lambrou ◽  
Dimitrios Koutsouris
Keyword(s):  
Data Compression ◽  
Data Transmission ◽  
Digital Video ◽  
Digital Television ◽  
End User ◽  
Digital Video Broadcasting ◽  
New Era ◽  
Video Broadcasting ◽  
Television Network ◽  
Interactive Services

Background: In the new era of wireless communications new challenges emerge including the provision of various services over the digital television network. In particular, such services become more important when referring to the tele-medical applications through terrestrial Digital Video Broadcasting (DVB). Objective: One of the most significant aspects of video broadcasting is the quality and information content of data. Towards that end several algorithms have been proposed for image processing in order to achieve the most convenient data compression. Methods: Given that medical video and data are highly demanding in terms of resources it is imperative to find methods and algorithms that will facilitate medical data transmission with ordinary infrastructure such as DVB. Results: In the present work we have utilized a quantization algorithm for data compression and we have attempted to transform video signal in such a way that would transmit information and data with a minimum loss in quality and succeed a near maximum End-user approval. Conclusions: Such approaches are proven to be of great significance in emergency handling situations, which also include health care and emergency care applications.

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