Seamless data-rate change using punctured convolutional codes for time-varying signal-to-noise ratio

2002 ◽  
Author(s):  
Ying Feria ◽  
Kar-Ming Cheung
Keyword(s):  
Signal To Noise Ratio ◽  
Convolutional Codes ◽  
Data Rate ◽  
Rate Change ◽  
Time Varying ◽  
Signal To Noise ◽  
Punctured Convolutional Codes ◽  
Noise Ratio

scholarly journals Time-Variant Front-End Read-Out Electronics for High-Data-Rate Detectors

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1528
Author(s):  
Leila Sharifi ◽  
Marcello De Matteis ◽  
Hubert Kroha ◽  
Robert Richter ◽  
Andrea Baschirotto
Keyword(s):  
Signal To Noise Ratio ◽  
Data Rate ◽  
Event Data ◽  
Noise Performance ◽  
Signal To Noise ◽  
Rate Enhancement ◽  
Noise Ratio ◽  
Edge Method ◽  
Time Invariant ◽  
Threshold Technique

The foreseen incremental luminosity for near-future high-energy physics experiments demands evolution for the read-out electronics in terms of event data-rate. However, the filtering necessary to reject noise and meet the signal-to-noise-ratio requirements imposes a restriction on the operational speed of the conventional read-out electronics. The stringent trade-off between signal-to-noise-ratio and the event data-rate originates from the time-invariant behavior of the conventional systems. In this paper, the cases of time-variant systems are addressed, studying a benchmark with the RC-CR shaping function used in time-over-threshold methods. It was demonstrated that the time-variant systems enable a higher data-rate for the given noise performance. Moreover, taking advantage of time-variant systems, the proposed rising-edge method enables further data-rate enhancement with respect to the traditional time-over-threshold technique by reading the data from the rising edge of the analog output waveform. A comparison between the conventional time-invariant time-over-threshold technique, its time-variant equivalent and rising-edge method confirms the better performance of the latter one in terms of data-rate enhancement for a target noise performance. Moreover, design challenges for time-variant systems are briefly discussed, considering the ATLAS Monitored Drift Tube detector as a design case.

scholarly journals Model Kanal 5G dengan Pengaruh Kelembapan pada Frekuensi 3,3 GHz dan Bandwidth 99 MHz Berbasis Convolutional Codes

2021 ◽  
Vol 9 (4) ◽  
pp. 878
Author(s):  
RENI DYAH WAHYUNINGRUM ◽  
KHOIRUN NI’AMAH ◽  
SOLICHAH LARASATI
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Channel Model ◽  
Signal To Noise Ratio ◽  
Convolutional Codes ◽  
Cyclic Prefix ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Signal To Noise ◽  
Power Delay Profile ◽  
Noise Ratio

ABSTRAKGenerasi telekomunikasi kelima (5G) diterapkan pada 2021 dengan frekuensi tinggi yang menyebabkan redaman yang besar dibandingkan pita sub-1 GHz. Penelitian ini mengkaji sistem 5G dengan frekuensi operasi 3,3 GHz dan bandwidth 99 MHz berdasarkan spesifikasi 5G dari Cyclic Prefix-Orthogonal Frequency Division Multiplexing (CP-OFDM) numerologi μ = 1 menggunakan parameter lingkungan yang diukur secara langsung di kota Bandung. Penelitian ini menemukan bahwa model kanal 5G dengan pengaruh kelembapan maksimum memiliki power delay profile (PDP) 9 path dengan nilai daya yang lebih kecil dan outage performances (𝑅>𝐶) yang lebih buruk dengan gap sebesar 0,3 dB dibandingkan dengan pengaruh kelembapan minimum. Hasil penelitian menunjukkan bahwa penggunaan convolutional codes dapat membantu menghemat Signal to Noise Ratio (SNR) dengan gap sebesar 3 dB. Hasil dari penelitian ini diharapkan dapat memberikan kontribusi bagi perkembangan komunikasi nirkabel 5G di Indonesia.Kata kunci: 5G, model kanal, convolutional codes, PDP, FER, BER. ABSTRACTThe fifth generation of telecommunications (5G) implemented in 2021, where high frequency which causes a large attenuation compared to the sub-1 GHz band. This research examines a 5G system with an operating frequency of 3.3 GHz and a bandwidth of 99 MHz based on the 5G specification of the Cyclic Prefix - Orthogonal Frequency Division Multiplexing (CP-OFDM) numerology μ = 1 using environmental parameters measured directly in Bandung, Indonesia. This research shows that the 5G channel model under maximum humidity has a 9 power delay profile (PDP) with a smaller power value and worse outage performances (𝑅>𝐶) with a gap of 0.3 dB compared to the effect of minimum humidity. The results showed that the use of convolutional codes can save the Signal to Noise Ratio (SNR) with gap of 3 dB. The results of this research are expected to contribute to the development of 5G wireless communications in Indonesia.Keywords: 5G, channel model, convolutional codes, PDP, FER, BER.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

1981 ◽  
Vol 39 ◽  
pp. 226-227
Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler
Keyword(s):  
Signal To Noise Ratio ◽  
Carbon Support ◽  
Electronic System ◽  
Optic Axis ◽  
Hollow Cone ◽  
Signal To Noise ◽  
Bright Field ◽  
Noise Ratio ◽  
Single Field ◽  
Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

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