scholarly journals Cross-layer optimization technology for wireless network multimedia video

2020 ◽  
Vol 44 (4) ◽  
pp. 582-588
Author(s):  
W. Xia
Keyword(s):  
Wireless Network ◽  
Signal To Noise Ratio ◽  
Delivery Rate ◽  
Cross Layer ◽  
Signal To Noise ◽  
Packet Delivery ◽  
Cross Layer Optimization ◽  
Transmission Quality ◽  
The Cross ◽  
Noise Ratio

With the development of communication technology, wireless Internet has become more and more popular. The traditional network layered protocols cannot meet the increasingly rich network services, especially video. This paper briefly introduced the cross-layer transmission of video in wireless network and the cross-layer optimization algorithm used for improving video transmission quality and improved the traditional cross-layer algorithm. Then, the two cross-layer algorithms were simulated and analyzed on MATLAB software. The results showed that the packet delivery rate, peak signal to noise ratio and downlink throughput of the improved cross-layer algorithm were significantly higher than those of the traditional cross-layer algorithm under the same signal to interference plus noise ratio of receiving users in wireless network; meanwhile, with the increase of signal to interference plus noise ratio of the receiving user, the packet delivery rate and peak signal to noise ratio of the two algorithms increased, and tended to be stable after some signal to interference plus noise ratio, while the throughput of the two algorithms increased linearly. In the established real wireless network, the package delivery rate, peak signal to noise ratio and throughput of video after application of cross-layer algorithm were significantly improved, and the wireless network applying the improved cross-layer algorithm improved more. In summary, compared with the traditional cross-layer algorithm, the improved cross-layer algorithm can better improve the transmission quality of video in wireless network.

Cognitive MAC protocol with minimum sampling time and cross-layer cooperation for low signal-to-noise ratio environments

2013 ◽  
Vol 10 (12) ◽  
pp. 125-138 ◽  
Author(s):  
Xie Xianzhong ◽  
Hu Xiaofeng ◽  
Yang Helin ◽  
Ma Bin ◽  
Lei Weijia
Keyword(s):  
Mac Protocol ◽  
Signal To Noise Ratio ◽  
Sampling Time ◽  
Cross Layer ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals Testing general relativity with the Doppler magnification effect

2019 ◽  
Vol 488 (3) ◽  
pp. 3759-3771 ◽  
Author(s):  
Sambatra Andrianomena ◽  
Camille Bonvin ◽  
David Bacon ◽  
Philip Bull ◽  
Chris Clarkson ◽  
...  
Keyword(s):  
General Relativity ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
Density Fluctuations ◽  
Signal To Noise ◽  
Tests Of General Relativity ◽  
Velocity Statistics ◽  
The Cross ◽  
Noise Ratio ◽  
Magnification Effect

ABSTRACT The apparent sizes and brightnesses of galaxies are correlated in a dipolar pattern around matter overdensities in redshift space, appearing larger on their near side and smaller on their far side. The opposite effect occurs for galaxies around an underdense region. These patterns of apparent magnification induce dipole and higher multipole terms in the cross-correlation of galaxy number density fluctuations with galaxy size/brightness (which is sensitive to the convergence field). This provides a means of directly measuring peculiar velocity statistics at low and intermediate redshift, with several advantages for performing cosmological tests of general relativity (GR). In particular, it does not depend on empirically calibrated scaling relations like the Tully–Fisher and Fundamental Plane methods. We show that the next generation of spectroscopic galaxy redshift surveys will be able to measure the Doppler magnification effect with sufficient signal-to-noise ratio to test GR on large scales. We illustrate this with forecasts for the constraints that can be achieved on parametrized deviations from GR for forthcoming low-redshift galaxy surveys with DESI and SKA2. Although the cross-correlation statistic considered has a lower signal-to-noise ratio than RSD, it will be a useful probe of GR since it is sensitive to different systematics.

On: “Enhancement of Signal‐to‐noise Ratios in Magnetotelluric Data” by Dominic W. Kao and David Rankin (GEOPHYSICS, February 1977, p. 103–110).

Geophysics ◽  
1979 ◽  
Vol 44 (9) ◽  
pp. 1594-1596 ◽  
Author(s):  
W. Hernandez ◽  
J. Jacobs
Keyword(s):  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Magnetotelluric Data ◽  
General Validity ◽  
The Cross ◽  
Noise Ratio

In their paper, Kao and Rankin present a technique designed to enhance the signal‐to‐noise ratio of magnetotelluric (MT) data. In particular, they claim it can remove the noise from the autopower estimates of MT data if the cross‐power estimates are noise free and, hence, increase the coherency of the data. We present a hypothetical, but realistic, example which we feel raises serious questions related to the general validity of the technique.

scholarly journals Joint Routing and Congestion Control in Multipath Channel based on Signal to Noise Ratio with Cross Layer Scheme

2018 ◽  
Vol 8 (4) ◽  
pp. 2207
Author(s):  
Istikmal Istikmal ◽  
Adit Kurniawan ◽  
Hendrawan Hendrawan
Keyword(s):  
Congestion Control ◽  
Routing Protocol ◽  
Signal To Noise Ratio ◽  
Multipath Fading ◽  
Packet Transmission ◽  
Multipath Channel ◽  
Cross Layer ◽  
Signal To Noise ◽  
Channel Condition ◽  
Noise Ratio

Routing protocol and congestion control in Transmission Control Protocol (TCP) have important roles in wireless mobile network performance. In wireless communication, the stability of the path and successful data transmission will be influenced by the channel condition. This channel condition constraints come from path loss and the multipath channel fading. With these constraints, the algorithm in the routing protocol and congestion control is confronted with the uncertainty of connection quality and probability of successful packet transmission, respectively. It is important to investigate the reliability and robustness of routing protocol and congestion control algorithms in dealing with such situation.  In this paper, we develop a detailed approach and analytical throughput performance with a cross layer scheme (CLS) between routing and congestion control mechanism based on signal to noise ratio (SNR) in Rician and Rayleigh as multipath fading channel. We proposed joint routing and congestion control TCP with a cross layer scheme model based on SNR (RTCP-SNR). We compare the performance of RTCP-SNR with conventional routing-TCP and routing-TCP that used CLS with routing aware (RTCP-RA) model. The analyses and the simulation results showed that RTCP-SNR in a multipath channel outperforms conventional routing-TCP and RTCP-RA.

scholarly journals Probing delayed-end reionization histories with the 21-cm LAE cross-power spectrum

2020 ◽  
Vol 494 (1) ◽  
pp. 703-718 ◽  
Author(s):  
Lewis H Weinberger ◽  
Girish Kulkarni ◽  
Martin G Haehnelt
Keyword(s):  
Power Spectrum ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
High Dynamic Range ◽  
Integration Time ◽  
Signal To Noise ◽  
Total Signal ◽  
The Cross ◽  
Noise Ratio ◽  
Cross Power Spectrum

ABSTRACT We model the 21-cm signal and Lyman-α emitter (LAE) population evolution during the epoch of reionization in order to predict the 21-cm LAE cross-power spectrum. We employ high-dynamic-range simulations of the intergalactic medium to create models that are consistent with constraints from the cosmic microwave background, Lyman-α forest, and LAE population statistics. Using these models we consider the evolution of the cross-power spectrum for a selection of realistic reionization histories and predict the sensitivity of current and upcoming surveys to measuring this signal. We find that the imprint of a delayed end to reionization can be observed by future surveys, and that strong constraints can be placed on the progression of reionization as late as z = 5.7 using a Subaru–SKA survey. We make predictions for the signal-to-noise ratios achievable by combinations of Subaru/PFS (Prime Focus Spectrograph) with the MWA, LOFAR, HERA, and SKA interferometers for an integration time of 1000 h. We find that a Subaru–SKA survey could measure the cross-power spectrum for a late reionization at z = 6.6 with a total signal-to-noise ratio greater than 5, making it possible to constrain both the timing and bubble size at the end of reionization. Furthermore, we find that expanding the current Subaru/PFS survey area and depth by a factor of three would double the total signal-to-noise ratio.

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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