A Comparison of 25 Gbps NRZ & PAM-4 Modulation Used in Reference, Legacy, & Premium Backplane Channels

2012 ◽  
Vol 2012 (1) ◽  
pp. 000283-000294 ◽  
Author(s):  
Chad Morgan ◽  
Adam Healey
Keyword(s):  
Insertion Loss ◽  
Signal To Noise Ratio ◽  
High Density ◽  
Advanced Materials ◽  
Signal To Noise ◽  
Baud Rate ◽  
Noise Ratio ◽  
Better Than

Standards bodies are now examining how to increase the throughput of high-density backplane links to 25 Gbps. One method for achieving this is to construct premium backplane links utilizing advanced materials and connectors. Another approach is to re-use legacy backplanes by employing PAM-4 signaling at half of the baud rate. For PAM-4 to offer an advantage over NRZ, the signal-to-noise ratio (SNR) at the slicer input, i.e. after equalization, must be ∼9.5 dB better than NRZ to overcome loss of separation between signal levels. This paper will examine 25 Gbaud NRZ and 12.5 Gbaud PAM-4 signaling across varying levels of channel insertion loss and crosstalk. The paper provides a reliable reference for engineers to use when considering when it is appropriate to use NRZ signaling at 25 Gbaud and when it is appropriate to use PAM-4 signaling at 12.5 Gbaud for successful high-density backplane operation.

MIMO Detectors: A Comprehensive Performance Analysis

2021 ◽  
Vol 16 (3) ◽  
pp. 24-27
Author(s):  
E. Obi ◽  
B.O. Sadiq ◽  
O.S . Zakariyya ◽  
A. Theresa
Keyword(s):  
Error Rate ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Symbol Error Rate ◽  
Signal To Noise ◽  
High Data ◽  
Noise Ratio ◽  
Better Than

Multiple-input multiple-output (MIMO) systems are increasingly becoming popular due to their ability to multiply data rates without any expansion in the bandwidth. This is critical in this era of high-data rate applications but limited bandwidth. MIMO detectors play an important role in ensuring effective communication in such systems and as such the performance of the following are compared in this paper with respect to symbol error rate (SER) versus signal-to-noise ratio (SNR): maximum likelihood (ML), zero forcing (ZF), minimum mean square error (MMSE) and vertical Bell laboratories layered space time (VBLAST). Results showed that the ML has the best performance as it has the least Symbol Error Rate (SER) for all values of Signal to Noise Ratio (SNR) as it was 91.9% better than MMSE, 99.6% better than VBLAST and 99.8% better than ZF at 20db for a 2x2 antenna configuration., it can also be deduced that the performance increased with increase in number of antenna for all detectors except the V-BLAST detector.

SEARCH FOR STEADY AND TRANSIENT POINT-LIKE SOURCES OF NEUTRINOS WITH ANTARES

2009 ◽  
Vol 18 (10) ◽  
pp. 1505-1509
Author(s):  
◽  
CIRO BIGONGIARI
Keyword(s):  
Short Duration ◽  
Angular Resolution ◽  
Signal To Noise Ratio ◽  
High Energy ◽  
Neutrino Telescope ◽  
Signal To Noise ◽  
Transient Sources ◽  
High Energy Neutrinos ◽  
Noise Ratio ◽  
Better Than

The ANTARES underwater neutrino telescope has been completed in May 2008 and is now taking data continuously. Thanks to its very good angular resolution (better than 0.3° for neutrinos with energy above 10 TeV) ANTARES is especially suited for the search of astrophysical point-like sources of high energy neutrinos. Data taken with a limited detector (5 out of 12 lines) between January and December 2007 have been analyzed to look for a possible neutrino excess from a list of prospective neutrino sources. In the case of transient sources, like GRBs, the short duration of the expected neutrino signal can be exploited to enhance the signal to noise ratio. ANTARES strategy for both steady and transient point-like sources is discussed. The methodology adopted and the results obtained are shown.

Signal-to-noise ratio models for high-density recording

1986 ◽  
Vol 22 (5) ◽  
pp. 898-900
Author(s):  
B. Finkelstein ◽  
E. Christensen
Keyword(s):  
Signal To Noise Ratio ◽  
High Density ◽  
Signal To Noise ◽  
High Density Recording ◽  
Noise Ratio

A CONDENSER MEMORY UNIT FOR IMPROVING SIGNAL-TO-NOISE RATIOS

1960 ◽  
Vol 38 (3) ◽  
pp. 346-353 ◽  
Author(s):  
D. M. Hunten
Keyword(s):  
Signal To Noise Ratio ◽  
Original Version ◽  
Square Root ◽  
Memory Unit ◽  
Signal To Noise ◽  
Low Leakage ◽  
Recent Modification ◽  
Noise Ratio ◽  
Better Than

The unit contains 30 low-leakage condensers which can store a signal for several hours if necessary. If the signal is repeated over and over, the successive scans can be added in and the signal-to-noise ratio builds up as the square root of the number of repetitions. In principle, the final signal-to-noise ratio is only slightly better than would be obtained from a single scan stretched out to fill the same total time, but in practice the result may be considerably better, especially if the signal fluctuates slowly. It has been used successfully in several investigations of twilight spectra with photoelectric and photoconductive spectrometers. The original version took 1 minute per scan and was rather bulky; a recent modification can scan 32 channels in 10 seconds if required.

scholarly journals Modifikasi Ant Colony Optimization Berdasarkan Gradient Untuk Deteksi Tepi Citra

2015 ◽  
Vol 6 (3) ◽  
Author(s):  
Febri Liantoni ◽  
Nanik Suciati ◽  
Chastine Fatichah
Keyword(s):  
Edge Detection ◽  
Ant Colony Optimization ◽  
Signal To Noise Ratio ◽  
Ant Colony ◽  
Test Results ◽  
Signal To Noise ◽  
Average Value ◽  
Image Edge ◽  
Noise Ratio ◽  
Better Than

Abstract. Ant Colony Optimization (ACO) is an optimization algorithm which can be used for image edge detection. In traditional ACO, the initial ant are randomly distributed. This condition can cause an imbalance ants distribution. Based on this problem, a modified ant distribution in ACO is proposed to optimize the deployment of ant based gradient. Gradient value is used to determine the placement of the ants. Ants are not distributed randomly, but are placed in the highest gradient. This method is expected to be used to optimize the path discovery. Based on the test results, the use of the proposed ACO modification can obtain an average value of the Peak Signal to Noise Ratio (PSNR) of 12.724. Meanwhile, the use of the traditional ACO can obtain an average value of PSNR of 12.268. These results indicate that the ACO modification is capable of generating output image better than traditional ACO in which ants are initially distributed randomly.Keywords: Ant Colony Optimization, gradient, Edge Detection, Peak Signal to Noise Ratio Abstrak. Ant Colony Optimization (ACO) merupakan algoritma optimasi, yang dapat digunakan untuk deteksi tepi pada citra Pada ACO tradisional, semut awal disebarkan secara acak. Kondisi ini dapat menyebabkan ketidakseimbangan distribusi semut. Berdasarkan permasalahan tersebut, modifikasi distribusi semut pada ACO diusulkan untuk mengoptimalkan penempatan semut berdasarkan gradient. Nilai gradient digunakan untuk menentukan penempatan semut. Semut tidak disebar secara acak akan tetapi ditempatkan di gradient tertinggi. Cara ini diharapkan dapat digunakan untuk optimasi penemuan jalur. Berdasarkan hasil uji coba, dengan menggunakan ACO modifikasi yang diusulkan dapat diperoleh nilai rata-rata Peak Signal to Noise Ratio (PSNR) 12,724. Sedangkan, menggunakan ACO tradisional diperoleh nilai rata-rata PSNR 12,268. Hasil ini menunjukkan bahwa ACO modifikasi mampu menghasilkan citra keluaran yang lebih baik dibandingkan ACO tradisional yang sebaran semut awalnya dilakukan secara acak.Kata Kunci: Ant Colony Optimization, gradient, deteksi tepi, Peak Signal to Noise Ratio

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