how to create barcode in ssrs report Error Control Coding in Software

Make QR Code JIS X 0510 in Software Error Control Coding

Error Control Coding
Reading QR Code In None
Using Barcode Control SDK for Software Control to generate, create, read, scan barcode image in Software applications.
Quick Response Code Generator In None
Using Barcode creator for Software Control to generate, create QR Code 2d barcode image in Software applications.
1.544 8/7 BIF 1.765
QR Recognizer In None
Using Barcode reader for Software Control to read, scan read, scan image in Software applications.
QR Code 2d Barcode Generation In Visual C#
Using Barcode maker for .NET framework Control to generate, create QR Code image in Visual Studio .NET applications.
1.765 Mb/s. From Eq. (10.16), the required bandwidth is (1.2)/2 1.06 MHz.
Denso QR Bar Code Maker In Visual Studio .NET
Using Barcode generator for ASP.NET Control to generate, create QR Code image in ASP.NET applications.
Drawing QR In .NET
Using Barcode creator for VS .NET Control to generate, create QR Code image in VS .NET applications.
11.8 Coding Gain As shown by Eqs. (11.12) and (11.13), the probability of bit error for a coded message is higher (therefore, worse) than that for an uncoded message, and therefore, to be of advantage, the coding itself must more than offset this reduction in performance. In order to illustrate this, the messages will be assumed to be BPSK (or QPSK) so that the expressions for error probabilities as given by Eqs. (11.12) and (11.13) can be used. Denoting by BERU the bit error rate after demodulation for the uncoded message and by BERC the bit error rate for the coded message after demodulation and decoding, then for the uncoded message BERU PeU (11.14)
QR Code ISO/IEC18004 Encoder In Visual Basic .NET
Using Barcode generator for .NET framework Control to generate, create QR Code 2d barcode image in Visual Studio .NET applications.
UPC Symbol Drawer In None
Using Barcode creator for Software Control to generate, create UPC-A Supplement 2 image in Software applications.
Certain codes known as perfect codes can correct errors up to some number t. The BER for such codes is given by (see Roddy and Coolen, 1995) BERC (n t!(n 1 1)! t)!
DataMatrix Printer In None
Using Barcode generator for Software Control to generate, create DataMatrix image in Software applications.
Painting EAN-13 Supplement 5 In None
Using Barcode creator for Software Control to generate, create EAN13 image in Software applications.
t PeC 1
Code 128 Generation In None
Using Barcode encoder for Software Control to generate, create Code128 image in Software applications.
ANSI/AIM Code 39 Generation In None
Using Barcode encoder for Software Control to generate, create Code-39 image in Software applications.
(11.15)
Uniform Symbology Specification Codabar Generation In None
Using Barcode creation for Software Control to generate, create 2 of 7 Code image in Software applications.
UCC-128 Decoder In Visual Basic .NET
Using Barcode recognizer for Visual Studio .NET Control to read, scan read, scan image in .NET framework applications.
where x! x(x 1)(x 2) . . . 3.2.1 (and n is the number of bits in a codeword). The Hamming codes are perfect codes that can correct one error. For this class of codes and with t 1, Eq. (11.15) simplifies to BERC (n
Making Code 39 Full ASCII In None
Using Barcode encoder for Microsoft Word Control to generate, create Code 39 Full ASCII image in Microsoft Word applications.
Code 39 Encoder In Java
Using Barcode maker for Android Control to generate, create Code 3/9 image in Android applications.
2 1)PeC
Code-128 Maker In VS .NET
Using Barcode creator for ASP.NET Control to generate, create Code 128C image in ASP.NET applications.
GS1 - 13 Encoder In Visual Studio .NET
Using Barcode creation for Visual Studio .NET Control to generate, create UPC - 13 image in VS .NET applications.
(11.16)
Create USS-128 In Objective-C
Using Barcode maker for iPad Control to generate, create UCC - 12 image in iPad applications.
Decoding UCC - 12 In None
Using Barcode recognizer for Software Control to read, scan read, scan image in Software applications.
A plot of BER C and BER U against [Eb/N0] is shown in Fig. 11.8 for the Hamming (7, 4) code. The crossover point occurs at about 4 dB, so for the coding to be effective, [E b /N 0 ] must be higher than this. Also, from the graph, for a BER of 10 5, the [Eb/N0] is 9.6 dB for the uncoded message and 9 dB for the coded message. Therefore, at this BER value the Hamming code is said to provide a coding gain of 0.6 dB. Some values for coding gains given in Taub and Schilling (1986) are block codes, 3 to 5 dB; convolutional coding with Viterbi decoding, 4 to 5.5 dB; concatenated codes using R-S block codes and convolutional decoding with Viterbi decoding, 6.5 to 7.5 dB. These values are for a Pe value of 10 5 and using hard decision decoding as described in the following section.
Eleven
A 0.01
0.001 Uncoded Coded
1 10 4
1 10 5
1 10 6
1 10 7
6 Eb dB N0
9.6 10
Plot of BER versus [Eb/N0] for coded and uncoded signals.
11.9 Hard Decision and Soft Decision Decoding With hard decision decoding, the output from the optimum demodulator is passed to a threshold detector that generates a clean signal, as shown in Fig. 11.9a. Using triple redundancy again as an example, the two codewords would be 111 and 000. For binary polar signals, these might be represented by voltage levels 1 V 1 V 1 V and 1 V 1 V 1 V. The threshold level for the threshold detector would be set at 0 V. If now the sampled signal from the optimum demodulator is 0.5 V 0.7 V 2 V, the output from the threshold detector would be 1 V 1 V 1 V, and the decoder would decide that this was a binary 1 1 0 codeword and produce a binary 1 as
Error Control Coding
Noisy signal .5V .7V 2V
Clean signal 1V 1V 1V
Optimum demodulator
Threshold detector
Hard decision decoder
Binary 1 output
Threshold level 0V
Noisy signal .5V .7V 2V
Optimum demodulator
Soft decision decoder
Binary 0 output
(b) Figure 11.9
(a) Hard decision and (b) soft decision decoding.
output. In other words, a firm or hard decision is made on each bit at the threshold detector. With soft decision decoding (Fig. 11.9b), the received codeword is compared in total with the known codewords in the set, 111 and 000 in this example. The comparison is made on the basis of minimum distance (the minimum distance referred to here is a Euclidean distance as described shortly. This is not the same as the minimum distance introduced in Sec. 11.2). To illustrate this, consider the first two points in an x, y, z coordinate system. Let point P1 have coordinates x1, y1, z1 and point P2 have coordinates x2, y2, z2. From the geometry of the situation, the distance d between the points is obtained from d
x2)2
y2)2
z2)2
Treating the codewords as vectors and comparing the received codeword on this basis with the stored version of 111 results in (0.5 1)2 (0.7 1)2 ( 2 1)2 9.34
Copyright © OnBarcode.com . All rights reserved.