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ECOM 4314 Data Communications Fall September, 2010.

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Presentation on theme: "ECOM 4314 Data Communications Fall September, 2010."— Presentation transcript:

1 ECOM 4314 Data Communications Fall September, 2010

2 Data Communication2 Chapter #10 Outline  Errors Detection and Correction  Coding  Modular Arithmetic  Block Coding  Error Detection  Error Correction  Hamming Distance  Hamming Code

3 Data Communication3 Data Link Layer  The data link layer transforms the physical layer, a raw transmission facility, to a link responsible for node-to-node (hop-to-hop) communication.  The data link layer divides the stream of bits received from the network layer into manageable data units called frames.  The data link layer adds a header to the frame to define the addresses of the sender and receiver of the frame.

4 Data Communication4 Data Link Layer  the data link layer imposes a flow control mechanism to avoid overwhelming the receiver.  The data link layer also adds reliability to the physical layer by adding mechanisms to detect and retransmit damaged, duplicate, or lost frames.

5 Data Communication5 Error Detection and Correction  Networks must be able to transfer data from one device to another with acceptable accuracy.  The Bit Error Rate (BER) is a measure of how frequently an error is likely to occur. For example BER of 10-5 means that. On average, 1 bit in every 100,000 will be wrong.

6 Data Communication6 Types of Errors  Single-Bit Error  The term single-bit error means that only 1 bit of a given data unit (such as a byte,  character, or packet) is changed from 1 to 0 or from 0 to 1.

7 Data Communication7 Types of Errors  Burst Error  The term burst error means that 2 or more bits in the data unit have changed from 1 to 0 or from 0 to 1.  a burst error does not necessarily mean that the errors occur in consecutive bits.  The length of the burst is measured from the first corrupted bit to the last corrupted bit.

8 Data Communication8Redundancy  The central concept in detecting or correcting errors is redundancy.  To be able to detect or correct errors, we need to send some extra bits with our data.  These redundant bits are added by the sender and removed by the receiver.  Their presence allows the receiver to detect or correct corrupted bits.

9 Data Communication9 Detection Versus Correction  In error detection, we are looking only to see if any error has occurred. The answer is a simple yes or no.  In error correction, we need to know the exact number of bits that are corrupted and more importantly, their location in the message.  The number of the errors and the size of the message are important factors

10 Data Communication10 Forward Error Correction Vs Retransmission  There are two main methods of error correction.  Forward error correction is the process in which the receiver tries to guess the message by using redundant bits.  Correction by retransmission is a technique in which the receiver detects the occurrence of an error and asks the sender to resend the message.

11 Data Communication11Coding  Redundancy is achieved through various coding schemes.  The sender adds redundant bits through a process that creates a relationship between the redundant bits and the actual data bits.  The receiver checks the relationships between the two sets of bits to detect or correct the errors.  We can divide coding schemes into two broad block coding and convolution coding.

12 Data Communication12Coding

13 Data Communication13 Modular Arithmetic  In modulo-N arithmetic, we use only the integers in the range 0 to N −1, inclusive.  Modulo-2 Arithmetic  N is 2  Use 0 and 1  Implemented as XOR

14 Data Communication14 Block Coding  The message is divided into blocks  Each block is k-bits size, called dataword  add r redundant bits to each block  The resulting n-bit blocks are called codewords. n = k + r

15 Data Communication15 Example 1  The 4B/5B block coding discussed in Chapter 4 is a good example of this type of coding. In this coding scheme, k = 4 and n = 5. As we saw, we have 2k= 16 dataword sand 2n= 32 codewords. We saw that 16 out of 32 codewordsare used for message transfer and the rest are either used for other purposes or unused.

16 Data Communication16 Error Detection  How can errors be detected by using block coding? If the following two conditions are met, the receiver can detect a change in the original codeword. 1. The receiver has (or can find) a list of valid codewords. 2. The original codeword has changed to an invalid one.

17 Data Communication17 Error Detection

18 Data Communication18Example  Let us assume that k = 2 and n = 3. Table 10.1 shows the list of datawordsand codewords. Later, we will see how to derive a codeword from a dataword.

19 Data Communication19Example  Assume the sender encodes the dataword01 as 011 and sends it to the receiver. Consider the following cases:  The receiver receives 011. It is a valid codeword. The receiver extracts the dataword01 from it.  The codeword is corrupted during transmission, and 111 is received. This is not a valid codeword and is discarded.

20 Data Communication20 Error Detection  The codeword is corrupted during transmission, and 000 is received. This is a valid codeword. The receiver incorrectly extracts the dataword00.  Two corrupted bits have made the error undetectable. An error-detecting code can detect only the types of errors for which it is designed; other types of errors may remain undetected.

21 Data Communication21 Error Correction  In error correction the receiver needs to find (or guess) the original codeword sent

22 Data Communication22Example  Let us add more redundant bits to Example 10.2 to see if the receiver can correct an error without knowing what was actually sent.  We add 3 redundant bits to the 2-bit dataword to make 5-bit codewords. Table 10.2 shows the datawords and codewords. Assume the dataword is 01.  The sender creates the codeword 01011. The codeword is corrupted during transmission, and 01001 is received. First, the receiver finds that the received codeword is not in the table. This means an error has occurred.  The receiver, assuming that there is only 1 bit corrupted, uses the following strategy to guess the correct dataword.

23 Data Communication23Example  1.Comparing the received codeword with the first codeword in the table (01001 versus 00000), the receiver decides that the first codeword is not the one that was sent because there are two different bits.  2.By the same reasoning, the original codeword cannot be the third or fourth one in the table.  3.The original codeword must be the second one in the table because this is the only one that differs from the received codeword by 1 bit. The receiver replaces 01001 with 01011 and consults the table to find the dataword01.

24 Data Communication24

25 Data Communication25 Hamming Distance  The hamming distance between tow words (same size) is the number of difference between the corresponding bits. d(x,y)  The minimum Hamming distance is the smallest Hamming distance between all possible pairs in a set of words.

26 Data Communication26 Hamming Distance  Find the minimum Hamming distance of the coding scheme in Table 10.1.  Solution We first find all Hamming distances.  The d min in this case is 2.

27 Data Communication27 Hamming Distance  Find the minimum Hamming distance of the coding scheme in Table 10.2.  Solution We first find all the Hamming distances. The dminin this case is 3.

28 Data Communication28 Hamming Distance  Any coding scheme needs at least three parameters  Codwordsize n  Datawordsize k  dmin  The hamming distance between the sent and received codewordsis the number of bits affected  To guarantee the detection of up to s errors in all cases, the minimum Hamming distance in a block code must be d min = s + 1.

29 Data Communication29Example  The minimum Hamming distance for our first code scheme (Table 10.1) is 2. This code guarantees detection of only a single error.  For example, if the third codeword (101) is sent and one error occurs, the received codeword does not match any valid codeword.  If two errors occur, however, the received codeword may match a valid codeword and the errors are not detected.

30 Data Communication30example  Our second block code scheme (Table 10.2) has dmin= 3. This code can detect up to two errors. Again, we see that when any of the valid codewordsis sent, two errors create a codeword which is not in the table of valid codewords. The receiver cannot be fooled. However, some combinations of three errors change a valid codeword to another valid codeword. The receiver accepts the received codeword and the errors are undetected.

31 Data Communication31 Hamming Distance

32 Data Communication32 Minimum Distance for Error Correcting  To guarantee correction of up to terrors in all cases, the minimum Hamming distance in a block code must be dmin= 2t+ 1.

33 Data Communication33 Linear Block Code  Almost all block codes used today belong to a subset called linear block codes.  A linear block code is a code in which the exclusive OR (addition modulo-2) of two valid codewordscreates another valid codeword.  The min. H.D. is the number of 1s in the nonzero valid codeword.

34 Data Communication34 Linear Block Code  Let us see if the two codes we defined in Table 10.1 and Table 10.2 belong to the class of linear block codes.  1.The scheme in Table 10.1 is a linear block codebecause the result of XORingany codeword with anyother codeword is a valid codeword. For example, theXORingof the second and third codewordscreates thefourth one.  2.The scheme in Table 10.2 is also a linear block code.We can create all four codewordsby XORingtwoother codewords.

35 Data Communication35example  In our first code (Table 10.1), the numbers of 1s in the nonzero codewordsare 2, 2, and 2. So the minimum Hamming distance is dmin= 2. In our second code (Table 10.2), the numbers of 1s in the nonzero codewordsare 3, 3, and 4. So in this code we have dmin= 3.

36 Data Communication36 Simple Parity-Check Codes  Simplest method and most common method for detecting errors in character oriented transmission.  An extra parity bit is added to each character before it is transmitted.  The value of the parity is determined by adding up the number ‘1’bits in the message to be sent.

37 Data Communication37 Simple Parity-Check Codes  The parity bit is chosen so that the total number of 1 bits, including the parity itself, is either odd or even  A simple parity-check code is a single-bit error- detecting code in which n= k+ 1 with dmin= 2.  A simple parity-check code can detect an odd number of errors

38 Data Communication38 Simple Parity-Check Codes

39 Data Communication39 Simple Parity-Check Codes

40 Data Communication40 Simple Parity-Check Codes  The syndrome is passed to the decision logic analyzer.  If the syndrome is 0, there is no error in the received codeword; the data portion of the received codeword is accepted as the dataword;  if the syndrome is 1, the data portion of the received codeword is discarded. The dataword is not created.

41 Data Communication41Example  Assume the sender sends the dataword 1011. The codeword created from this dataword is 10111, which is sent to the receiver. We examine five cases : 1.No error occurs; the received codeword is 10111. The syndrome is O. The dataword 1011 is created. 2.One single-bit error changes aI' The received codeword is 10011. The syndrome is 1. No dataword is created. 3.One single-bit error changes r 0 The received codeword is 10110. The syndrome is 1. No dataword is created. Note that although none of the dataword bits are corrupted.

42 Data Communication42Example 4.An error changes r 0 and a second error changes a 3 The received codeword is 00110. The syndrome is O. The dataword 0011 is created at the receiver. The simple parity-check decoder cannot detect an even number of errors. 5.Three bits- a 3, a 2, and a 1 -are changed by errors. The received codeword is 01011. The syndrome is 1. The dataword is not created. The simple parity check, guaranteed to detect one single error, can also find any odd number of errors.

43 Data Communication43 Two-dimensional parity check  A better approach is the two-dimensional parity check  In this method, the dataword is organized in a table (rows and columns).  For each row and each column, 1 parity-check bit is calculated.  The whole table is then sent to the receiver, which finds the syndrome for each row and each column.  The two-dimensional parity check can detect up to three errors that occur anywhere in the table  However, errors affecting 4 bits may not be detected

44 Data Communication44 Two-dimensional parity check

45 Data Communication45 Two-dimensional parity check

46 Data Communication46 Two-dimensional parity check

47 Data Communication47 Hamming Codes  This code used for error-correcting.  These codes were originally designed with d min = 3, which means that they can detect up to two errors or correct one single error.  Choose an integer m >= 3  The relationship between m and n in these codes is n= 2 m −1.  k= n-m  If m= 3, then n= 7 and k= 4. this is the hamming code C(7,4) with dm= 3.

48 Data Communication48 Hamming Codes Hamming code C(7, 4)

49 Data Communication49 Hamming Codes  Figure 10.12 shows the structure of the encoder and decoder for this example

50 Data Communication50 Hamming Codes  r0= a2+ a1+ a0 modulo-2  r1= a3+ a2+ a1 modulo-2  r2= a1+ a0+ a3 modulo-2  s0= b2+ b1+ b0 modulo-2  s1= b3+ b2+ b1 modulo-2  s2= b1+ b0+ b3 modulo-2

51 Data Communication51 Hamming Codes  The 3-bit syndrome creates eight different bit patterns (000 to 111) that can represent eight different conditions.  These conditions define a lack of error or an error in 1 of the 7 bits of the received codeword.  Note that the generator is not concerned with the four cases shaded in Table because there is either no error or an error in the parity bit.

52 Data Communication52Example  Let us trace the path of three datawords from the sender to the destination: 1.The dataword0100 becomes the codeword 0100011.The codeword 0100011 is received. The syndrome is000, the final dataword is 0100. 2.The dataword 0111 becomes the codeword 0111001.The syndrome is 011. After flipping b2(changing the 1to 0), the final dataword is 0111. 3.The dataword1101 becomes the codeword 1101000.The syndrome is 101. After flipping b0, we get 0000,the wrong dataword. This shows that our code cannot correct two errors.

53 Data Communication53Example  We need a dataword of at least 7 bits. Calculate values of k and n that satisfy this requirement.  Solution We need to make k = n −m greater than or equal to 7, or 2m −1 −m ≥7. 1.If we set m = 3, the result is n = 23 −1 and k = 7 −3,or 4, which is not acceptable. 2.If we set m = 4, then n = 24 −1 = 15 and k = 15 −4 =11, which satisfies the condition. So the code is C(15,11)

54 Data Communication54 CYCLIC CODES  Cyclic codes are special linear block codes with one extra property. In a cyclic code, if a codeword is cyclically shifted (rotated), the result is another codeword.  For example if 1011000 is a codeword and we cyclically left-shift, then 0110001 is also a codeword.

55 Data Communication55 Cyclic Redundancy Check  We can create cyclic codes to correct errors.  we simply discuss a category of cyclic codes called the cyclic redundancy check (CRC) that is used in networks such as LANs and WANs.

56 Data Communication56

57 Data Communication57

58 Data Communication58 Cyclic codes  Datawordkbits  Codeword nbits  Divisor n-k+1

59 Data Communication59 Division in CRC Encoder

60 Data Communication60

61 Data Communication61Polynomials  A better way to understand cyclic codes and how they can be analyzed is to represent them as polynomials

62 Data Communication62Checksum  The last error detection method we discuss here is called the checksum. The checksum is used in the Internet by several protocols although not at the data link layer.  Like linear and cyclic codes, the checksum is based on the concept of redundancy.  The concept of the checksum is not difficult. Let us illustrate it with a few examples

63 Data Communication63Example  Suppose our data is a list of five 4-bit numbers that we want to send to a destination.  In additionto sending these numbers, we send the sum of the numbers. For example, if the set of numbers is (7, 11, 12, 0, 6), we send (7, 11, 12,0,6,36), where 36 is the sum of the original numbers.  The receiver adds the five numbers and compares the result with the sum. If the two are the same, the receiver assumes no error, accepts the five numbers, and discards the sum.  Otherwise, there is an error somewhere and the data are not accepted.

64 Data Communication64Example  We can make the job of the receiver easier if we send the negative (complement) of the sum,  called the checksum. In this case, we send (7, 11, 12,0,6, -36). The receiver can add all the numbers received (including the checksum). If the result is 0, it assumes no error; otherwise, there is an error

65 Data Communication65 One's Complement  The previous example has one major drawback. All of our data can be written as a 4-bit word (they are less than 15) except for the checksum. One solution is to use one's complement arithmetic.  In this arithmetic, we can represent unsigned numbers between 0 and 2 n - 1 using only n bits. If the number has more than n bits, the extra leftmost bits need to be added to the n rightmost bits (wrapping).

66 Data Communication66 One's Complement  In one's complement arithmetic, a negative number can be represented by inverting all bits (changing a 0 to a 1 and a 1 to a 0).

67 Data Communication67Example  How can we represent the number 21 in one's complement arithmetic using only four bits? The number 21 in binary is 10101 (it needs five bits). We can wrap the leftmost bit and add it to the four rightmost bits. We have (0101 + 1) = 0110 or 6.

68 Data Communication68Example  How can we represent the number -6 in one's complement arithmetic using only four bits? In one's complement arithmetic, the negative or complement of a number is found by inverting all bits. Positive 6 is 0110; negative 6 is 100I. If we consider only unsigned numbers, this is 9. In other words, the complement of 6 is 9. Another way to find the complement of a number in one's complement arithmetic is to subtract the number from 2 n - 1 (16 - 1 in this case).

69 Data Communication69

70 Data Communication70References  Ayman, Maliha, “Data Communication Lectures”, IUG.  BehrouzA. Forouzan, “Data Communications and Networking”, 4rdEdition, Chapter10, 2007

71 Data Communication71Thanks

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