ECE 6640 Digital Communications

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1 ECE 6640 Digital Communications Dr. Bradley J. Bazuin Assistant Professor Department of Electrical and Computer Engineering College of Engineering and Applied Sciences

2 Chapter 8 8. Channel Coding: Part Reed-Solomon Codes. 2. Interleaving and Concatenated Codes. 3. Coding and Interleaving Applied to the Compact Disc Digital Audio System. 4. Turbo Codes. 5. Appendix 8A. The Sum of Log-Likelihood Ratios. ECE

3 Sklar s Communications System Notes and figures are based on or taken from materials in the course textbook: ECE 6640 Bernard Sklar, Digital Communications, Fundamentals and Applications, 3 Prentice Hall PTR, Second Edition, 2001.

4 Reed-Solomon Codes Nonbinary cyclic codes with symbols consisting of m-bit sequences (n, k) codes of m-bit symbols exist for all n and k where Convenient example 0 k n 2 An extended code could use n=2 m and become a perfect length hexidecimal or byte-length word. R-S codes achieve the largest possible code minimum distance for any linear code with the same encoder input and output block lengths! d min n k 1 ECE m m m n,k 2 1, t 2 d t min 1 n k 2 2

5 Comparative Advantage to Binary For a (7,3) binary code: 2^7=128 n-tuples 2^3=8 3- symbol codewords 8/128=1/16 of the n-tuples are codewords For a (7,3) R-S with 3-bit symbols (2^7)^3 =2,097,152 n-tuples (2^3)^3= symbol codewords 2^9/2^21=1/2^12=1/4,096 of the n-tuples are codewords Significantly increasing hamming distances are possible! ECE

6 ECE R-S Error Probability Useful for burst-error corrections Numerous systems suffer from burst-errors Error Probability The bit error probability can be upper bounded by the symbol error probability for specific modulation types. For MFSK t j j 1 2 j m m E m m p 1 p j 1 2 j P P P m 1 m E B

7 Burst Errors Result in a series of bits or symbols being corrupted. Causes: Signal fading (cell phone Rayleigh Fading) Lightening or other impulse noise (radar, switches, etc.) Rapid Transients CD/DVD damage See Wikipedia for references: Note that for R-S Codes, the t correction is for symbols, not just bits therefore, t=4 implies 3 to 4 n-tuples of sequential errors. ECE

8 R-S and Finite Fields R-S codes use generator polynomials Encoding may be done in a systematic form Operations (addition, subtraction, multiplication and division) must be defined for the m-bit symbol systems. Galois Fields (GF) allow operations to be readily defined ECE

9 R-S Encoding/Decoding Done similarly to binary cyclic codes GF math performed for multiplication and addition of feedback polynomial U(X)=m(X) x g(x) with p(x) parity computed Syndrome computation performed Errors detected and corrected, but with higher complexity (a binary error calls for flipping a bit, what about an m-bit symbol?) r(x)=u(x) + e(x) Must determine error location and error value ECE

10 Reed-Solomon Summary Widely used in data storage and communications protocols You may need to know more in the future (systems you work with may use it) ECE

11 7.11 Reed-Solomon Codes Reed-Solomon codes are a special class of nonbinary BCH codes that were first introduced in Reed and Solomon. An good overview can be found at: on_codes.html Matlab Information ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

12 Reed-Solomon Codes Nonbinary cyclic codes with symbols consisting of m-bit sequences (n, k) codes of m-bit symbols exist for all n and k where Convenient example m 0 k n 2 2 m m n,k 2 1, t An extended code could use n=2 m and become a perfect length hexidecimal or byte-length word. R-S codes achieve the largest possible code minimum distance for any linear code with the same encoder input and output block lengths! d min n k 1 d t 1 n k 2 2 ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN: min

13 Comparative Advantage to Binary For a (7,3) binary code: 2^7=128 n-tuples 2^3=8 3- symbol codewords 8/128=1/16 of the n-tuples are codewords For a (7,3) R-S with 3-bit symbols (t=2) (2^7)^3 =2,097,152 n-tuples (2^3)^3= symbol codewords 2^9/2^21=1/2^12=1/4,096 of the n-tuples are codewords Significantly increasing hamming distances are possible! Notes and figures are based on or taken from materials in the course textbook: ECE 6640 Bernard Sklar, Digital Communications, Fundamentals and Applications, 13 Prentice Hall PTR, Second Edition, 2001.

14 Reed Solomon Code Options m=3 (7,5) 3-bit symbols, t=1 (7,3) 3-bit symbols, t=2 m=4 (15,13) 4-bit symbols, t=1 (15,11) 4-bit symbols, t=2 (15, 9) 4-bit symbols, t=3 (15, 7) 4-bit symbols, t=4 (15, 5) 4-bit symbols, t=5 Byte wide coding m=8 (255,223) 8-bit symbols, t=16 (255,239) 8-bit symbols, t=8 t represents m-bit symbol error corrections Note: The symbols may be transmitted as m-ary elements. (i.e. m=3 8-psk or m=4 16-QAM) ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

15 ECE R-S Error Probability Useful for burst-error corrections Numerous systems suffer from burst-errors Error Probability - Symbol The bit error probability can be upper bounded by the symbol error probability for specific modulation types. For MFSK t j j 1 2 j m m E m m p 1 p j 1 2 j P P P m 1 m E B John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

16 Example ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

17 R-S and Finite Fields R-S codes use generator polynomials Encoding may be done in a systematic form Operations (addition, subtraction, multiplication and division) must be defined for the m-bit symbol systems. Galois Fields (GF) allow operations to be readily defined ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

18 R-S Encoding/Decoding Done similarly to binary cyclic codes GF math performed for multiplication and addition of feedback polynomial U(X)=m(X) x g(x) with p(x) parity computed Syndrome computation performed Errors detected and corrected, but with higher complexity (a binary error calls for flipping a bit, what about an m-bit symbol?) r(x)=u(x) + e(x) Must determine error location and error value ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

19 Reed-Solomon Summary Widely used in data storage and communications protocols You may need to know more in the future (systems you work with may use it) ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

20 Interleaving Convolutional codes are suitable for memoryless channels with random error events. Some errors have bursty nature: Statistical dependence among successive error events (time-correlation) due to the channel memory. Like errors in multipath fading channels in wireless communications, errors due to the switching noise, Interleaving makes the channel looks like as a memoryless channel at the decoder. Digital Communications I: Modulation and Coding Course, Period , Sorour Falahati, Lecture 13 ECE

21 Interleaving Interleaving is done by spreading the coded symbols in time (interleaving) before transmission. The reverse in done at the receiver by deinterleaving the received sequence. Interleaving makes bursty errors look like random. Hence, Conv. codes can be used. Types of interleaving: Block interleaving Convolutional or cross interleaving Digital Communications I: Modulation and Coding Course, Period , Sorour Falahati, Lecture 13 ECE

22 Interleaving Consider a code with t=1 and 3 coded bits. A burst error of length 3 can not be corrected. A1 A2 A3 B1 B2 B3 C1 C2 C3 2 errors Let us use a block interleaver 3X3 A1 A2 A3 B1 B2 B3 C1 C2 C3 A1 B1 C1 A2 B2 C2 A3 B3 C3 Interleaver Deinterleaver A1 B1 C1 A2 B2 C2 A3 B3 C3 A1 A2 A3 B1 B2 B3 C1 C2 C3 1 errors 1 errors 1 errors ECE Digital Communications I: Modulation and Coding Course, Period , Sorour Falahati, Lecture 13

23 A Block Interleaver A block interleaver formats the encoded data in a rectangular array of m rows and n columns. Usually, each row of the array constitutes a codeword of length n. An interleaver of degree m consists of m rows (m codewords) as illustrated in Figure ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, 23 Fourth Edition, ISBN:

24 Convolutional Interleaving A simple banked switching and delay structure can be used as proposed by Ramsey and Forney. Interleave after encoding and prior to transmission Deinterleave after reception but prior to decoding ECE

25 Forney Reference Forney, G., Jr., "Burst-Correcting Codes for the Classic Bursty Channel," Communication Technology, IEEE Transactions on, vol.19, no.5, pp.772,781, October ECE

26 Convolutional Example Data fills the commutator registers Output sequence (in repeating blocks of 16) ECE

27 Proakis 7.13 Combining Codes The problem, however, is that the decoding complexity of a block code generally increases with the block length, and this dependence in general is an exponential dependence. Therefore improved performance through using block codes is achieved at the cost of increased decoding complexity. One approach to design block codes with long block lengths and with manageable complexity is to begin with two or more simple codes with short block lengths and combine them in a certain way to obtain codes with longer block length that have better distance properties. Then some kind of suboptimal decoding can be applied to the combined code based on the decoding algorithms of the simple constituent codes. Product Codes Concatenated Codes ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

28 Product Codes A simple method of combining two or more codes is described in this section. Let us assume we have two systematic linear block codes; code C i is an (n i, k i ) code with minimum distance d min i for i = 1, 2. The product of these codes is an (n 1 n 2, k 1 k 2 ) linear block code whose bits are arranged in a matrix form as shown in Figure ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

29 Concatenated codes A concatenated code uses two levels on coding, an inner code and an outer code (higher rate). Popular concatenated codes: Convolutional codes with Viterbi decoding as the inner code and Reed-Solomon codes as the outer code The purpose is to reduce the overall complexity, yet achieving the required error performance. Input data Outer encoder Interleaver Inner encoder Modulate Channel Output data Outer decoder Deinterleaver Inner decoder Demodulate ECE Digital Communications I: Modulation and Coding Course, Period , Sorour Falahati, Lecture 13

30 Practical example: Compact Disc Without error correcting codes, digital audio would not be technically feasible. Channel in a CD playback system consists of a transmitting laser, a recorded disc and a photo-detector. Sources of errors are manufacturing damages, fingerprints or scratches Errors have bursty like nature. Error correction and concealment is done by using a concatenated error control scheme, called cross-interleaver Reed-Solomon code (CIRC). ECE Digital Communications I: Modulation and Coding Course, Period , Sorour Falahati, Lecture 13

31 CD CIRC Specifications Maximum correctable burst length 4000 bits (2.5 mm track length) Maximum interpolatable burst length 12,000 bit (8 mm) Sample interpolation rate One sample every 10 hours at P B = samples/min at P B =10-3 Undetected error samples (clicks) Less than one every 750 hours at P B =10-3 Negligible at P B =10-3 New discs are characterized by P B =10-4 ECE

32 Compact disc cont d CIRC encoder and decoder: Encoder interleave C * 2 D C1 D encode interleave encode interleave deinterleave C * 2 D C1 D decode deinterleave decode deinterleave Decoder ECE Digital Communications I: Modulation and Coding Course, Period , Sorour Falahati, Lecture 13

33 CD Encoder Process 16-bit Left Audio 16-bit Right Audio (24 byte frame) RS code 8-bit symbols RS(255, 251) 24 Used Symbols 227 Unused Symbols Equ. RS(28, 24) RS(255, 251) 28 Used Symbols 223 Unused Symbols Equ. RS(32, 28) Overall Rate 3/4 ECE

34 CD Decoder Process ECE

35 Advanced Topic: Turbo Codes Concatenated coding scheme for achieving large coding gains Combine two or more relatively simple building blocks or component codes. Often combined with interleaving. For example: A Reed-Solomon outer code with a convolutional inner code May use soft decisions in first decoder to pass to next decoder. Multiple iterations of decoding may be used to improve decisions! A popular topic for research, publications, and applications. ECE

36 Turbo Code MATLAB I have been trying to run a simulation. Reed Solomon Examples Turbo Code Examples ECE

37 Turbo Code Performance The decoding operation can be performed multiple times or iterations. There is a degree of improvement as shown. ECE

38 MATLAB Simulations 10 0 LTE Turbo-Coding N = 2048, 1 iterations 10 0 LTE Turbo-Coding N = 2048, 2 iterations BER 10-4 BER E b /N 0 (db) E b /N 0 (db) ECE

39 MATLAB Simulations 10 0 LTE Turbo-Coding N = 2048, 3 iterations 10 0 LTE Turbo-Coding N = 2048, 4 iterations BER 10-4 BER E b /N 0 (db) E b /N 0 (db) ECE

40 Section 8.9 Turbo Codes The construction and decoding of concatenated codes with interleaving, using convolutional codes. Parallel concatenated convolutional codes (PCCCs) with interleaving, also called turbo codes, were introduced by Berrou et al. (1993) and Berrou and Glavieux (1996). A basic turbo encoder, shown in Figure 8.9 1, is a recursive systematic encoder (RSC or RSCC) that employs two recursive systematic convolutional encoders in parallel, where the second encoder is preceded by an interleaver. ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

41 Turbo Coding We observe that the nominal rate at the output of the turbo encoder is Rc = 1/3. As in the case of concatenated block codes, the interleaver is usually selected to be a block pseudorandom interleaver that reorders the bits in the information sequence before feeding them to the second encoder. In effect, as will be shown later, the use of two recursive convolutional encoders in conjunction with the interleaver produces a code that contains very few codewords of low weight. ECE 6640 The use of the interleaver in conjunction with the two encoders results in codewords that have relatively few nearest neighbors. That is, the codewords are relatively sparse. John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

42 An Recursive Systematic encoder (RSC) EXAMPLE A (31, 27) RSC encoder is represented by g1 = (11001) and g2 =(10111) corresponding to g 1 (D) = 1+ D + D 4 g 2 (D) = 1+ D 2 + D 3 + D 4. The encoder is given by the block diagram shown in Figure ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

43 Performance Bounds Turbo codes are two recursive systematic convolutional codes concatenated by an interleaver. Although the codes are linear and time-invariant, the operation of the interleaver, although linear, is not timeinvariant. The trellis of the resulting linear but time-varying finitestate machine has a huge number of states that makes maximum-likelihood decoding hopeless. Therefore the text offers a union bound approach but refers readers to other papers. ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

44 Iterative Decoding A suboptimal iterative decoding algorithm, known as the turbo decoding algorithm, was proposed by Berrou et al. (1993) which achieves excellent performance very close to the theoretical bound predicted by Shannon. The turbo decoding algorithm is based on iterative usage of the Log-APP or the Max-Log-APP algorithm. (APP: a-posteriori probability) a BCJR simplification described on p A soft-input soft-output decoder is used that allows multiple iterations to be performed. ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

45 Decoder Performance It is seen from these plots that three regions are distinguishable. For the low-snr region where the error probability changes very slowly as a function of Eb/N 0 and the number of iterations. For moderate SNRs the error probability drops rapidly with increasing Eb/N 0 and over many iterations Pb decreases consistently. This region is called the waterfall region or the turbo cliff region. Finally, for moderately large Eb/N 0 values, the code exhibits an error floor which is typically achieved with a few iterations. As discussed before, the error floor effect in turbo codes is due to their low minimum distance. ECE 6640 John G. Proakis, Digital Communications, 5th ed., McGraw Hill, Fourth Edition, ISBN:

46 Drawback and Summary The major drawback with decoding turbo codes with large interleavers is the decoding delay and the computational complexity inherent in the iterative decoding algorithm. In most data communication systems, however, the decoding delay is tolerable, and the additional computational complexity is usually justified by the significant coding gain that is achieved by the turbo code. ECE

47 References Digital Communications I: Modulation and Coding Course, Period , Sorour Falahati, Lecture 13 A Tutorial on Convolutional Coding with Viterbi Decoding by Chip Fleming of Spectrum Applications Robert Morelos-Zaragoza, The Error Correcting Codes (ECC) Page Matthew C. Valenti, Center for Identification Technology Research (CITeR), West Virginia University Site ECE

ECE 6640 Digital Communications

ECE 6640 Digital Communications Dr. Bradley J. Bazuin Assistant Professor Department of Electrical and Computer Engineering College of Engineering and Applied Sciences Chapter 8 8. Channel Coding: Part