Reed solomon codes
- 1. REED SOLOMON CODES B.Tech CS B1 Aditi Anup B001 Rhea Acharya B002 Samreen Reyaz B005
- 2. Introduction ❖ Introduced by Irving S. Reed and Gustave Solomon in 1960 ❖ Error correcting codes ❖ One of the oldest but still widely used ❖ Reed Solomon code is a linear cyclic systematic non-binary block code. ❖ It is capable of correcting both burst errors and erasures. ❖ Wide range of applications in digital communications and storage.
- 3. ❖ Storage devices ❖ Wireless or mobile communications ❖ Satellite communications ❖ Digital television / DVB ❖ High-speed modems ❖ QR codes ❖ Bar Codes Applications
- 4. ❖ Encoder takes a block of digital data and adds extra "redundant" bits. ❖ Errors occur during transmission or storage for a number of reasons ❖ Decoder processes each block and attempts to correct errors and recover the original data. ❖ The number and type of errors that can be corrected depends on the characteristics of the Reed-Solomon code. Procedure Communications Channel or storage device Reed-Solomon encoder Reed-Solomon decoder Data Source Data Output Noise/Errors
- 5. Properties ❖ A Reed-Solomon code is specified as RS(n,k) with s-bit symbols. ❖ Maximum codeword length (n) for a Reed-Solomon code is n = 2s – 1 ❖ This means that the encoder takes k data symbols of s bits each and adds parity symbols to make an n symbol codeword. ❖ There are n-k parity symbols of s bits each. ❖ A Reed-Solomon decoder can correct up to t symbols that contain errors in a codeword, where 2t = n-k.
- 6. Example ❖ A popular Reed-Solomon code is RS(255,223) with 8-bit symbols. Each codeword contains 255 code word bytes, of which 223 bytes are data and 32 bytes are parity. For this code: n = 255, k = 223, s = 8 p = 255 - 223 = 32 2t = 32, t = 16 ❖ The decoder can correct any 16 symbol errors in the code word: i.e. errors in up to 16 bytes anywhere in the codeword can be automatically corrected.
- 7. Symbol Errors ❖ Reed Solomon Encoder and Decoder falls in the category of forward error correction encoders and it is optimized for burst errors rather than bit errors. ❖ One symbol error occurs when 1 bit in a symbol is wrong or when all the bits in a symbol are wrong. ❖ Example: RS(255,223) can correct 16 symbol errors. ➢ In the worst case, 16 bit errors may occur, each in a separate symbol (byte) so that the decoder corrects 16 bit errors. ➢ In the best case, 16 complete byte errors occur so that the decoder corrects 16 x 8 bit errors.
- 8. Decoding Reed-Solomon algebraic decoding procedures can correct errors(s) and erasures(r). An erasure occurs when the position of an erred symbol is known. A decoder can correct up to t errors or up to 2t erasures. Erasure information can often be supplied by the demodulator in a digital communication system, i.e. the demodulator "flags" received symbols that are likely to contain errors.
- 9. When a codeword is decoded, there are three possible outcomes: 1. If 2s + r < 2t (s errors, r erasures), then the original transmitted codeword will always be recovered, 2. The decoder will detect that it cannot recover the original code word and indicate this fact. 3. The decoder will mis-decode and recover an incorrect code word without any indication. The probability of each of the three possibilities depends on the particular Reed- Solomon code and on the number and distribution of errors.
- 10. Coding Gain ❖ Probability of error remaining in the decoded data when Reed- Solomon is used is lower. ❖ This probability is often described as Coding Gain.
- 11. Example A digital communication system is designed to operate at a Bit Error Ratio (BER) of 10-9, i.e. no more than 1 in 109 bits are received in error. This can be achieved by boosting the power of the transmitter or by adding Reed-Solomon. Reed-Solomon allows the system to achieve this target BER with a lower transmitter output power. The power "saving" given by Reed-Solomon (in decibels) is the coding gain.
- 12. Finite(Galois) Field Arithmetic ❖ Reed-Solomon codes are based on a specialist area of mathematics known as Galois fields or finite fields. ❖ A finite field has the property that arithmetic operations (+,-,x,/ etc.) on field elements always have a result in the field. ❖ A Reed-Solomon encoder or decoder needs to carry out these arithmetic operations. ❖ These operations require special hardware or software functions to implement.
- 13. Implementation of Reed- Solomon ❖ Hardware Implementation ❖ Software Implementation
- 14. Hardware Implementation ❖ Many existing systems use "off-the-shelf" integrated circuits that encode and decode Reed-Solomon codes. ❖ These ICs tend to support a certain amount of programmability (for example, RS(255,k) where k = 1 to 16 symbols). ❖ A recent trend is towards VHDL or Verilog designs (logic cores or intellectual property cores). These have a number of advantages over standard ICs.
- 15. ❖ A logic core can be integrated with other VHDL or Verilog components and synthesized to a Field Programmable Gate Array or an Application Specific Integrated Circuit – this enables System on Chip designs where multiple modules can be combined in a single IC. ❖ Depending on production volumes, logic cores can often give significantly lower system costs than "standard" ICs. By using logic cores, a designer avoids the potential need to do a "lifetime buy" of a Reed-Solomon IC.
- 16. Software Implementation ❖ Until recently, software implementations in "real-time" required too much computational power for all but the simplest of Reed-Solomon codes (i.e. codes with small values of t). ❖ The major difficulty in implementing Reed-Solomon codes in software is that general purpose processors do not support Galois field arithmetic operations. ❖ For example, to implement a Galois field multiply in software requires a test for 0, two log table look-ups, modulo add and anti-log table look-up. ❖ However, careful design together with increases in processor performance mean that software implementations can operate at relatively high data rates.
- 17. Example ❖ Concept of “reduced dictionary” 1) detect which words are corrupted (as they are not in our reduced dictionary) 2) correct corrupted words by finding the most similar word in our dictionary. ❖ Reduced dictionary has: this, that and corn corrupted word received: co**, can be corrected corrupted word received: th**, cannot be corrected ❖ Making sure that any 2 words of the dictionary share only a minimum number of letters at the same position is called maximum separability.
- 18. ❖ We generate only a reduced dictionary containing only words with maximum separability ❖ Reed–Solomon is a way to automatically create a reduced dictionary ❖ If a word gets corrupted in the communication, it can be easily fixed ❖ Longer the words, more the separability ❖ More characters can be corrupted without impact
- 20. Append a unique set of characters so that there are no duplicate characters at any of the appended positions, and add one more word to help with the explanation:
- 21. Note that each word in this dictionary differs from every other word by at least 5 characters, so the distance is 5. This allows up to 4 errors in known positions, which are called erasures or 2 errors in unknown positions to be corrected.
- 23. Thank You Aditi Anup B001 Rhea Acharya B002 Samreen Reyaz B005
Editor's Notes
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