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Decoding Reed–Solomon Codes

  • Reference work entry
  • First Online:
Encyclopedia of Algorithms
  • 380 Accesses

Years and Authors of Summarized Original Work

  • 1999; Guruswami, Sudan

Problem Definition

In order to ensure the integrity of data in the presence of errors, an error-correcting code is used to encode data into a redundant form (called a codeword). It is natural to view both the original data (or message) as well as the associated codeword as strings over a finite alphabet. Therefore, an error-correcting code C is defined by an injective encoding map \( { E\!\!:\!\Sigma^k\!\rightarrow\!\!\Sigma^n } \), where k is called the message length, and n the block length. The codeword, being a redundant form of the message, will be longer than the message. The rate of an error-correcting code is defined as the ratio k/n of the length of the message to the length of the codeword. The rate is a quantity in the interval \( { (0,1] } \), and is a measure of the redundancy introduced by the code. Let R(C) denote the rate of a code C.

The redundancy built into a codeword enables detection and hopefully...

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Recommended Reading

  1. Guruswami V (2007) Algorithmic results in list decoding. In: Foundations and trends in theoretical computer science, vol 2, issue 2. NOW Publishers, Hanover

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  2. Guruswami V (2004) List decoding of error-correcting codes. Lecture notes in computer science, vol 3282. Springer, Berlin

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  3. Guruswami V, Rudra A (2008) Explicit codes achieving list decoding capacity: Error-correction with optimal redundancy. IEEE Trans Inform Theory 54(1):135–150

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  4. Guruswami V, Rudra A (2006) Limits to list decoding Reed–Solomon codes. IEEE Trans Inf Theory 52(8):3642–3649

    Article  MathSciNet  MATH  Google Scholar 

  5. Guruswami V, Sudan M (1999) Improved decoding of Reed–Solomon and algebraic-geometric codes. IEEE Trans Inf Theory 45(6):1757–1767

    Article  MathSciNet  MATH  Google Scholar 

  6. Guruswami V, Vardy A (2005) Maximum likelihood decoding of Reed–Solomon codes is NP-hard. IEEE Trans Inf Theory 51(7):2249–2256

    Article  MathSciNet  MATH  Google Scholar 

  7. Koetter R, Vardy A (2003) Algebraic soft-decision decoding of Reed–Solomon codes. IEEE Trans Inf Theory 49(11):2809–2825

    Article  MathSciNet  MATH  Google Scholar 

  8. Peterson WW (1960) Encoding and error-correction procedures for Bose-Chaudhuri codes. IEEE Trans Inf Theory 6:459–470

    Article  MathSciNet  MATH  Google Scholar 

  9. Sudan M (1997) Decoding of Reed–Solomon codes beyond the error-correction bound. J Complex 13(1):180–193

    Article  MathSciNet  MATH  Google Scholar 

  10. Sudan M (2000) List decoding: algorithms and applications. SIGACT News 31(1):16–27

    Article  MATH  Google Scholar 

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Guruswami, V. (2016). Decoding Reed–Solomon Codes. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_101

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