Introduction to Convolutional Codes with Applications

  • Authors:
  • Ajay Dholakia

  • Affiliations:
  • -

  • Venue:
  • Introduction to Convolutional Codes with Applications
  • Year:
  • 1994

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Abstract

From the Publisher:Convolutional codes have been extensively used in practical error control applications on a variety of communication channels. Introduction to Convolutional Codes with Applications provides an introduction to the basic concepts of convolutional codes, their structure and classification, various error correction and decoding techniques for convolutionally encoded data, and some of the most common applications. The definition and representations, distance properties, and important classes of convolutional codes are also discussed in detail. Introduction to Convolutional Codes with Applications provides the first comprehensive description of table-driven correction and decoding of convolutionally encoded data. Complete examples of Viterbi, sequential, and majority-logic decoding technique are also included, allowing a quick comparison among the different decoding approaches. Introduction to Convolutional Codes with Applications summarizes the research of the last two decades on applications of convolutional codes in hybrid ARQ protocols. A new classification of hybrid ARQ protocols based on fixed or variable amount of coding redundancy is suggested. This classification allows a natural way of studying the underlying concepts of hybrid ARQ schemes and accommodates all of the new research in this area. A novel application of fast decodable invertible convolutional codes for lost packet recovery in high speed networks is described. This opens the door for using convolutional coding for error recovery in high speed networks. Practicing communications, electronics and networking engineers who want to get a better grasp of the underlying concepts of convolutional coding and its applications will greatly benefit by the simple and concise style of explanation. As a reference, an up-to-date bibliography of over 300 papers is included. Introduction to Convolutional Codes with Applications is also suitable for use as a textbook or a reference text in an advanced course on co