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Data block convolutional coding device and method, and corresponding decoding method and device

Patent 6119264 Issued on September 12, 2000. Estimated Expiration Date: Icon_subject April 19, 2018. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.

Patent References

Method and apparatus for encoding/decoding a convolutional code to a periodic convolutional code block
Patent #: 4293951
Issued on: 10/06/1981
Inventor: Rhodes

Method for a maximum likelihood decoding of a convolutional code with decision weighting, and corresponding decoder
Patent #: 5406570
Issued on: 04/11/1995
Inventor: Berrou, et al.

Error-correction coding method with at least two systematic convolutional codings in parallel, corresponding iterative decoding method, decoding module and decoder Patent #: 5446747
Issued on: 08/29/1995
Inventor: Berrou

Inventors

Assignee

Application

No. 155819 filed on 04/19/1998

US Classes:

714/786Forward error correction by tree code (e.g., convolutional)

Examiners

Primary: Decady, Albert
Assistant: Chase, Shelly A

Attorney, Agent or Firm

International Class

H03M 013/03

Foreign Application Priority Data

1996-04-03 FR

Abstract

Disclosed are a method and a device for the convolutive encoding of blocks each formed by a predetermined number N of source data elements, wherein each of said source data elements is introduced twice into one and the same convolutive encoder implementing a generating polynomial with a period L in an order such that the two instances of introduction of one and same source data element di are separated by the introduction of (pi.L)-1 other source data elements, pi being a non-zero integer. Also disclosed are a corresponding decoding method and device that can be applied, in particular, to the transmission of short messages, for example in radiotelephony, for satellite communications or gain computer telecommunications (Internet for example). FIG. 2.

Other References

  • Pyndiah et al., Near Optimum Decoding of Product Codes, IEEE, pp. 339-343, 1994
  • Berrou et al., Near Shannon Limit Error-Correcting Coding and Decoding: Turbo-Codes (1), IEEE, pp. 1064-1070, 1993
  • Haganauer, Source-Controlled Channel Decoding, IEEE, pp. 2499-2457, 1995
  • Jung, Comparison of Turbo Codes Decoders Applied to Short Frame Transmission Systems, IEEE pp. 530-537, Apr. 1996
  • Robertson, Improving Decoder and Code Structure of Parallel concatenated Recursive Systematic (Turbo) Codes, IEEE, pp. 183-187, Apr. 1994
  • Benedetto et al., Design Guidelines of Parallel Concatenated Convolutional codes, IEEE, pp. 2273-22777, May 1995
  • Thitimajshima, Recursive Systematic Convolutional Codes and Application to parallel Concatenation, IEEE, pp. 2267-2272, May 1995
  • Qiang Wang and Vijay K. Bhargava, "An Efficient Maximum Likelihood Decoding Algorithm for Generalized Tail Biting Convolutional Codes Including Quasicyclic Codes", IEEE Transactions on Communications, pp. 875-879; Aug. 8, 1989, New York, US
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