Award Abstract # 8801254
Implementation of Maximum Likelihood Decoding for Trellis Codes and Trellis Coded Modulation

NSF Org: TI
Translational Impacts
Recipient: QUALCOMM INCORPORATED
Initial Amendment Date: June 9, 1988
Latest Amendment Date: June 9, 1988
Award Number: 8801254
Award Instrument: Standard Grant
Program Manager: Ritchie B. Coryell
TI
 Translational Impacts
TIP
 Directorate for Technology, Innovation, and Partnerships
Start Date: May 1, 1988
End Date: October 31, 1989 (Estimated)
Total Intended Award Amount: $225,942.00
Total Awarded Amount to Date: $225,942.00
Funds Obligated to Date: FY 1988 = $225,942.00
History of Investigator:
  • Andrew Viterbi (Principal Investigator)
Recipient Sponsored Research Office: Qualcomm Incorporated
5775 MOREHOUSE DR
SAN DIEGO
CA  US  92121-1714
(619)587-1121
Sponsor Congressional District: 51
Primary Place of Performance: DATA NOT AVAILABLE
Primary Place of Performance
Congressional District:
Unique Entity Identifier (UEI): VGLXNJSGWA84
Parent UEI: VGLXNJSGWA84
NSF Program(s): SBIR Phase II
Primary Program Source:  
Program Reference Code(s): 4720, 5373
Program Element Code(s): 537300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.084

ABSTRACT

A single chip implementation of a maximum likelihood Viterbi decoder is being studied for use with convolutional codes and trellis coded modulation. The actual final design and fabrication will occur in Phase III. The decoder is matched to all codes with up to 64 states with the property that branches connect any state in the trellis to at most 4 new states. This decoder chip will have extensive applications in digital communication systems and in digital recording systems including magnetic, magneto-optic and optical systems. This chip is expected to be of use in high-speed telephone-line modems, satellite communication, and magnetic recording applications. The maximum-likelihood decoder will significantly reduce the incidence of channel induced errors in the information bit stream, which was previously convolutionally encoded. While the convolutional encoder is easy to implement, the dynamic programming algorithm which constitutes the Viterbi decoder is much more difficult and is thus a very significant contribution.

Please report errors in award information by writing to: awardsearch@nsf.gov.

Print this page

Back to Top of page