Linearity-Enhanced Serial List Decoding of Linearly Expurgated Tail-Biting Convolutional Codes
Wenhui Sui, Brendan Towell, Zihan Qu, Eugene Min, Richard Wesel, University of California, Los Angeles, United States
Session:
Convolutional and Streaming Codes 1
Track:
2: Modern Coding Theory
Location:
Omega
Presentation Time:
Wed, 10 Jul, 10:10 - 10:30
Session Chair:
Vijay Kumar,
Abstract
With a sufficiently large list size, the serial list Viterbi algorithm (S-LVA) provides maximum likelihood (ML) decoding of a concatenated convolutional code (CC) and an expurgating linear function (ELF), which is similar in function to a cyclic redundancy check (CRC), but doesn't enforce that the code be cyclic. However, S-LVA with a large list size requires considerable complexity. This paper exploits linearity to reduce decoding complexity for tail-biting CCs (TBCCs) concatenated with ELFs.