In this correspondence, the error exponents and decoding complexity of binary woven convolutional codes with outer and inner warp are studied. It is shown that for both constructions an error probability that is expon...
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In this correspondence, the error exponents and decoding complexity of binary woven convolutional codes with outer and inner warp are studied. It is shown that for both constructions an error probability that is exponentially decreasing with the memory of the woven convolutional codes can be achieved with a nonexponentially increasing decoding complexity. Furthermore, the error exponent for woven convolutional codes with inner warp is larger than the one for woven convolutional codes with outer warp.
The performance of woven convolutional codes that have a two-level unequal error protection on the information sequence is investigated. Two different constructions are considered. The first construction allows to pro...
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The performance of woven convolutional codes that have a two-level unequal error protection on the information sequence is investigated. Two different constructions are considered. The first construction allows to protect only a small part of the information significantly better. The second construction provides a better protection for an arbitrary part of the information. Simulated bit error rates for both constructions are presented and compared with woven convolutional codes that have equal error protection.
Nested convolutionalcodes are a set of convolutionalcodes that is derived from a given generator matrix. The structural properties of nested convolutionalcodes and nested generator matrices are studied. A method to...
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Nested convolutionalcodes are a set of convolutionalcodes that is derived from a given generator matrix. The structural properties of nested convolutionalcodes and nested generator matrices are studied. A method to construct the set of all minimal (rational) generator matrices of a given convolutionalcode is presented. As an example, two different sets of nested convolutionalcodes are derived from two equivalent minimal generator matrices. The significant difference in their free-distance profiles emphasizes the importance of being careful when selecting the generator matrices that determine the nested convolutionalcodes. As an application of nested convolutionalcodes, wovencodes with outer warp, and inner nested convolutionalcodes are considered. The free-distance profile of the inner generator matrix is shown to be an important design tool.
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