Pipeline Decoding of Woven Convolutional Codes
نویسندگان
چکیده
A pipeline decoder for woven convolutional codes (WCCs) is introduced. The decoding is performed iteratively by shifting a window over the received sequence. For the symbol–by–symbol a posteriori (s/s– APP) decoding of convolutional code segments, a windowed version of the BCJR algorithm is applied. This pipeline concept allows a trade–off between decoding delay, decoding complexity, and performance, while using an iterative decoding scheme. Some simulation results for WCCs with inner and outer warp are presented.
منابع مشابه
On the error exponent for woven convolutional codes with inner warp
In this correspondence the error exponent and the decoding complexity of binary woven convolutional codes with outer warp and with binary convolutional codes as outer and inner codes are studied. It is shown that an error probability that is exponentially decreasing with the product of the outer and inner code memories can be achieved with a nonexponentially increasing decoding complexity.
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