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2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop
Suboptimal decoding of convolutional codes, motivated by the need to deal with large constraint length codes, has in the past been achieved by stack algorithms or sequential decoding, which typically do not produce soft outputs, which may be desirable in some modern iterative decoding frameworks. Motivated by an approximate posterior equalizer, we present a suboptimal decoder which employs a similar decomposition for binary convolutional codes observed in additive white Gaussian noise. Thisdoi:10.1109/dsp.2009.4785997 fatcat:j2wdj5cylfaqtpbidwum5tmjcm