Performance and Decoding Complexity Analysis of Short Binary Codes
Bo Lian · TSpace (University of Toronto) · 2019
Motivated by emerging 5G wireless systems supporting ultra-reliable low-latency applications, this work studies performance-complexity trade-offs for short block length codes. While well-established tools exist for code optimization of long block length codes, there is no universal approach to the code design problem for short block lengths. Three candidate approaches for short block length designs are considered: 1) tail-biting convolutional codes decoded with the wrap-around Viterbi algorithm (WAVA), 2) polar codes decoded with successive-cancellation (SC) and an SC-list algorithm aided with error detection, 3) tail-biting convolutional codes and a class of random linear codes with a particular index profile decoded with a sequential decoding algorithm. Simulation results show that polar codes have a beneficial performance-complexity trade-off for moderate block lengths at or above 512 bits, but at shorter lengths sequentially decoded codes can have a better trade-off. WAVA decoding is competitive only at short lengths and or very low error rates.