Will the real error floor please stand up?

In this paper we continue our study of the influence of message saturation and quantization on the error-rate performance of iterative, message-passing decoders for low-density parity-check (LDPC) codes. We extend our previous analytical results for the min-sum algorithm (MSA) and its variants to the sum-product algorithm (SPA), demonstrating the significant impact of message saturation on the appearance and location of error floors. Simulation results for selected LDPC codes on the binary symmetric channel (BSC) and the additive white Gaussian noise channel (AWGNC) confirm that the benefits of a quasiuniform quantization scheme, already observed in the context of MSA decoding, apply also to SPA-based decoding.