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A 588-Gb/s LDPC Decoder Based on Finite-Alphabet Message Passing

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Author Ghanaatian Reza, Balatsoukas-Stimming Alexios, Muller Thomas Christoph, Meidlinger Michael, Matz Gerald, Teman Adam, Burg Andreas,
Project Design of Energy Efficient and Wireless Communication Systems under Unreliable Silicon
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Original article (peer-reviewed)

Journal IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Volume (Issue) 26(2)
Page(s) 329 - 340
Title of proceedings IEEE Transactions on Very Large Scale Integration (VLSI) Systems
DOI 10.1109/tvlsi.2017.2766925


An ultrahigh throughput low-density parity-check (LDPC) decoder with an unrolled full-parallel architecture is proposed, which achieves the highest decoding throughput compared to previously reported LDPC decoders in the literature. The decoder benefits from a serial message-transfer approach between the decoding stages to alleviate the well-known routing congestion problem in parallel LDPC decoders. Furthermore, a finite-alphabet message passing algorithm is employed to replace the VN update rule of the standard min-sum (MS) decoder with lookup tables, which are designed in a way that maximizes the mutual information between decoding messages. The proposed algorithm results in an architecture with reduced bit-width messages, leading to a significantly higher decoding throughput and to a lower area compared to an MS decoder when serial message transfer is used. The architecture is placed and routed for the standard MS reference decoder and for the proposed finite-alphabet decoder using a custom pseudo-hierarchical backend design strategy to further alleviate routing congestions and to handle the large design. Postlayout results show that the finite-alphabet decoder with the serial message-transfer architecture achieves a throughput as large as 588 Gb/s with an area of 16.2 mm 2 and dissipates an average power of 22.7 pJ per decoded bit in a 28-nm fully depleted silicon on isulator library. Compared to the reference MS decoder, this corresponds to 3.1 times smaller area and 2 times better energy efficiency.