A 75-Gb/s/mm2 and Energy-Efficient LDPC Decoder Based on a Reduced Complexity Second Minimum Approximation Min-Sum Algorithm

Henry Lopez, Hsun Wei Chan, Kang Lun Chiu, Pei Yun Tsai, Shyh Jye Jerry Jou

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

This article presents a high-throughput and low-routing complexity low-density parity check (LDPC) decoder design based on a novel second minimum approximation min-sum (SAMS) algorithm. The routing congestion is mitigated by reducing the required interconnections in the critical path of the routing network. The implementation and postlayout results with 28-nm 1P9M CMOS process show that the proposed design can achieve a throughput of 10.5 Gb/s for a millimeter-wave 60-GHz baseband system while satisfying the low bit error rate (BER) requirements (10-7). The proposed design reduces the wiring in the routing network by 21% and improves the area by 12% compared to the conventional min-sum (MS) and normalized MS (NMS) algorithm. Additional hardware optimizations are obtained by considering the internal message passing resolution based on the BER and signal-to-noise ratio (SNR) requirements for a practical baseband system. The power consumption is efficiently reduced by the employment of a shared address generator that exploits the degree of parallelism to reduce the switching activity on a group of memory elements. The LDPC decoder is implemented with a core area of 0.14 mm2, power consumption of 81 mW at 312.5 MHz, and the area and power efficiency of 75 Gb/s/mm2 and 10.2 pJ/bit, respectively.

Original languageEnglish
Article number8935206
Pages (from-to)926-939
Number of pages14
JournalIEEE Transactions on Very Large Scale Integration (VLSI) Systems
Volume28
Issue number4
DOIs
StatePublished - Apr 2020

Keywords

  • Low-density parity check (LDPC) decoder
  • min-sum (MS) algorithm
  • normalized MS (NMS)
  • offset MS (OMS)

Fingerprint

Dive into the research topics of 'A 75-Gb/s/mm2 and Energy-Efficient LDPC Decoder Based on a Reduced Complexity Second Minimum Approximation Min-Sum Algorithm'. Together they form a unique fingerprint.

Cite this