5 research outputs found

    The 5G channel code contenders

    No full text

    Scalable Energy-Recovery Architectures.

    Full text link
    Energy efficiency is a critical challenge for today's integrated circuits, especially for high-end digital signal processing and communications that require both high throughput and low energy dissipation for extended battery life. Charge-recovery logic recovers and reuses charge using inductive elements and has the potential to achieve order-of-magnitude improvement in energy efficiency while maintaining high performance. However, the lack of large-scale high-speed silicon demonstrations and inductor area overheads are two major concerns. This dissertation focuses on scalable charge-recovery designs. We present a semi-automated design flow to enable the design of large-scale charge-recovery chips. We also present a new architecture that uses in-package inductors, eliminating the area overheads caused by the use of integrated inductors in high-performance charge-recovery chips. To demonstrate our semi-automated flow, which uses custom-designed standard-cell-like dynamic cells, we have designed a 576-bit charge-recovery low-density parity-check (LDPC) decoder chip. Functioning correctly at clock speeds above 1 GHz, this prototype is the first-ever demonstration of a GHz-speed charge-recovery chip of significant complexity. In terms of energy consumption, this chip improves over recent state-of-the-art LDPCs by at least 1.3 times with comparable or better area efficiency. To demonstrate our architecture for eliminating inductor overheads, we have designed a charge-recovery LDPC decoder chip with in-package inductors. This test-chip has been fabricated in a 65nm CMOS flip-chip process. A custom 6-layer FC-BGA package substrate has been designed with 16 inductors embedded in the fifth layer of the package substrate, yielding higher Q and significantly improving area efficiency and energy efficiency compared to their on-chip counterparts. From measurements, this chip achieves at least 2.3 times lower energy consumption with better area efficiency over state-of-the-art published designs.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116653/1/terryou_1.pd

    Research on energy-efficient VLSI decoder for LDPC code

    Get PDF
    制度:新 ; 報告番号:甲3742号 ; 学位の種類:博士(工学) ; 授与年月日:2012/9/15 ; 早大学位記番号:新6113Waseda Universit

    VLSI decoding architectures: flexibility, robustness and performance

    Get PDF
    Stemming from previous studies on flexible LDPC decoders, this thesis work has been mainly focused on the development of flexible turbo and LDPC decoder designs, and on the narrowing of the power, area and speed gap they might present with respect to dedicated solutions. Additional studies have been carried out within the field of increased code performance and of decoder resiliency to hardware errors. The first chapter regroups several main contributions in the design and implementation of flexible channel decoders. The first part concerns the design of a Network-on-Chip (NoC) serving as an interconnection network for a partially parallel LDPC decoder. A best-fit NoC architecture is designed and a complete multi-standard turbo/LDPC decoder is designed and implemented. Every time the code is changed, the decoder must be reconfigured. A number of variables influence the duration of the reconfiguration process, starting from the involved codes down to decoder design choices. These are taken in account in the flexible decoder designed, and novel traffic reduction and optimization methods are then implemented. In the second chapter a study on the early stopping of iterations for LDPC decoders is presented. The energy expenditure of any LDPC decoder is directly linked to the iterative nature of the decoding algorithm. We propose an innovative multi-standard early stopping criterion for LDPC decoders that observes the evolution of simple metrics and relies on on-the-fly threshold computation. Its effectiveness is evaluated against existing techniques both in terms of saved iterations and, after implementation, in terms of actual energy saving. The third chapter portrays a study on the resilience of LDPC decoders under the effect of memory errors. Given that the purpose of channel decoders is to correct errors, LDPC decoders are intrinsically characterized by a certain degree of resistance to hardware faults. This characteristic, together with the soft nature of the stored values, results in LDPC decoders being affected differently according to the meaning of the wrong bits: ad-hoc error protection techniques, like the Unequal Error Protection devised in this chapter, can consequently be applied to different bits according to their significance. In the fourth chapter the serial concatenation of LDPC and turbo codes is presented. The concatenated FEC targets very high error correction capabilities, joining the performance of turbo codes at low SNR with that of LDPC codes at high SNR, and outperforming both current deep-space FEC schemes and concatenation-based FECs. A unified decoder for the concatenated scheme is subsequently propose
    corecore