Low-complexity Concurrent Error Detection for convolution with Fast Fourier Transforms

被引:0
作者
Bleakley, C. J. [2 ]
Reviriego, P. [1 ]
Maestro, J. A. [1 ]
机构
[1] Univ Antonio de Nebrija, E-28040 Madrid, Spain
[2] Univ Coll Dublin, Dublin 4, Ireland
关键词
FAULT-TOLERANT CONVOLUTION; RELIABILITY; ALGORITHM; SYSTEM;
D O I
10.1016/j.microrel.2011.02.010
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, a novel low-complexity Concurrent Error Detection (CED) technique for Fast Fourier Transform-based convolution is proposed. The technique is based on checking the equivalence of the results of time and frequency domain calculations of the first sample of the circular convolution of the two convolution input blocks and of two consecutive output blocks. The approach provides low computational complexity since it re-uses the results of the convolution computation for CED checking. Hence, the number of extra calculations needed purely for CED is significantly reduced. When compared with a conventional Sum Of Squares - Dual Modular Redundancy technique, the proposal provides similar error coverage for isolated soft errors at significantly reduced computational complexity. For an input sequence consisting of complex numbers, the proposal reduces the number of real multiplications required for CED in adaptive and fixed filters by 60% and 45%, respectively. For input sequences consisting of real numbers, the reductions are 66% and 54%, respectively. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1152 / 1156
页数:5
相关论文
共 50 条
  • [21] A low-complexity error-feedback lattice-equalizer with phase tracking for underwater acoustic communications
    Wu, Fei-Yun
    Yang, Hui-Zhong
    Liu, Shengxing
    JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 2024, 156 (04) : 2250 - 2264
  • [22] A low-complexity AMP detection algorithm with deep neural network for massive mimo systems
    Zhang, Zufan
    Li, Yang
    Yan, Xiaoqin
    Ouyang, Zonghua
    DIGITAL COMMUNICATIONS AND NETWORKS, 2024, 10 (05) : 1375 - 1386
  • [23] An Evolutionary-Based Approach for Low-Complexity Intrusion Detection in Wireless Sensor Networks
    Zhang, Ting
    Han, Dezhi
    Marino, Mario D.
    Wang, Lin
    Li, Kuan-Ching
    WIRELESS PERSONAL COMMUNICATIONS, 2022, 126 (03) : 2019 - 2042
  • [24] Reliability feedback-aided low-complexity detection in uplink massive MIMO systems
    Datta, Arijit
    Mandloi, Manish
    Bhatia, Vimal
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2019, 32 (15)
  • [25] Low-Complexity Signal Detection for Large-Scale MIMO in Optical Wireless Communications
    Gao, Xinyu
    Dai, Linglong
    Hu, Yuting
    Zhang, Yu
    Wang, Zhaocheng
    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2015, 33 (09) : 1903 - 1912
  • [26] An Improved MMSE-Based MIMO Detection using Low-Complexity Constellation Search
    Hung, Cheng-Yu
    Chung, Wei-Ho
    2010 IEEE GLOBECOM WORKSHOPS, 2010, : 746 - 750
  • [27] Low-Complexity CTU Partition Structure Decision and Fast Intra Mode Decision for Versatile Video Coding
    Yang, Hao
    Shen, Liquan
    Dong, Xinchao
    Ding, Qing
    An, Ping
    Jiang, Gangyi
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2020, 30 (06) : 1668 - 1682
  • [28] Low-complexity and fast-convergence linear precoding based on modified SOR for massive MIMO systems
    Liu, Yang
    Li, Yuting
    Cheng, Xiaodong
    Lian, Yinbo
    Jia, Yongjun
    Zhang, Hui
    DIGITAL SIGNAL PROCESSING, 2020, 107
  • [29] Fault detection and diagnosis for rotating machinery: A model based on convolutional LSTM, Fast Fourier and continuous wavelet transforms
    Jalayer, Masoud
    Orsenigo, Carlotta
    Vercellis, Carlo
    COMPUTERS IN INDUSTRY, 2021, 125
  • [30] Low-Complexity Iterative Detection and Decoding in Finite Geometry LDPC-coded MIMO Systems
    Balasuriya, Nuwan
    Yahampath, Pradeepa
    Ngatched, Telex
    Alfa, Attahiru Sule
    2009 IEEE 20TH INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS, 2009, : 1752 - 1756