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
  • [41] Joint steepest descent and non-stationary Richardson method for low-complexity detection in massive MIMO systems
    Khoso, Imran A.
    Zhang, Xiaofei
    Dai, Xiaoming
    Ahmed, Adeel
    Dayo, Zaheer Ahmed
    TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES, 2022, 33 (09)
  • [42] Low-complexity signal detection networks based on Gauss-Seidel iterative method for massive MIMO systems
    Yao, Haifeng
    Li, Ting
    Song, Yunchao
    Ji, Wei
    Liang, Yan
    Li, Fei
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2022, 2022 (01)
  • [43] Affine Frequency Division Multiplexing With Index Modulation: Full Diversity Condition, Performance Analysis, and Low-Complexity Detection
    Tao, Yiwei
    Wen, Miaowen
    Ge, Yao
    Li, Jun
    Basar, Ertugrul
    Al-Dhahir, Naofal
    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2025, 43 (04) : 1041 - 1055
  • [44] Adaptive Low-Complexity Constellation-Reduction Aided Detection in MIMO Systems Employing High-Order Modulation
    Ma, Ruijuan
    Ren, Pinyi
    Xue, Shaoli
    Du, Qinghe
    2013 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2013, : 4083 - 4088
  • [45] High-Precision Motion Detection Using Low-Complexity Doppler Radar With Digital Post-Distortion Technique
    Gu, Changzhan
    Peng, Zhengyu
    Li, Changzhi
    IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 2016, 64 (03) : 961 - 971
  • [46] Low-Complexity MIMO Detection using Post-Processing SINR Ordering and Partial K-Best Search
    Chen, Richard H.
    Chung, Wei-Ho
    2011 IEEE GLOBAL TELECOMMUNICATIONS CONFERENCE (GLOBECOM 2011), 2011,
  • [47] A fast coding unit mode decision method based on the mode inheritance of upper coding unit for low-complexity compression of smart contents
    Jun, Dongsan
    DISPLAYS, 2018, 55 : 3 - 9
  • [48] A Test Vector Generation Method Based on Symbol Error Probabilities for Low-Complexity Chase Soft-Decision Reed-Solomon Decoding
    Valls, Javier
    Torres, Vicente
    Jose Canet, Maria
    Garcia-Herrero, Francisco M.
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2019, 66 (06) : 2198 - 2207
  • [49] MetNet: A Novel Low-Complexity Neural Network-Aided Detection for Faster-Than-Nyquist (FTN) Signaling in ISI Channels
    Abdelsamie, Ammar
    Marsland, Ian
    Ibrahim, Ahmed
    Yanikomeroglu, Halim
    IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, 2023, 4 : 798 - 809
  • [50] A low-complexity PPG pulse detection method for accurate estimation of the pulse rate variability (PRV) during sudden decreases in the signal amplitude
    Arguello Prada, Erick Javier
    Paredes Higinio, Alejandro
    PHYSIOLOGICAL MEASUREMENT, 2020, 41 (03)