Near Optimal Viterbi Algorithm for Storage Channels With Linear Regressive Noise

被引：2
|
作者：
Soltanpur, Cinna [1 ]
Cruz, J. R. [1 ]
机构：
[1] Univ Oklahoma, Sch Elect & Comp Engn, Norman, OK 73019 USA
来源：
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS | 2016年 / 34卷 / 09期
基金：
美国国家科学基金会;
关键词：
Viterbi algorithm; linear regression; signal-correlated noise; RECORDING CHANNELS; ERROR-PROBABILITY; LOWER BOUNDS; LIKELIHOOD; INVERSION; DETECTORS;
D O I：
10.1109/JSAC.2016.2603718
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：
This paper proposes a noise-predictive detection algorithm for intersymbol interference channels with linear regressive noise. A block factorization of the covariance matrix of the linear regressive Gaussian noise is used to derive the branch metrics. This algorithm exhibits near optimal performance. A generalization of this algorithm to signal dependent linear regressive noise is also presented and its performance improvement over conventional algorithms with comparable complexity is shown using simulation results.
引用
收藏
页码：2518 / 2524
页数：7
相关论文
共 22 条
  • [21] Adaptive Stray Inductance Extraction Algorithm Using Linear Regression for Power Module with High Noise Immunity and Accuracy
    Zhu A.
    Gao H.
    Xia Y.
    Luo H.
    Li W.
    He X.
    CPSS Transactions on Power Electronics and Applications, 2022, 7 (02): : 176 - 185
  • [22] Optimization Method to Predict Optimal Noise Reduction Parameters for the Non-Local Means Algorithm Based on the Scintillator Thickness in Radiography
    Cha, Bo Kyung
    Lee, Kyeong-Hee
    Lee, Youngjin
    Kim, Kyuseok
    SENSORS, 2023, 23 (24)
123