Dimension degradation of fractionally spaced super-exponential algorithm for sparse channel equalisation

JinLiang Bai; ZhiYe Jiang; Feng Wang; Yi Zhou; Heng Sun

Dimension degradation of fractionally spaced super-exponential algorithm for sparse channel equalisation

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Author(s): JinLiang Bai¹ ; ZhiYe Jiang¹ ; Feng Wang² ; Yi Zhou² ; Heng Sun¹
- Affiliations: 1: National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics , Beijing , People's Republic of China ;
  2: Array and Information Processing Laboratory, College of Computer and Information, Hohai University , West Focheng Road No. 8, Jiangning District, Nanjing , People's Republic of China
Source: Volume 2019, Issue 21, November 2019, p. 7822 – 7826
DOI: 10.1049/joe.2019.0794 , Online ISSN 2051-3305

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)

Received 08/03/2019, Accepted 02/05/2019, Published 13/08/2019

Fractionally spaced super-exponential (FSSE) algorithm has the disadvantage of computational complexity since it exploits high-order statistics explicitly. The authors propose a dimension degradation technique for FSSE when it is applied to the equalisation of a sparse channel in accordance with the relationship between the coefficients of the cross fourth-order cumulant (CFOC) in FSSE and the channel impulse response. They implement partial updating on the prominent coefficients of the CFOC with all the small coefficients remaining unchanged. The computational complexity of the modified FSSE reduces significantly with an acceptable performance loss, and its performance is validated via numerical simulations.

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Dimension degradation of fractionally spaced super-exponential algorithm for sparse channel equalisation

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