Open AccessHybrid optimisation method of sparse FIR DFEs based on reweighted ℓ 1 ‐norm minimisation and greedy algorithms
Author(s) -
Yu Lihong,
Zhao Jiaxiang
Publication year - 2019
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2018.7438
Subject(s) - minimisation (clinical trials) , intersymbol interference , greedy algorithm , algorithm , finite impulse response , computer science , norm (philosophy) , mathematical optimization , mathematics , decoding methods , statistics , political science , law
The finite‐impulse‐response (FIR) decision feedback equalisers (DFEs) with a large number of taps are used to eliminate the intersymbol interference. In this Letter, a hybrid optimisation approach based on reweighted ℓ 1 ‐norm minimisation and the greedy algorithm is proposed to get a better estimation of the non‐zero taps. First, the authors transform the problem of designing sparse FIR multiple‐input multiple‐output DFEs into an ℓ 0 ‐norm minimisation problem, then use the proposed approach, which involves two stages as the preliminary selection of non‐zero tap positions and re‐optimisation with non‐zero taps, to determine the positions and values of the non‐zero taps for the FIR DFEs. The simulation results demonstrate the effectiveness of the proposed hybrid optimisation approach.