Next Article in Journal
Two-Dimensional DOA Estimation for Three-Parallel Nested Subarrays via Sparse Representation
Next Article in Special Issue
A Case Study on Attribute Recognition of Heated Metal Mark Image Using Deep Convolutional Neural Networks
Previous Article in Journal
Coupling of PZT Thin Films with Bimetallic Strip Heat Engines for Thermal Energy Harvesting
Previous Article in Special Issue
Automatic Detection and Classification of Audio Events for Road Surveillance Applications
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Sensors 2018, 18(6), 1860; https://doi.org/10.3390/s18061860

Design of Sparse FIR Decision Feedback Equalizers in MIMO Systems Using Hybrid l1/l2 Norm Minimization and the OMP Algorithm

1
College of Computer and Control Engineering, Nankai University, Tianjin 300350, China
2
Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China
3
College of Electronic and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, China
*
Author to whom correspondence should be addressed.
Received: 10 May 2018 / Revised: 1 June 2018 / Accepted: 4 June 2018 / Published: 6 June 2018
(This article belongs to the Special Issue Sensor Signal and Information Processing)
Full-Text   |   PDF [1892 KB, uploaded 7 June 2018]   |  

Abstract

In this paper, a novel scheme using hybrid l1/l2 norm minimization and the orthogonal matching pursuit (OMP) algorithm is proposed to design the sparse finite impulse response (FIR) decision feedback equalizers (DFE) in multiple input multiple output (MIMO) systems. To reduce the number of nonzero taps for the FIR DFE while ensuring its design accuracy, the problem of designing a sparse FIR DFE is transformed into an l0 norm minimization problem, and then the proposed scheme is used to obtain the sparse solution. In the proposed scheme, a sequence of minimum weighted l2 norm problems is solved using the OMP algorithm. The nonzero taps positions can be corrected with the different weights in the diagonal weighting matrix which is computed through the hybrid l1/l2 norm minimization. The simulation results verify that the sparse FIR MIMO DFEs designed by the proposed scheme get a significant reduction in the number of nonzero taps with a small performance loss compared to the non-sparse optimum DFE under the minimum mean square error (MMSE) criterion. In addition, the proposed scheme provides better design accuracy than the OMP algorithm with the same sparsity level. View Full-Text
Keywords: multiple input multiple output (MIMO); decision feedback equalization (DFE); sparse representation; hybrid l1/l2 norm minimization; orthogonal matching pursuit (OMP) multiple input multiple output (MIMO); decision feedback equalization (DFE); sparse representation; hybrid l1/l2 norm minimization; orthogonal matching pursuit (OMP)
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Yu, L.; Zhao, J.; Xu, W.; Liu, H. Design of Sparse FIR Decision Feedback Equalizers in MIMO Systems Using Hybrid l1/l2 Norm Minimization and the OMP Algorithm. Sensors 2018, 18, 1860.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top