Open AccessReduced complexity lattice‐based multiple‐input multiple‐output schemes
Author(s) -
Ouni Nizar,
Tourki Kamel,
Mohaisen Manar,
Bouallegue Ridha
Publication year - 2019
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2018.5586
Subject(s) - lattice reduction , computer science , precoding , orthogonality , algorithm , minimum mean square error , spectral efficiency , computational complexity theory , channel (broadcasting) , reduction (mathematics) , decoding methods , mimo , mathematics , telecommunications , estimator , statistics , geometry
Multiple‐input multiple‐output is being considered as a highly interesting topic for the new generation of wireless communication systems. The major challenge is how to enhance the link reliability while neither affecting the spectral efficiency nor the quality of service. To reduce the complexity of the maximum likelihood (ML) receiver, efforts have been focused on zero forcing (ZF) decoder using lattice reduction‐aided (LRA) techniques. In this study, the authors propose a method that improves performance using the LRA‐based precoding technique without increasing the decoder complexity. Their approach is to exploit the channel matrix to generate matrices for both the precoding and LRA detection technique. This makes it possible to achieve maximum orthogonality for the generated channel matrices while reducing considerably the noise effect. They focus on the use of the LRA‐ZF for the ease of its implementation and low complexity. The proposed method outperforms LRA‐minimum mean square error‐based receiver and gets closer to ML receiver performance. The performance and complexity of the proposed scheme are discussed.