Open AccessMulti‐class import vector machine for transmit antenna selection in MIMO systems
Author(s) -
Yang Xiaofeng,
Zhao Feng
Publication year - 2020
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2019.3233
Subject(s) - mimo , computer science , antenna (radio) , selection (genetic algorithm) , spatial multiplexing , multiplexing , class (philosophy) , diversity gain , signal to noise ratio (imaging) , task (project management) , support vector machine , 3g mimo , electronic engineering , artificial intelligence , telecommunications , engineering , channel (broadcasting) , systems engineering
Antenna selection is a promising solution to reduce the high cost of multiple RF chains in multiple‐input multiple‐output (MIMO) systems while maintaining the benefits of spatial diversity and multiplexing gain. By modelling the problem of transmit antenna selection as a multi‐class classification and/or decision‐making task, this Letter proposed a multi‐class import vector machine (IVM) based approach to maximise the average received signal‐to‐noise ratio (SNR). Simulation results prove that IVM outperforms the conventional optimisation driven algorithm and the state‐of‐the‐art learning‐based scheme of support vector machine in terms of average received SNR performance with feasible complexity and sparsity.