Open AccessPerformance of decremental antenna selection algorithms for spatial multiplexing MIMO systems with linear receiver over correlated fading channels
Author(s) -
Kim Sangchoon
Publication year - 2017
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.2016.1059
Subject(s) - mimo , fading , algorithm , spatial multiplexing , computer science , robustness (evolution) , multiplexing , channel (broadcasting) , spectral efficiency , computational complexity theory , precoding , orthogonal frequency division multiplexing , eigendecomposition of a matrix , bit error rate , mathematics , eigenvalues and eigenvectors , telecommunications , decoding methods , biochemistry , chemistry , physics , quantum mechanics , gene
This study proposes enhanced suboptimal transmit antenna selection algorithms based on eigenvalue decomposition for spatial multiplexing multiple‐input multiple‐output (MIMO) systems with linear receivers over correlated MIMO flat fading channels. The suboptimal algorithms presented are based on the n th rooting of maximal ratio combined full channel matrix, in which the condition number significantly decreases, and the decremental selection strategy. The first algorithm exploits channel gains obtained by the channel scaling technique, and is further simplified with much lower complexity in the second algorithm. It is shown that they outperform other suboptimal algorithms in terms of bit error rate minimisation under doubly correlated channels. Moreover, their computational complexities are compared with those of other fast antenna selection algorithms. In addressing channel estimation errors on doubly correlated channels, the proposed decremental selection approaches are shown to offer more robustness than other algorithms.