Open AccessStochastic multiple‐input multiple‐output channel model based on singular value decomposition
Author(s) -
Liu Yang,
Yu Yu,
Lu WenJun,
Zhu Hongbo
Publication year - 2015
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.2015.0362
Subject(s) - mimo , singular value decomposition , singular value , scalar (mathematics) , precoding , channel (broadcasting) , computer science , stochastic modelling , transmitter , mathematics , matrix (chemical analysis) , algorithm , control theory (sociology) , telecommunications , eigenvalues and eigenvectors , statistics , artificial intelligence , physics , geometry , materials science , control (management) , quantum mechanics , composite material
A novel stochastic multiple‐input multiple‐output (MIMO) channel model based on the singular value decomposition of the channel matrix is proposed in this study. Under the framework of the proposed model, each of the right singular vectors can be modelled as the product of a stochastic scalar and a non‐random vector, as is each of the left singular vectors. The non‐random vectors, defined as the eigenmodes of the transmitter and receiver, respectively, can be easily extracted from the measurements, so are the singular values of the channel matrix. The implications of the proposed model's parameters that provide further insight into the MIMO channel are interpreted and a way of exploiting the parameters is given. To validate the proposed model, MIMO channel measurement is carried out under different indoor environments and the channel capacity is analysed. It is shown that the proposed model provides a better fit to the measurement results than the other popular stochastic channel models. The proposed stochastic MIMO channel model can be used for the MIMO communication system design and evaluation.