2134/38270
Diyari Hassan
Diyari
Hassan
Soydan Redif
Soydan
Redif
Sangarapillai Lambotharan
Sangarapillai
Lambotharan
Polynomial matrix decompositions and semi-blind channel estimation for MIMO frequency-selective channels
Loughborough University
2019
untagged
Mechanical Engineering not elsewhere classified
2019-07-09 12:56:37
Journal contribution
https://repository.lboro.ac.uk/articles/journal_contribution/Polynomial_matrix_decompositions_and_semi-blind_channel_estimation_for_MIMO_frequency-selective_channels/9545378
Polynomial eigenvalue decomposition (PEVD) and polynomial QR decomposition (PQRD) are generalisation of
eigenvalue decomposition (EVD) and QR decomposition (QRD), and they are suitable for decoupling and precoding of frequencyselective (FS) multiple-input multiple-output (MIMO) channels. Precoding and decoding of communication channels however
require reliable estimation of the channel which is normally achieved through use of pilot signals. The pilot transmission will
reduce spectral efficiency due to lower data throughput – not particularly attractive for FS-MIMO channels. In this paper, we
therefore introduce a new method that utilises a semi-blind channel estimation (semi-BCE) scheme coupled with PQRD/PEVDbased MIMO-channel decomposition to enable efficient communications over wireless MIMO channels. The proposed semi-BCE
algorithm is a generalisation of a recently developed single-input single output (SISO) BCE method to MIMO systems. A new
class of PQRD algorithms is introduced, which is based on the recently-developed sequential matrix diagonalization (SMD). The
decoders produced by the proposed SMD-based PQRD algorithm are shown to be more suitable (efficient) for MIMO-channel
equalisation than those generated by the prior art. Computer simulations show that the proposed MIMO-channel coding strategy
compares favourably to state-of-the-art MIMO systems, in terms of bit error rate (BER) performance, while reducing the overhead.