In Multiuser MIMO (MU-MIMO) systems, precoding is essential to eliminate or minimize the multiuser interference (MUI).
However, the design of a suitable precoding algorithm with good overall
performance and low computational complexity at the same time is quite challenging, especially with the increase of system dimensions.
In this thesis, we explore the art of novel low-complexity high-performance precoding algorithms with both linear and non-linear processing strategies.
Block diagonalization (BD)-type based precoding techniques are well-known linear precoding strategies
for MU-MIMO systems.
By employing BD-type precoding algorithms at the transmit side, the MU-MIMO broadcast channel is decomposed
into multiple independent parallel SU-MIMO channels and achieves the
maximum diversity order at high data rates. The main computational complexity of BD-type precoding algorithms comes from
two singular value decomposition (SVD) operations, which depend on the number of users and the dimensions of each user's channel matrix.
In this thesis, two categories of low-complexity precoding algorithms are proposed to
reduce the computational complexity and improve the performance of BD-type precoding algorithms.
One is based on multiple LQ decompositions and lattice reductions. The other one is based on a channel inversion technique, QR decompositions, and lattice reductions to decouple the MU-MIMO channel into equivalent SU-MIMO channels.
Both of the two proposed precoding algorithms can achieve a comparable sum-rate performance as BD-type precoding algorithms, substantial bit error
rate (BER) performance gains, and a simplified receiver structure, while requiring a much lower complexity.
Tomlinson-Harashima precoding (THP) is a prominent nonlinear processing technique employed at the transmit side and is a dual to the successive interference cancelation (SIC) detection at the receive side. Like SIC detection, the performance of THP strongly depends on the ordering of the precoded symbols.
The optimal ordering algorithm, however, is impractical for MU-MIMO systems with multiple receive antennas. We propose a multi-branch THP (MB-THP) scheme and algorithms that employ multiple transmit processing and ordering strategies along with a selection scheme to mitigate interference in MU-MIMO systems.
Two types of multi-branch THP (MB-THP) structures are proposed. The first one employs a decentralized strategy with diagonal weighted filters at the receivers of the users and the second uses a diagonal weighted filter at the transmitter.
The MB-MMSE-THP algorithms are also derived based on an extended system model with the aid of an LQ decomposition, which is much simpler compared to the conventional MMSE-THP algorithms. Simulation results show that a better BER performance can be achieved by the proposed MB-MMSE-THP precoder with a small computational complexity increase.
