Generalized Design of Low-Complexity Block Diagonalization Type Precoding Algorithms for Multiuser MIMO Systems

Abstract

Block diagonalization (BD) based precoding techniques are well-known linear transmit strategies for multiuser MIMO (MU-MIMO) systems. By employing BD-type precoding algorithms at the transmit side, the MU-MIMO broadcast channel is decomposed into multiple independent parallel single user MIMO (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 work, low-complexity precoding algorithms are proposed to reduce the computational complexity and improve the performance of BD-type precoding algorithms. We devise a strategy based on a common channel inversion technique, QR decompositions, and lattice reductions to decouple the MU-MIMO channel into equivalent SU-MIMO channels. Analytical and simulation results show that the 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. Index Terms-Multiuser MIMO (MU-MIMO), block diagonalization (BD), regularized block diagonalization (RBD), lowcomplexity, lattice reduction (LR).

Massive MIMO signal transmission in spatially correlated channel environments

“…Since these schemes use singular value decomposition (SVD) technique, they suffer from extensively high complexity when they are applied in the m-MIMO environment. The lowcomplexity BF scheme based on QR decomposition was introduced in [11,12], whose implementation complexity is, however, still high if a massive number of antennas are used. In order to reduce the implementation complexity further, the BF scheme based on the iterative QR decomposition (IQRD) was proposed in [13].…”

MRT precoding in downlink multi-user MIMO systems

“…As to the analysis of multiple streams, some researches for MU-MIMO focused on zero-forcing precoding, and it is noted that most of the previous works on BD precoding assumed designing the BD-type precoding schemes with less computational complexity. QR-decomposition-based BD (QR-BD), generalization ZF-CI (GZI), and lattice reduction (LR)-assisted precoding are proposed in [11][12][13][14]. For the multiple streams system, we must do power control or the adaptive modulation and coding to balance the effective channel gain for each stream [15,16], which gets the same SNR for much channel with the geometric mean decomposition (GMD); otherwise, the performance of each user will suffer significant loss.…”

A Review of Fixed-Complexity Vector Perturbation for MU-MIMO

“…Note that the aforementioned precoding approaches conventionally assume that a single stream transmission is employed. Block diagonalization (BD), which supports multi-stream transmission, can be used to transform the MU-MIMO channel into several parallel SU-MIMO systems that can be independently precoded [17][18][19].…”