Multiuser Multi-input Multi-output Broadcast Channel Research Articles

Lattice reduction aided with block diagonalization for multiuser MIMO systems

The block diagonalization (BD) precoding technique is a well-known linear transmit strategy for multiuser multi-input multi-output (MU-MIMO) systems. 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 lattice reduction-aided decoding (LRAD) features the reduced decoding complexity in MIMO communications. The Lenstra-Lenstra-Lovasz (LLL) algorithm has been extensively used to obtain better bases of the channel matrix while the complex lattice reduction (CLR) is aimed at improving orthogonality of basis vectors and shortening them. The orthogonalization and size reduction work are left for the CLR algorithm so that a modification of the channel matrix is carried out, resulting in better precoding and detection performances. We also derive bounds for lattice decoding. Simulation results show that the bit error rate (BER) performance of our proposed algorithm is better than that of conventional ones and it reduces the complexity compared with the LLL algorithm-based schemes.

A simple block diagonal precoding for multi-user MIMO broadcast channels

Abstract The block diagonalization (BD) is a linear precoding technique for multi-user multi-input multi-output (MIMO) broadcast channels, which is able to completely eliminate the multi-user interference (MUI), but it is not computationally efficient. In this paper, we propose the block diagonal Jacket matrix decomposition, which is able not only to extend the conventional block diagonal channel decomposition but also to achieve the MIMO broadcast channel capacity. We also prove that the QR algorithm achieves the same sum rate as that of the conventional BD scheme. The complexity analysis shows that our proposal is more efficient than the conventional BD method in terms of the number of the required computation.

Multi-User Downlink System Design with Bright Transmitters and Blind Receivers

This paper considers a scenario for multi-user multi-input multi-output (MIMO) communication systems when perfect channel state information at the transmitter (CSIT) is given while the equivalent channel state information at the receiver (CSIR) is not available. Such an assumption is valid for the downlink multi-user MIMO systems with linear precoders that depend on channels to all receivers. We propose a concept called dual systems with zero-forcing design based on the duality principle, originally proposed to relate the Gaussian multi-access channel (MAC) and the Gaussian broadcast channel (BC). For the K-user N×2 MIMO BC with N antennas at the transmitter and two antennas at each of the K receivers, we design a downlink interference cancellation (IC) transmission scheme by obtaining the dual of uplink MAC systems employing IC methods. The transmitter simultaneously sends K precoded Alamouti codes, one for each user. Each receiver zero-forces the unintended user's Alamouti codes and decouples its own data streams using two simple linear operations independent of CSIR. Analysis shows that the proposed scheme achieves a diversity gain of 2(N - K + 1) for equal energy constellations with short-term power and rate constraints. Power allocation among K users can also be performed to improve the array gain but not the diversity gain. Numerical results demonstrate that the bit error rate of the downlink IC scheme has a diversity gain improvement compared to the block diagonalization (BD) method, which requires global channel information at each node.