Linear Multiuser Multiple-input Multiple-output Research Articles

A Novel Nonlinear and Non-iterative Precoding Technique for Single and Multi User MIMO Systems

A modification of the well known linear and iterative based precoder intended for both single and multi-user multiple-input multiple-output (MIMO) has been proposed. The proposed precoder uses the nonlinear and non-iterative processing strategies to obtain more efficient and less complexity designs. The non-linearity in the precoder is introduced by using the nonlinear constellation precoding technique based on maximum distance separable codes. Also, the computation complexity in iterative based precoder design is avoided by using a singular value decomposition method. The maximum likelihood detection for the linear MIMO channel is considered. The simulation results are provided in-terms of bit error rate versus signal-to-noise ratio to show that the proposed combined non-linear and non-iterative precoding schemes outperform the conventional linear and iterative based MIMO precoder designs.

On the Optimality of Linear Multiuser MIMO Beamforming for a Two-User Two-Input Multiple-Output Broadcast System

The asymptotic optimality of a jointly optimized linear multiuser beamforming system with two transmit and many receive antennas for the fading multiple-input multiple-output (MIMO) Gaussian broadcast channel is investigated. We derive the asymptotic sum capacity of the independent and identically-distributed (i.i.d.) MIMO broadcast channel and the asymptotic sum rate of a linear multiuser beamforming system with respect to the number of receive antennas per user, where two users are served with a zero inter-user interference constraint. Based on this result, we show that linear multiuser beamforming with many receive antennas can asymptotically achieve the sum capacity of the two-user i.i.d. MIMO broadcast channel even without opportunistic scheduling gain. Numerical results confirm that as the number of receive antennas increases the sum rate of linear multiuser beamforming system converges to the sum capacity.

Robust Linear MIMO in the Downlink: A Worst-Case Optimization with Ellipsoidal Uncertainty Regions

This paper addresses the joint robust power control and beamforming design of a linear multiuser multiple-input multiple-output (MIMO) antenna system in the downlink where users are subjected to individual signal-to-interference-plus-noise ratio (SINR) requirements, and the channel state information at the transmitter (CSIT) with its uncertainty characterized by an ellipsoidal region. The objective is to minimize the overall transmit power while guaranteeing the users' SINR constraints for every channel instantiation by designing the joint transmitreceive beamforming vectors robust to the channel uncertainty. This paper first investigates a multiuser MISO system (i.e., MIMO with single-antenna receivers) and by imposing the constraints on an SINR lower bound, a robust solution is obtained in a way similar to that with perfect CSI. We then present a reformulation of the robust optimization problem using S-Procedure which enables us to obtain the globally optimal robust power control with fixed transmit beamforming. Further, we propose to find the optimal robust MISO beamforming via convex optimization and rank relaxation. A convergent iterative algorithm is presented to extend the robust solution for multiuser MIMO systems with both perfect and imperfect channel state information at the receiver (CSIR) to guarantee the worst-case SINR. Simulation results illustrate that the proposed joint robust power and beamforming optimization significantly outperforms the optimal robust power allocation with zeroforcing (ZF) beamformers, and more importantly enlarges the feasibility regions of a multiuser MIMO system.

Linear Multiuser MIMO Transceiver Design With Quality of Service and Per-Antenna Power Constraints

Joint design of linear multiuser multiple-input-multiple-output (MIMO) transceiver subject to different quality of service (QoS) constraints per user and with per-antenna or antenna group power constraints is considered. Solutions for two linear transceiver optimization problems are proposed, i.e., balancing the weighted signal-to-interference-plus-noise ratio (SINR) per data stream and balancing the weighted rate for each scheduled user with minimum rate requirements per user. The proposed joint transceiver optimization algorithms are compared to corresponding optimal nonlinear transmission methods as well as to generalized zero-forcing transmission solutions. Unlike the optimal nonlinear schemes, the optimization problems employed in the linear multiuser MIMO transceiver design are not convex in general. However, the proposed algorithms are shown to provide very efficient solutions despite of the fact that the global optimum cannot be guaranteed due to nonconvexity of the problems.

Feasibility conditions of linear multiuser MIMO systems in the asymptotic regime

This letter investigates the feasibility conditions of a linear multiuser multiple-input multiple-output (MIMO) flat fading channel with individual users' signal-to-interference-plus-noise-ratio (SINR) requirements in the asymptotic large-system regime. Following the notion of the effective bandwidth, originally discovered in [4] by Viswanath <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">al</i> ., we propose the feasibility conditions for linear multiuser MIMO channels for both up and downlinks with and without power constraints, and prove that the conditions are indeed necessary and sufficient for feasibility in the asymptotic large-system regime.