On the design of amplify-and-forward MIMO-OFDM relay systems with QoS requirements specified as Schur-convex functions of the MSEs

In this paper, we focus on the design of linear and nonlinear architectures in amplify-and-forward multiple-input–multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) relay networks in which different types of services are supported. The goal is to jointly optimize the processing matrices to minimize the total power consumption while satisfying the quality-of-service (QoS) requirements of each service specified as Schur-convex functions of the mean square errors (MSEs) over all assigned subcarriers. It turns out that the optimal solution leads to the diagonalization of the source–relay–destination channel up to a unitary matrix, depending on the specific Schur-convex function

Resource Allocation for Power Minimization in the Downlink of THP-based Spatial Multiplexing MIMO-OFDMA Systems

In this work, we deal with resource allocation in the downlink of spatial multiplexing MIMO-OFDMA systems. In particular, we concentrate on the problem of jointly optimizing the transmit and receive processing matrices, the channel assignment and the power allocation with the objective of minimizing the total power consumption while satisfying different quality-of-service requirements. A layered architecture is used in which users are first partitioned in different groups on the basis of their channel quality and then channel assignment and transceiver design are sequentially addressed starting from the group of users with most adverse channel conditions. The multi-user interference among users belonging to different groups is removed at the base station using a Tomlinson-Harashima pre-coder operating at user level. Numerical results are used to highlight the effectiveness of the proposed solution and to make comparisons with existing alternatives.Comment: 12 pages, 6 figures, IEEE Trans. Veh. Techno

Transceiver Optimization for Two-Hop AF MIMO Relay Systems With DFE Receiver and Direct Link

In this paper, we consider precoding and receiving matrices optimization for a two-hop amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay system with a decision feedback equalizer (DFE) at the destination node in the presence of the direct source-destination link. By adopting the minimum mean-squared error (MMSE) criterion, we develop two new transceiver design algorithms for such a system. The first one employs an iterative procedure to design the source, relay, feed-forward, and feedback matrices. The second algorithm is a non-iterative suboptimal approach which decomposes the optimization problem into two tractable subproblems and obtains the source and relay precoding matrices by solving the two subproblems sequentially. Simulation results validate the better MSE and bit-error-rate (BER) performance of the proposed algorithms and show that the non-iterative suboptimal method has a negligible performance loss when the ratio of the source node transmission power to the relay node transmission power is small. In addition, the computational complexity analysis suggests that the second algorithm and one iteration of the first algorithm have the same order of complexity. As the first algorithm typically converges within a few iterations, both proposed algorithms exhibit a low complexity order

Efficient channel estimation algorithms for cooperative multiple-input multiple-output (MIMO) wireless communication networks

Multiple-input multiple-output (MIMO) relay communication systems have been identified to be one of the promising solutions to high rate wireless communications. In optimizing the MIMO relay networks, the knowledge of channel state information (CSI) is essential. This thesis develops novel channel estimation algorithms for MIMO relay communication networks, considering the amplify-and-forward relaying scheme. The proposed algorithms outperform existing schemes in estimating the CSI of each hop in MIMO relay networks