Tomlinson-Harashima Precoding Based Transceiver Design for MIMO Relay Systems With Channel Covariance Information

In this paper, we investigate the performance of the Tomlinson-Harashima (TH) precoder based nonlinear transceiver design for a nonregenerative multiple-input multiple-output (MIMO) relay system assuming that the full channel state information (CSI) of the source-relay link is known, while only the channel covariance information (CCI) of the relay-destination link is available at the relay node. We first derive the structure of the optimal TH precoding matrix and the source precoding matrix that minimize the mean-squared error (MSE) of the signal waveform estimation at the destination. Then we develop an iterative algorithm to optimize the relay precoding matrix. To reduce the computational complexity of the iterative algorithm, we propose a simplified precoding matrices design scheme. Numerical results show that the proposed precoding matrices design schemes have a better bit-error-rate performance than existing algorithms

Robust MMSE Precoding Strategy for Multiuser MIMO Relay Systems with Switched Relaying and Side Information

In this work, we propose a minimum mean squared error (MMSE) robust base station (BS) precoding strategy based on switched relaying (SR) processing and limited transmission of side information for interference suppression in the downlink of multiuser multiple-input multiple-output (MIMO) relay systems. The BS and the MIMO relay station (RS) are both equipped with a codebook of interleaving matrices. For a given channel state information (CSI) the selection function at the BS chooses the optimum interleaving matrix from the codebook based on two optimization criteria to design the robust precoder. Prior to the payload transmission the BS sends the index corresponding to the selected interleaving matrix to the RS, where the best interleaving matrix is selected to build the optimum relay processing matrix. The entries of the codebook are randomly generated unitary matrices. Simulation results show that the performance of the proposed techniques is significantly better than prior art in the case of imperfect CSI.

Precoding Method Interference Management for Quasi-EVD Channel

The Cholesky decomposition-block diagonalization (CD-BD) interference alignment (IA) for a multiuser multiple input multiple output (MU-MIMO) relay system is proposed, which designs precoders for the multiple access channel (MAC) by employing the singular value decomposition (SVD) as well as the mean square error (MSE) detector for the broadcast Hermitian channel (BHC) taken advantage of in our design. Also, in our proposed CD-BD IA algorithm, the relaying function is made use to restructure the quasieigenvalue decomposition (quasi-EVD) equivalent channel. This approach used for the design of BD precoding matrix can significantly reduce the computational complexity and proposed algorithm can address several optimization criteria, which is achieved by designing the precoding matrices in two steps. In the first step, we use Cholesky decomposition to maximize the sum-of-rate (SR) with the minimum mean square error (MMSE) detection. In the next step, we optimize the system BER performance with the overlap of the row spaces spanned by the effective channel matrices of different users. By iterating the closed form of the solution, we are able not only to maximize the achievable sum-of-rate (ASR), but also to minimize the BER performance at a high signal-to-noise ratio (SNR) region

Robust Design for Amplify-and-Forward MIMO Relay Systems with Direct Link and Imperfect Channel Information

In this paper, we propose statistically robust design for multiple-input multiple-output (MIMO) relay systems with the direct source-destination link and imperfect channel state information (CSI). The minimum mean-squared error (MMSE) of the signal waveform estimation at the destination node is adopted as the design criterion. We develop two iterative methods to solve the nonconvex joint source, relay, and receiver optimization problem. In particular, we derive the structure of the optimal relay precoding matrix and show the effect of CSI mismatch on the structure of the optimal robust source and relay matrices. The proposed algorithms generalize the transceiver design of MIMO relay systems with the direct link to the practical scenario of imperfect CSI knowledge. Simulation results demonstrate an improved performance of the proposed algorithms with respect to the conventional methods at various levels of CSI mismatch

Tomlinson Harashima precoding design for non-regenerative MIMO relay networks

In this paper we consider the design of minimum mean square error (MMSE) transceivers for non-regenerative multiple input multiple output (MIMO) relay systems. Our design utilises Tomlinson Harashima precoding (THP) at the source along with linear processors in each stage of the network. Assuming full channel state information (CSI) is available at each node in the network the various processors are jointly optimised to minimise the system arithmetic mean square error (MSE) whilst abiding by average power constraints at both the source and relay terminals in the network. Simulations show that the proposed schemes outperform existing methods in terms of bit error ratio (BER)

A Low-Complexity Precoding Scheme for the Downlink of Multi-Cell Multi-User MIMO AF System

Because of its simplicity, amplify-and-forward (AF) is one of the most popular cooperative relaying technique. Relays are used in cooperative communication to improve reliability, coverage or spectral efficiency of cell-edge users. However, relays tend to increase the interferences seen by users of adjacent cells, particularly by the cell-edge users, when used in multi-cell systems. In this paper, we propose a low-complexity precoding scheme to mitigate the effect of other-cell interference (OCI) in cooperative communication. The scheme is designed by taking into account the interference plus noise covariance matrix of each user for mitigating the interference at each receiver by means of precoding at the relay node. Simulation results show the effectiveness of the proposed scheme, both in terms of sum-rate and computational complexity, when compared to other existing OCI-aware precoding algorithms for AF

Linear Precoders for Non-Regenerative Asymmetric Two-way Relaying in Cellular Systems

Two-way relaying (TWR) reduces the spectral-efficiency loss caused in conventional half-duplex relaying. TWR is possible when two nodes exchange data simultaneously through a relay. In cellular systems, data exchange between base station (BS) and users is usually not simultaneous e.g., a user (TUE) has uplink data to transmit during multiple access (MAC) phase, but does not have downlink data to receive during broadcast (BC) phase. This non-simultaneous data exchange will reduce TWR to spectrally-inefficient conventional half-duplex relaying. With infrastructure relays, where multiple users communicate through a relay, a new transmission protocol is proposed to recover the spectral loss. The BC phase following the MAC phase of TUE is now used by the relay to transmit downlink data to another user (RUE). RUE will not be able to cancel the back-propagating interference. A structured precoder is designed at the multi-antenna relay to cancel this interference. With multiple-input multiple-output (MIMO) nodes, the proposed precoder also triangulates the compound MAC and BC phase MIMO channels. The channel triangulation reduces the weighted sum-rate optimization to power allocation problem, which is then cast as a geometric program. Simulation results illustrate the effectiveness of the proposed protocol over conventional solutions.Comment: 30 pages, 7 figures, submitted to IEEE Transactions on Wireless Communication

A worst-case robust MMSE transceiver design for nonregenerative MIMO relaying

Transceiver designs have been a key issue in guaranteeing the performance of multiple-input multiple-output (MIMO) relay systems, which are, however, often subject to imperfect channel state information (CSI). In this paper, we aim to design a robust MIMO transceiver for nonregenerative MIMO relay systems against imperfect CSI from a worst-case robust perspective. Specifically, we formulate the robust transceiver design, under the minimum mean-squared error (MMSE) criterion, as a minimax problem. Then, by decomposing the minimax problem into two subproblems with respect to the relay precoder and destination equalizer, respectively, we show that the optimal solution to each subproblem has a favorable channel-diagonalizing structure under some mild conditions. Based on this finding, we transform the two complex-matrix subproblems into their equivalent scalar forms, both of which are proven to be convex and can be efficiently solved by our proposed methods. We further propose an alternating algorithm to jointly optimize the precoder and equalizer that only requires scalar operations. Finally, the effectiveness of the proposed robust design is verified by simulation results

Training based channel estimation algorithms for dual hop MIMO OFDM relay systems

In this paper we consider minimum mean square error (MMSE) training based channel estimation for two-hop multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) relaying systems. The channel estimation process is divided into two main phases. The relay-destination channel is estimated in the first phase and can be obtained using well known point-to-point MIMO OFDM estimation methods. In the second phase, the source-relay channel is estimated at the destination with the use of a known training sequence that is transmitted from the source and forwarded to the destination by a non-regenerative relay. To obtain an estimate of the source-relay channel, the source training sequence, relay precoder, and destination processor, require to be optimised. To solve this problem we derive an iterative algorithm that involves sequentially solving a number of convex optimisation problems to update the source, relay, and destination design variables. Since the iterative algorithm may be too computationally expensive for practical implementation we then derive simplified solutions that have reduced computational complexity. Simulation results demonstrate the effectiveness of the proposed algorithms