In this paper, we investigate the robust transceiver design for a downlink multiuser multiple-input multiple-output (MIMO) amplify-and-forward (AF) relay system with imperfect channel state information (CSI). We consider that the actual channel is within the neighborhood of a nominal channel and formulate two optimization problems following the philosophy of worst-case robustness, i.e., minimizing the sum mean-square-error (SMSE) and minimizing the total transmit power for any channel realization in the uncertainty region. In order to efficiently find the solutions, we transform the original problems into suitable forms using the sign-definiteness lemma and then propose an alternating iterative algorithm with guaranteed convergence. To further reduce the computational complexity, the cutting-set method is developed, which alternates between transceiver design and channel determination steps. Moreover, some interesting extensions of the proposed methods are discussed, including various types of uncertainty models and transmit power constraints, nonlinear transceiver structure, and uncertain noise covariance. Simulation results are presented to demonstrate the effectiveness of the proposed robust designs.

In this study, the authors consider the robust transceiver design in a dual‐hop multi‐user multiple‐input multiple‐output amplify‐and‐forward relay system. By incorporating the antenna correlation at both ends of the channel and taking the channel estimation errors into account, the authors propose two robust design approaches under the minimum sum mean‐square‐error criterion. Specifically, they decouple the original problem into three convex sub‐problems in the first approach and develop an iterative algorithm with guaranteed convergence. The second approach converts the original problem into simple power allocation problems utilising a certain relaying structure, and the approximate closed‐form solutions are derived. Some practical implementation issues are also discussed. Simulation results are provided to demonstrate the effectiveness of the proposed approaches.

ABSTRACT Signal‐time coding (STC) is a newly proposed transmission scheme for half‐duplex relay networks, which is able to achieve higher information flow rate by combining the traditional encoding/modulation mode in the signal domain with the signal pulse phase modulation in the time domain. However, most of the results for STC are only obtained under the ideal assumptions that the signal detections at physical layer are perfect and there are still a lot of fundamental problems to be explored. This paper considers the implementing issues of STC at physical layer in additive white Gaussian noise relay networks. Firstly, a performance evaluation criterion, the reliable information per symbol (RIPS), is proposed to characterize the performance of STC in noisy wireless networks. Secondly, a new construction scheme based on route ID for the codeword of STC is presented, and some structural properties of the codeword of STC are investigated. Thirdly, the error probabilities of STC in both the signal domain and the time domain are discussed. Furthermore, two implementing schemes, that is, the energy detection based STC (ED‐STC) and the symbol detection based STC (SD‐STC), are proposed, and their performance bounds in terms of RIPS are discussed. Numerical analyses show that both ED‐STC and SD‐STC outperform traditional transmission methods in terms of effective information rate even under some practical conditions. Copyright © 2011 John Wiley & Sons, Ltd.

This paper studies the beamforming design of two-way relay systems for simultaneous information and power transfer with consideration of imperfect channel state information (CSI). To this end, we seek the robust beamforming design to maximize the weighted sum rate under the power constraint at relay nodes and the energy harvesting constraints at the two source nodes. Due to the infinitely many nonconvex constraints, the robust beamforming design problem is challenging. Therefore, we firstly propose an approximate to the signal to interference plus noise ratio (SINR). Then an iterative algorithm is developed based on the semidefinite relaxation (SDR), S-procedure and successive convex approximation (SCA) techniques. Furthermore, the effectiveness of the proposed algorithm is validated by numerical experiments.

Weighted sum-rate maximization with transmit power limit and energy harvesting constraints is considered in the context of two-way collaborative relay systems. We discuss an ideal scheme where the source nodes can decode information signal and harvest energy, simultaneously. An iterative algorithm based on semidefinite relaxation (SDR) and successive convex approximation (SCA) is developed to obtain (at least) a local optimal solution. In view of the limitation of the current circuits, we propose a practical ping-pong scheme wherein the source node can only perform one operation at a time. Furthermore, the iterative algorithm and its convergence are extended to such a case. The efficacy of the proposed algorithms is validated by numerical experiments.

This paper considers robust multi-cell coordinated beamforming (MCBF) design for downlink wireless systems, in the presence of channel state information (CSI) errors. By assuming that the CSI errors are complex Gaussian distributed, we formulate a chance-constrained robust MCBF design problem which guarantees that the mobile stations can achieve the desired signal-to-interference-plus-noise ratio (SINR) requirements with a high probability. A convex approximation method, based on semidefinite relaxation and tractable probability approximation formulations, is proposed. The goal is to solve the convex approximation formulation in a distributed manner, with only a small amount of information exchange between base stations. To this end, we develop a distributed implementation by applying a convex optimization method, called weighted variable-penalty alternating direction method of multipliers (WVP-ADMM), which is numerically more stable and can converge faster than the standard ADMM method. Simulation results are presented to examine the chance-constrained robust MCBF design and the proposed distributed implementation algorithm.

Multicell coordinated beamforming (MCBF) has been recognized as a promising approach to enhancing the system throughput and spectrum efficiency of wireless cellular systems. In contrast to the conventional single-cell beamforming (SBF) design, MCBF jointly optimizes the beamforming vectors of cooperative base stations (BSs) (via a central processing unit (CPU)) in order to mitigate the intercell interference. While most of the existing designs assume that the CPU has the perfect knowledge of the channel state information (CSI) of mobile stations (MSs), this paper takes into account the inevitable CSI errors at the CPU, and study the robust MCBF design problem. Specifically, we consider the worst-case robust design formulation that minimizes the weighted sum transmission power of BSs subject to worst-case signal-to-interference-plus-noise ratio (SINR) constraints on MSs. The associated optimization problem is challenging because it involves infinitely many nonconvex SINR constraints. In this paper, we show that the worst-case SINR constraints can be reformulated as linear matrix inequalities, and the approximation method known as semidefinite relation can be used to efficiently handle the worst-case robust MCBF problem. Simulation results show that the proposed robust MCBF design can provide guaranteed SINR performances for the MSs and outperforms the robust SBF design.

Signal-Time Coding (STC), a novel transmission mechanism, was proposed recently. It combines the traditional encoding/modulation mode in the signal domain with the signal pulse phase modulation in the time domain and can achieve higher information flow rate in some cases for relay networks. However, there are still many fundamental problems to be investigated. This paper considers the implementing issue of STC in AWGN relay networks. Firstly, an energy detection based STC (ED-STC) scheme is proposed and the error probabilities of ED-STC in both the signal domain and the time domain are given. Secondly, a performance evaluation criterion, the reliable information per symbol (RIPS), is proposed to characterize the performance of STC in noisy wireless networks. Moreover, the performance bounds of the RIPS of ED-STC are derived. Numerical analysis show that ED-STC outperforms traditional transmission method in terms of effective information rate within some practical conditions.

This paper considers the multiuser non-regenerative MIMO relay systems in the context of the cellular downlink, where the base station simultaneously transmits data streams to multiple mobile stations through the relay station. All the nodes are equipped with multiple antennas. A joint transceiver design method is proposed to minimize the sum mean square error (MSE) of the system under the transmitted power constraints. Moreover, two special designs which the linear signal processing is performed at either the base station or relay station are studied, respectively. The closed-form expressions of the transceiver are obtained by using the Karush-Kuhn-Tucker (KKT) conditions and realized through an iterative algorithm with the guaranteed convergence, which provides a local optimal solution. Moreover, a greedy algorithm is developed to improve the performance by selecting a subset of mobile stations which have good channel conditions in each transmission. Simulation results compare different methods in terms of the average BER and the sum rate.

In this paper, we consider a two-hop multiuser amplify-and-forward MIMO relay system with multi-antenna nodes. By taking the antenna correlation and channel estimation error into account, the problems of minimum sum mean square error (MSE) transceiver optimization for the uplink and the dual downlink are formulated. When the direction of transmission is reversed and the total power constraints of the source and the relay are switched, an uplink-downlink duality in terms of average sum MSE region is established based on the Karush-Kuhn-Tucker (KKT) conditions of both problems. As a consequence of this duality, the downlink transceiver optimization satisfying the KKT conditions can be solved by focusing on an equivalent uplink problem, and vice versa. Simulation results are provided to demonstrate our analysis.

The paper considers MIMO relay networks where a source node transmits the signals to a destination node through multiple relay nodes, each of which is equipped with multiple antennas. As shown by previous studies, using multiple relay nodes to forward the signals can improve the performance. The distributed array gain can be achieved at the destination node while maintaining the maximum spatial multiplexing gain when the zero-forcing (ZF) weighting matrices are applied at the relay nodes. However, this relaying scheme cannot obtain the receive array gain simultaneously. To overcome the disadvantage, we propose a novel multiple relay nodes selection scheme based on the criterion of maximizing the minimum received SNR among all antennas at the destination node to enhance the diversity gain and the array gain. Simulation results confirm the superiority of our proposed selection scheme over the conventional ZF MIMO relaying scheme.

Based on curvelet transform this paper embeds one leveled watermark onto significant coefficients by quantization in individual frequency scales. Watermark bits come from image HASH, which is defined in the paper. Bigger coefficients are used for watermarking for the conception that coefficient energy is proportion to its directional sensitivity and bigger coefficients are more stable. Watermark is extracted without resort to the original image. The proposed watermarking can realize multifunction of content authentication and copyright protection the same time.

Multipurpose watermarking for content authentication and copyright verification are accomplished by using the multiscale curvelet transform. A curvelet transform gains better and sparser representation than most traditional multiscale transforms. In this paper, an image is decomposed into multiscale coefficients with a dyadic number of wedges constructed from a variety of neighboring scales. Image hash is designed to extract image features from an approximate scale. The image features represented in the form of bit sequences are then embedded onto the wedges by a quantization based on human visual system behavior. The implementation strategy achieves content authentications for fatigue watermarking and copyright verifications for robust watermarking. The experiments demonstrate good results to support the feasibility of using this method in multipurpose applications.