This paper considers joint linear processing at multi-antenna sources and one multiple-input multiple-output (MIMO) relay station for both one-way and two-way relay-assisted wireless communications. The one-way relayi...
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This paper considers joint linear processing at multi-antenna sources and one multiple-input multiple-output (MIMO) relay station for both one-way and two-way relay-assisted wireless communications. The one-way relaying is applicable in the scenario of downlink transmission by a multi-antenna base station to multiple single-antenna users with the help of one MIMO relay. In such a scenario, the objective of join linear processing is to maximize the information throughput to users. The design problem is equivalently formulated as the maximization of the worst signal-to-interference-plus-noise ratio (SINR) among all users subject to various transmission power constraints. Such a program of nonconvex objective minimization under nonconvex constraints is transformed to a canonical d.c. (difference of convex functions/sets) program of d.c. function optimization under convex constraints through nonconvex duality with zero duality gap. An efficient iterative algorithm is then applied to solve this canonical d.c program. For the scenario of using one MIMO relay to assist two sources exchanging their information in two-way relying manner, the joint linear processing aims at either minimizing the maximum mean square error (MSE) or maximizing the total information throughput of the two sources. By applying tractable optimization for the linear minimum MSE estimator and d.c. programming, an iterative algorithm is developed to solve these two optimization problems. Extensive simulation results demonstrate that the proposed methods substantially outperform previously-known joint optimization methods.
This paper considers the joint source and relay precoding design for millimeter-wave (mm-wave) systems under the assumption that the source, relay, and destination nodes are equipped with multiple antennas. We focus o...
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This paper considers the joint source and relay precoding design for millimeter-wave (mm-wave) systems under the assumption that the source, relay, and destination nodes are equipped with multiple antennas. We focus on the rate maximization problem with the per antenna power constraints at the source and relay while taking into account the computational complexity and sparse characteristics of mm-wave channels. We solve this problem as follows. First, the precoding problem is formulated by exploiting the sparse and low-rank structures of mm-wave channels which is nonconvex. Second, we reformulate this nonconvex problem into two semidefinite programming (SDP) subproblems, each having a rank one constraint. Third, we propose two algorithms to solve these two SDP subproblems: interior-point-based and low complexity algorithms. Finally, the original rate maximization problem is examined by iteratively utilizing the solutions of these SDP problems. The proposed interior-point-based method to solve the SDP problem uses the standard convex optimization tools followed by the random vector generation scheme to get the rank one solution. However, the proposed low complexity algorithm examines the SDP problem in one-dimensional spatial signal space (i.e., without rank relaxation) via a new augmented Lagrangian function method. Simulation results show that both algorithms achieve good performances, and the latter one is much faster than the former one with a slight decrease in performance. In addition, both algorithms achieve superior performances compared to the existing precoding design algorithms.
Effective communication strategies with a properly designed source precoding matrix (PM) and a properly designed relay beamforming matrix (BM) can significantly improve the spectral efficiency of multiple-input multip...
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Effective communication strategies with a properly designed source precoding matrix (PM) and a properly designed relay beamforming matrix (BM) can significantly improve the spectral efficiency of multiple-input multiple-output (MIMO) relaying broadcast channels (RBCs). In the present paper, we first propose a general communication scheme with non-regenerative relay that can overcome the half-duplex relay constraint of the general MIMO-RBC. Based on the proposed scheme, the robust source PM and relay BM are designed for imperfect channel state information at the transmitter (CSIT). In contrast to the conventional non-regenerative relaying communication scheme for the MIMO-RBC, in the proposed scheme, the source can send information continuously to the relay and users during two phases. Furthermore, in conjunction with the advanced precoding strategy, the proposed scheme can achieve a full-degree-of-freedom (DoF) MIMO-RBC with that each entry in the related channel matrix is considered to an i.i.d. complex Gaussian variable. The robust source PM and relay BM designs were investigated based on both throughput and fairness criteria with imperfect CSIT. However, solving the problems associated with throughput and fairness criteria for the robust source PM and relay BM designs is computationally intractable because these criteria are non-linear and non-convex. In order to address these difficulties, we first set up equivalent optimization problems based on a tight lower bound of the achievable rate. We then decompose the equivalent throughput problem into several decoupled subproblems with tractable solutions. Finally, we obtain the suboptimal solution for the throughput problem by an alternating optimization approach. We solve the fairness problem by introducing an adjusted algorithm according to the throughput problem. Finally, we demonstrate that, in both cases of throughput and fairness criteria, the proposed relaying communication scheme with precoding algorithms out
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