Design of amplify and forward MIMO relay networks with QoS constraint (original) (raw)
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ABSTRACTWe investigate the problem of precoding optimization in an amplify‐and‐forward multiple‐input‐multiple‐output relay system. Most reported works on this problem focus chiefly on the design of relay precoder without simultaneously optimizing the direct link. In this paper, we propose a method for joint source/relay precoder design, taking both direct and relay links into account. Our design is based on maximizing the mutual information (MI) under limited transmission power constraints at the source and relay, respectively. We first formulate a constrained optimization problem before relaxing the original cost function for tractability and derive a MI lower bound. This elaborate bound can asymptotically approach the exact expression of MI in an iterative fashion. In contrast to previous strategies, we then prove that the optimal structure of the source and relay precoders jointly convert the multiple‐input‐multiple‐output relay channel into a bank of single‐input‐single‐output ...
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We consider a wireless communication scenario with K source-destination pairs communicating through several half-duplex amplify-and-forward relays. We design the relay beamforming matrices by minimizing the total power transmitted from all the relays subject to quality of service constraints on the received signal to interference-plus-noise ratio at each destination node. We propose a novel method for solving the resulting nonconvex optimization problem in which the problem is decomposed into a group of second-order cone programs (SOCPs) parameterized by K real parameters. Grid search or nested bisection can be used to search for the optimal values of these parameters. We provide numerical simulations showing the superior performance of the proposed algorithms compared to earlier suboptimal approximations and their ability to approach the globally optimal solution of the non-convex problem.
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Optimization problems of beamforming in multi-user amplify-and-forward (AF) wireless relay networks are indefinite (nonconvex) quadratic programs, which require effective computational solutions. Solutions to these problems have often been obtained by relaxing the original problems to semi-definite programs (SDPs) of convex optimization. Most existing works have claimed that these relaxed SDPs actually provide the optimal beamforming solutions. This paper, however, shows that this is not the case in many practical scenarios where SDPs fail to provide even a feasible beamforming solution. To fill this gap, we develop in this paper a nonsmooth optimization algorithm, which provides the optimal solution at low computational complexity.
2016
The problem of sum-rate maximization in two-way amplify-and-forward (AF) multiple-input multiple-output (MIMO) relaying is considered. Mathematically, this problem is equivalent to the constrained maximization of the product of quadratic ratios that is a non-convex problem. Such prob-lems appear also in many other applications. This problem can be further relaxed into a difference-of-convex functions (DC) programming problem, which is typically solved using the branch-and-bound method without polynomial-time com-plexity guarantees. We, however, develop a polynomial-time convex optimization-based algorithm for solving the corre-sponding DC programming problem named polynomial-time DC (POTDC). POTDC is based on a specific parameter-ization of the problem, semi-definite programming (SDP) relaxation, linearization, and iterations over a single param-eter. The complexity of the problem solved at each iteration of the algorithm is equivalent to that of the SDP problem. The effectiveness o...