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首页> 外文期刊>IEEE transactions on wireless communications >Joint Source-Relay Optimization for Fixed Receivers in Multi-Antenna Multi-Relay Networks
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Joint Source-Relay Optimization for Fixed Receivers in Multi-Antenna Multi-Relay Networks

机译:多天线多中继网络中固定接收机的联合源-中继优化

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We jointly optimize the source and relay precoders for multi—antenna multi—relay networks employing a prefixed receiver. Prefixed receivers are of practical interest since they enable low complexity at the end—user's receiver as well as backward compatibility. To compute the source and relay precoders, we consider two different criteria. The objective of the first criterion is to maximize the worst stream signal—to—interference—plus—noise ratio (SINR) at the output of the receiver subject to source and relay transmit power constraints. Under the second criterion, we minimize the source and relay transmit powers subject to a certain quality—of—service constraint. Both optimization problems are non—convex. To solve them, we propose iterative alternating algorithms, where, in each iteration, we compute the precoders alternately, i.e., for each precoder optimization, we fix all the precoders except the one which is optimized. For both criteria, we formulate the optimization problem for the computation of the source precoder as a second order cone programming (SOCP) problem, for which the optimal solution can be found using interior point algorithms. For each relay precoder, we formulate the optimization problem as a semidefinite relaxation (SDR) problem for which ready—to—use solvers exist. If the solution to the SDR problem is not of rank one, matrix rank—one decomposition or randomization is applied. We also provide sufficient conditions for the convergence of the proposed iterative alternating algorithms to a fixed point. Simulation results show that the performance of the proposed algorithms is close to the performance achieved if the source, relay, and receiver filters are jointly optimized.
机译:我们联合优化了使用前缀接收器的多天线多中继网络的源和中继预编码器。前缀接收器具有实际意义,因为它们使最终的低复杂度(用户的接收器)以及向后兼容性成为可能。为了计算源和中继预编码器,我们考虑了两个不同的标准。第一个标准的目的是在受源和中继发射功率约束的情况下,使接收机输出端的最差流信号-干扰加噪声比(SINR)最大化。根据第二个标准,我们将源和中继的发射功率降到最低,这要取决于一定的服务质量约束。这两个优化问题都是非凸的。为了解决这些问题,我们提出了迭代交替算法,其中在每次迭代中我们交替计算预编码器,即对于每个预编码器优化,我们固定除已优化的编码器之外的所有预编码器。对于这两个标准,我们将用于源预编码器计算的优化问题公式化为二阶锥规划(SOCP)问题,可以使用内点算法找到其最佳解决方案。对于每个中继预编码器,我们将优化问题表述为存在半确定松弛(SDR)问题,对于该问题存在准备使用的求解器。如果SDR问题的解决方案不是一等的,则应用矩阵一等分(分解或随机化)。我们还为将迭代交替算法收敛到固定点提供了充分条件。仿真结果表明,所提出算法的性能与联合优化源滤波器,中继滤波器和接收机滤波器的性能接近。

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