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Energy-Efficient Coordinated Multi-Cell Multigroup Multicast Beamforming with Antenna Selection

机译:通过天线选择的节能协调多电池多群多播波束成形

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This paper studies energy-efficient coordinated beamforming in multi-cell multi-user multigroup multicast multiple-input single-output systems. We aim at maximizing the network energy efficiency by taking into account the fact that some of the radio frequency chains can be switched off in order to save power. We consider the antenna specific maximum power constraints to avoid non-linear distortion in power amplifiers and user-specific quality of service (QoS) constraints to guarantee a certain QoS levels. We first introduce binary antenna selection variables and use the perspective formulation to model the relation between them and the beamformers. Subsequently, we propose a new formulation which reduces the feasible set of the continuous relaxation, resulting in better performance compared to the original perspective formulation based problem. However, the resulting optimization problem is a mixed-Boolean non-convex fractional program, which is difficult to solve. We follow the standard continuous relaxation of the binary antenna selection variables, and then reformulate the problem such that it is amendable to successive convex approximation. Thereby, solving the continuous relaxation mostly results in near-binary solution. To recover the binary variables from the continuous relaxation, we switch off all the antennas for which the continuous values are smaller than a small threshold. Numerical results illustrate the superior convergence result and significant achievable gains in terms of energy efficiency with the proposed algorithm.
机译:本文研究了多单元多用户多群多播多播多播多播多播的节能协调波束成形。我们的目的是通过考虑到一些射频链可以关闭以最大限度地提高网络能效,以便节省电力。我们考虑天线特定的最大功率约束,以避免功率放大器中的非线性失真和用户特定的服务质量(QoS)约束,以保证某个QoS级别。我们首先介绍二进制天线选择变量,并使用透视布制定来模拟它们与波束形成器之间的关系。随后,我们提出了一种新的制剂,其减少了可行性放松的可行性集,导致与基于原始的透视制剂的问题相比更好的性能。然而,所得到的优化问题是混合布尔非凸分数程序,这很难解决。我们遵循二进制天线选择变量的标准连续放松,然后重构问题,使得它可以连续凸起近似。由此,求解连续弛豫主要导致近二元溶液。为了从连续放松恢复二进制变量,我们关闭所有天线,连续值小于小阈值。数值结果说明了具有所提出的算法的能效的优异收敛结果和显着的可实现的增益。

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