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arXiv 1702.05901cs.ITmath.IT
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降低大规模天线系统中多播的计算复杂性

Reducing the Computational Complexity of Multicasting in Large-Scale Antenna Systems

Meysam Sadeghi, Luca Sanguinetti, Romain Couillet, Chau Yuen

摘要:

本文研究了大规模天线系统中多个同信道组的物理层多播问题。每个组中的用户对共同的消息感兴趣,而不同的组具有不同的消息。特别是,我们的目标是设计的预编码向量解决所谓的服务质量(QoS)和加权最大最小公平性(MMF)的问题,假设信道状态信息是在基站(BS)。为了解决这两个问题,基线方法利用半定松弛(SDR)技术。考虑具有$N$天线的BS,SDR复杂度大于$\mathcal{O}(N^{6})$,这阻碍了其在大规模天线系统中的应用。为了克服这个问题,我们提出了两类新的算法,不仅具有显着降低计算复杂性比现有的解决方案,但也大大优于SDR的方法。此外,我们提出了变换版本的QoS和加权MMF问题之间的新型二元性。对偶性明确地确定了加权MMF问题的解决方案,给出了QoS问题的解决方案,反之亦然。数值结果被用来验证所提出的解决方案的有效性,并在不同的操作条件下与现有的替代方案进行比较。

英文摘要:

In this paper, we study the physical layer multicasting to multiple co-channel groups in large-scale antenna systems. The users within each group are interested in a common message and different groups have distinct messages. In particular, we aim at designing the precoding vectors solving the so-called quality of service (QoS) and weighted max-min fairness (MMF) problems, assuming that the channel state information is available at the base station (BS). To solve both problems, the baseline approach exploits the semidefinite relaxation (SDR) technique. Considering a BS with $N$ antennas, the SDR complexity is more than $\mathcal{O}(N^{6})$, which prevents its application in large-scale antenna systems. To overcome this issue, we present two new classes of algorithms that, not only have significantly lower computational complexity than existing solutions, but also largely outperform the SDR based methods. Moreover, we present a novel duality between transformed versions of the QoS and the weighted MMF problems. The duality explicitly determines the solution to the weighted MMF problem given the solution to the QoS problem, and vice versa. Numerical results are used to validate the effectiveness of the proposed solutions and to make comparisons with existing alternatives under different operating conditions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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