论文标题
大量MIMO HETNETS的非合作编码:SILNR最大化预编码
Noncooperative Precoding for Massive MIMO HetNets: SILNR Maximization Precoding
论文作者
论文摘要
大量的多输入多重输出(MIMO)是提高下一代细胞系统光谱效率的关键要素。由于频道互惠,在时间划分双拼合模式下,每个基站(BS)可以在发射机(CSIT)(CSIT)中获取可能位于相邻单元格的一组用户。当配备不太如此的天线的小细胞BS被Marcrocell密集地部署时,使用本地CSIT的一种简单的非合作的MIMO预编码技术无法实现高频谱效率,因为强烈的间距间介绍(ICI)。在本文中,我们提出了一种新型的非合作质量模拟编码技术,称为信噪比 - 裂纹 - 渗透 - 裂解 - 加上noise-ratio(SILNR)最大化预码。提出的预码的关键思想是通过同时使用本地CSIT同时减轻使用者间介绍(IUI)和ICI泄漏功率来共同找到每个单元格的计划用户集,用于用户的波束成形向量以及分配的功率。为此,我们提出了一种低复杂性算法,该算法找到了总和光谱效率下限的最大化问题的局部 - 最佳解决方案,即非凸优化问题。通过系统级的模拟,我们表明,所提出的预码方法大大优于现有的非合作预码技术,而每个用户的ergodic频谱效率和速率分布。
Massive multi-input multiple-out (MIMO) is a key ingredient in improving the spectral efficiencies for next-generation cellular systems. Thanks to the channel reciprocity, in time-division-duplexing mode, each base station (BS) can acquire local channel state information at the transmitter (CSIT) for a set of users possibly located in adjacent cells. When the small cell BSs equipped with not-so-many antennas are densely deployed with marcrocells, a simple noncooperative MIMO precoding technique using local CSIT fails to achieve high spectral efficiency because of strong inter-cell-interference (ICI). In this paper, we present a novel noncooperative massive MIMO precoding technique called signal-to-interference-plus-leakage-plus-noise-ratio (SILNR) maximization precoding. The key idea of the proposed precoding is to jointly find a scheduled user set per cell, the beamforming vectors for the users, and the allocated power by simultaneously mitigating both inter-user-interference (IUI) and ICI leakage power using local CSIT. To accomplish this, we present a low-complexity algorithm that finds a local-optimal solution of the maximization problem for a lower bound of the sum spectral efficiency, i.e., a non-convex optimization problem. By system-level-simulations, we show that the proposed precoding method considerably outperforms the existing noncooperative precoding techniques in terms of the ergodic spectral efficiencies and rate distributions per user.