Massive multiuser multiple input multiple output (MU‐MIMO) system is aimed to improve throughput and spectral efficiency through a large number of antennas incorporated at the transmitter and/or receiver. However, the MU‐MIMO system usually suffers from interantenna interference (IAI) and multiuser interference (MUI). The IAI imposes due to closely spaced antennas at each user equipment (UE), and MUI is enforced when one user comes under the vicinity of another user in the same cellular network. Most of the previous literatures considered any one of these interferences. However, the present work proposes singular value decomposition (SVD) precoding‐assisted user‐level local likelihood ascent search (LLAS) algorithm to mitigate both IAI and MUI. In the uplink MU‐MIMO, the IAI is cancelled by SVD, and the residual MUI is mitigated by LLAS detection. The LLAS detection balances the trade‐off between the classical suboptimal likelihood ascent search (LAS) and optimal maximum likelihood (ML) detection techniques. The proposed LLAS performs local search among all 2M_T‐dimensional neighborhood vectors at each UE, where M_T represents number of transmitting antennas of each UE. Thus, its performance is near optimal, and its complexity is much lower than ML detector.

中文翻译：

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编码大规模MU-MIMO系统的基于近似最优局部似然搜索的检测算法设计

大规模多用户多输入多输出（MU‐MIMO）系统旨在通过在发射机和/或接收机处集成大量天线来提高吞吐量和频谱效率。但是，MU-MIMO系统通常会遭受天线间干扰（IAI）和多用户干扰（MUI）。由于每个用户设备（UE）上的天线间距太近，IAI受到限制，并且当一个用户进入同一蜂窝网络中的另一个用户附近时，将强制执行MUI。先前的大多数文献都考虑了这些干扰中的任何一种。但是，本工作提出了奇异值分解（SVD）预编码辅助的用户级局部似然性上升搜索（LLAS）算法，以减轻IAI和MUI的影响。在上行链路MU-MIMO中，通过SVD消除了IAI，通过LLAS检测减轻了残留的MUI。LLAS检测可在经典的次优似然上升搜索（LAS）和最佳最大似然（ML）检测技术之间取得平衡。拟议的LLAS在所有2个之间执行本地搜索每个UE的M _T维邻域矢量，其中M _T代表每个UE的发射天线数。因此，其性能接近最佳，并且其复杂度远低于ML检测器。