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Downlink MU-MIMO With QoS Aware Transmission: Precoder Design and Performance Analysis

机译:具有QoS感知传输功能的下行MU-MIMO:预编码器设计和性能分析

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In this paper, a downlink wireless communication channel is considered. The base station (BS) has common data for all users, unicast data for a set of intended users, and transmits the superposition of these messages. This setting neither falls into the non-orthogonal multiple access (NOMA) nor into the multi-group multicasting literatures. In NOMA systems, the BS has unicast data for all users, and multiple users share the same resources. In multi-group multicasting, there are non-overlapping groups, each demanding a different multicast message. This paper studies precoder design to achieve maximum weighted sum rate (WSR). It is first shown that the precoders designed for WSR maximization and weighted minimum mean square error (WMMSE) minimization are equivalent. Second, an iterative low complexity algorithm (named WMMSE), based on WMMSE transmit precoders and receivers, is proposed. Another low-complexity precoder, the phase aligned zero forcing (PAZF) precoder, is also introduced. The results show that both algorithms converge fast. The WMMSE algorithm outperforms both PAZF and the zero-forcing (ZF) precoder for all signal-to-noise ratio ranges. It offers better interference management and high coherent combining gains for common data while PAZF finds the optimal phase rotation on the ZF precoder, and increases coherent combining gains.
机译:在本文中,考虑了下行链路无线通信信道。基站(BS)具有所有用户的公共数据,一组目标用户的单播数据,并传输这些消息的叠加。此设置既不属于非正交多路访问(NOMA),也不属于多组多播文献。在NOMA系统中,BS具有所有用户的单播数据,并且多个用户共享相同的资源。在多组多播中,有不重叠的组,每个组都要求一个不同的多播消息。本文研究预编码器设计,以实现最大加权总和(WSR)。首先表明,为WSR最大化和加权最小均方误差(WMMSE)最小化而设计的预编码器是等效的。其次,提出了一种基于WMMSE发送预编码器和接收器的迭代低复杂度算法(称为WMMSE)。还介绍了另一种低复杂度的预编码器,即相位对齐调零(PAZF)预编码器。结果表明,两种算法都能快速收敛。对于所有信噪比范围,WMMSE算法的性能均优于PAZF和迫零(ZF)预编码器。它为公共数据提供了更好的干扰管理和较高的相干合并增益,而PAZF在ZF预编码器上找到了最佳的相位旋转,并增加了相干合并增益。

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