We provide a simple, yet general and accurate framework for analyzing zero-forcing (ZF) precoding performance for a full-dimensional massive multiple-input multiple-output system. Exploiting an order two Neumann series, our framework approximates the expected (average) ZF signal-to-noise ratio and ergodic sum spectral efficiency, while catering for a finite multipath propagation model, as well as correlated and uncorrelated user equipment (UE) positions in both azimuth and elevation domains. The analysis provides clear insights on the influence of propagation and system parameters on ZF performance. We identify how far UEs must lie in azimuth and elevation for the ZF precoder to approach uncorrelated channels. Our framework is useful for predicting the ZF performance degradation arising from channel correlation. For optimal performance, UEs could be separated by around 30$^\circ$ in azimuth and 15$^\circ$ in elevation - conditions which are difficult to meet in reality.
翻译:我们为分析一个全维大规模多投入多输出系统提供了简单、但又一般和准确的框架,用于分析一个全维、多输出多输出多输出系统的预编码性能。对两个Neumann系列的测序,我们的框架接近了预期(平均)ZF信号对噪音比率和egodic光谱效率,同时满足一个有限的多路径传播模型,以及在方位和高纬域的相联和不相干用户设备(UE)位置。分析清晰地揭示了传播和系统参数对ZF性能的影响。我们查明了铀必须处于方位和高度以至ZF预编码器接近不相关管道的方位和高度。我们的框架有助于预测从频道关系中产生的ZF性能退化。为了最佳性能,Eus可以分离出大约30 circ$的方位角和1,500 circ$的升度,这些条件在现实中难以满足。