Massive multiple-input multiple-output is a very important technology for future fifth-generation systems. However, massive massive multiple input multiple output systems are still limited because of pilot contamination, impacting the data rate due to the non-orthogonality of pilot sequences transmitted by users in the same cell to the neighboring cells. We propose a channel estimation with complete knowledge of large-scale fading by using an orthogonal pilot reuse sequence to eliminate PC in edge users with poor channel quality based on the estimation of large-scale fading and performance analysis of maximum ratio transmission and zero forcing precoding methods. We derived the lower bounds on the achievable downlink DR and signal-to-interference noise ratio based on assigning PRS to a user grouping that mitigated this problem when the number of antenna elements approaches infinity The simulation results showed that a high DR can be achieved due to better channel estimation and reduced performance loss
翻译:大规模多投入多重输出是未来第五代系统非常重要的技术,但是,由于试点污染,大规模大规模多投入多重输出多重输出系统仍然有限,这影响到数据率,因为同一单元格的用户向相邻单元格传送的试验序列没有垂直性,因此数据率受到影响。我们提议通过使用正对式试点再利用序列,完全了解大规模衰退,通过使用正对式试点再利用序列,在频道质量差的边缘用户中消除个人计算机,因为根据对最大比率传输和零强制预编码方法的大规模衰退和性能分析估计,在频道质量差的边缘用户中消除个人计算机。我们从可实现的下链接DR和信号至干扰噪音率的下限值上得出了较低的界限,因为将PRS分配给一个用户群,当天线元素数量接近无限时可以缓解这一问题。模拟结果表明,由于更好的频道估计和减少性能损失,可以实现高DR。