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arXiv 1701.05166cs.ITmath.IT
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大规模天线系统中上行干扰的抑制

Uplink Interference Reduction in Large Scale Antenna Systems

Ansuman Adhikary, Alexei Ashikhmin, Thomas L. Marzetta

摘要:

大规模MIMO系统需要大量(数十或数百个)基站天线来服务数量少得多的终端。与传统的MIMO技术相比,这些系统在频谱和能量效率方面表现出很大的增益。随着天线数量的增加,大规模MIMO系统的性能受到导频污染引起的干扰的限制。A. Ashikhmin和T. Marzetta提出了基于基站之间的有限协作的大规模衰落预编码(LSFP)和解码(LSFD)(以导频污染预编码的名义)。他们表明,迫零LSFP和LSFD完全消除了导频污染,并随着天线数量的增加而导致无限的吞吐量。在本文中,我们专注于上行链路,并表明,即使在有限数量的基站天线的情况下,LSFD产生一个非常大的性能增益。特别是,我们的算法之一给出了超过140倍的增加,在5%的中断数据传输率!我们表明,可以通过优化用户的传输功率进一步提高性能。最后,我们提出了分散的LSFD,只需要有限的合作,相邻细胞之间。

英文摘要:

A massive MIMO system entails a large number (tens or hundreds) of base station antennas serving a much smaller number of terminals. These systems demonstrate large gains in spectral and energy efficiency compared with conventional MIMO technology. As the number of antennas grows, the performance of a massive MIMO system gets limited by the interference caused by pilot contamination. Earlier A. Ashikhmin and T. Marzetta proposed (under the name of Pilot Contamination Precoding) Large Scale Fading Precoding (LSFP) and Decoding (LSFD) based on limited cooperation between base stations. They showed that Zero-Forcing LSFP and LSFD eliminate pilot contamination entirely and lead to an infinite throughput as the number of antennas grows. In this paper, we focus on the uplink and show that even in the case of a finite number of base station antennas, LSFD yields a very large performance gain. In particular, one of our algorithms gives a more than 140 fold increase in the 5% outage data transmission rate! We show that the performance can be improved further by optimizing the transmission powers of the users. Finally, we present decentralized LSFD that requires limited cooperation only between neighboring cells.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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