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Rate Analysis for NOMA in Massive MIMO Based Stochastic Cellular Networks with Pilot Contamination

机译:基于大规模MIMO的具有先导污染的随机蜂窝网络中NOMA的速率分析

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Massive multiple-input multiple-output (MIMO) enabled base stations employing non-orthogonal multiple access (NOMA) hold immense potential in increasing the spectral efficiency of future cellular networks. In this paper, we evaluate the achievable rate of N-user NOMA under a Poisson process of massive MIMO enabled base stations. We adopt a timedivision duplexing (TDD) mode, where the uplink pilots are reused among the different base stations, and within each NOMA cluster of each base station, while matched-filter based precoding is employed in the downlink. The achievable rate by a typical NOMA user is characterized by taking into account imperfect successive interference cancellation (SIC) and error propagation. To this end, the moment generating function of the interference from other base stations due to pilot contamination is derived along with the signal detection probability. It is shown that NOMA can significantly improve the rate performance under most system parameters, and that the rate performance can be increased further through denser networks. Moreover, we show that the individual user rates and fairness amongst users within a NOMA cluster are significantly impacted by the specific power allocation algorithm.
机译:采用非正交多址(NOMA)的大规模多输入多输出(MIMO)的基站采用非正交多址(NOMA),增加了增加未来蜂窝网络的光谱效率的巨大潜力。在本文中,我们评估了大量MIMO的基站的泊松过程下的N用户NOMA的可实现速率。我们采用定时性双工(TDD)模式,其中上行链路导频在不同的基站中重复使用,并且在每个基站的每个NOMA簇内,而在下行链路中采用基于匹配的滤波器的预编码。通过典型的NOMA用户可实现的速率,其特征在于考虑不完全的连续干扰消除(SIC)和误差传播。为此,由于信号检测概率导出由于导频污染引起的其他基站的干扰的瞬间产生函数。结果表明,NOMA可以在大多数系统参数下显着提高速率性能,并且可以通过更密集网络进一步提高速率性能。此外,我们表明,NOMA集群中的用户之间的个人用户速率和公平性受到特定功率分配算法的显着影响。

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