论文标题
具有随机部署用户的MIMO-NOMA系统的性能分析
Performance Analysis of MIMO-NOMA Systems with Randomly Deployed Users
论文作者
论文摘要
This paper investigates the performance of Multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) systems with randomly deployed users, where the randomly deployed NOMA users follow Poisson point process (PPP), the spatial correlation between MIMO channels are characterized by using Kronecker model, and the composite channel model is used to capture large-scale fading as well as small-scale fading.用户分布的空间随机性，天线之间的空间相关性和大规模褪色将严重影响系统性能，但是在先前的文献中，很少考虑它们用于MIMO-NOMA系统，并且对所有这些影响因素的考虑都会挑战分析。基于零强度（ZF）检测，平均停战概率和平均好评的精确表达式均以封闭形式得出。此外，对高信噪比（SNR）（/小细胞半径）和低SNR（/大细胞半径）进行了渐近分析，以获得更多有见地的结果。特别是，多样性顺序由$δ= {{n_r} - {m} + 1} $，$ k $ - 最接近基站用户的平均中断概率遵循$ o \ left的比例定律（{d^{d^{α\ left） scales as $O({D^{2}})$ and $O({D^{-2}})$ as $D \to 0$ and $D \to \infty$, respectively, where $N_r$, $M$, $α$ and $D$ stand for the number of receive antennas, the total number of data streams, the path loss exponent and the cell radius, respectively.分析结果最终通过数值分析得到验证。
This paper investigates the performance of Multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) systems with randomly deployed users, where the randomly deployed NOMA users follow Poisson point process (PPP), the spatial correlation between MIMO channels are characterized by using Kronecker model, and the composite channel model is used to capture large-scale fading as well as small-scale fading. The spatial randomness of users' distribution, the spatial correlation among antennas and large-scale fading will severally impact the system performance, but they are seldom considered in prior literature for MIMO-NOMA systems, and the consideration of all these impact factors challenges the analysis. Based on zero-forcing (ZF) detection, the exact expressions for both the average outage probability and the average goodput are derived in closed-form. Moreover, the asymptotic analyses are conducted for both high signal-to-noise ratio (SNR) (/small cell radius) and low SNR (/large cell radius) to gain more insightful results. In particular, the diversity order is given by $δ= {{N_r} - {M} + 1}$, the average outage probability of $k$-th nearest user to the base station follows a scaling law of $O\left({D^{α\left( {{N_r} - {M} + 1} \right) + 2k}}\right)$, the average goodput scales as $O({D^{2}})$ and $O({D^{-2}})$ as $D \to 0$ and $D \to \infty$, respectively, where $N_r$, $M$, $α$ and $D$ stand for the number of receive antennas, the total number of data streams, the path loss exponent and the cell radius, respectively. The analytical results are finally validated through the numerical analysis.
