论文标题
无细胞的巨大咪咪与物联网的非正交飞行员
Cell-Free Massive MIMO with Nonorthogonal Pilots for Internet of Things
论文作者
论文摘要
我们考虑根据无细胞大型MIMO原理组织的物联网（IoT）。由于事物的数量很大，即使事物是静止的，也不能将正交飞行员分配给所有这些飞行员。这导致了不可避免的飞行员污染问题，这一事实使事实变得更加恶化：由于物联网的运行功率非常低。为了减轻此问题并达到高吞吐量，我们使用具有最佳线性最小平方误差（LMMSE）通道估计的无单元系统，而传统上简单的次优估计器已在此类系统中使用。我们进一步得出了这种情况的分析上行链路和下行链路信号与噪声比率（SINR）表达式，这仅取决于大规模褪色系数。这使我们能够设计新的功率控制算法，仅需要很少发射功率适应。模拟结果表明，上行链路和下行链路吞吐量提高了40％，与现有无单元的无线系统相比，能源效率为95％，至少比基于小型细胞系统的IoT系统至少提高了三倍的上行链路链路链路链接改善。
We consider Internet of Things (IoT) organized on the principles of cell-free massive MIMO. Since the number of things is very large, orthogonal pilots cannot be assigned to all of them even if the things are stationary. This results in an unavoidable pilot contamination problem, worsened by the fact that, for IoT, since the things are operating at very low transmit power. To mitigate this problem and achieve a high throughput, we use cell-free systems with optimal linear minimum mean squared error (LMMSE) channel estimation, while traditionally simple suboptimal estimators have been used in such systems. We further derive the analytical uplink and downlink signal-to-interference-plus-noise ratio (SINR) expressions for this scenario, which depends only on large scale fading coefficients. This allows us to design new power control algorithms that require only infrequent transmit power adaptation. Simulation results show a 40% improvement in uplink and downlink throughputs and 95% in energy efficiency over existing cell-free wireless systems and at least a three-fold uplink improvement over known IoT systems based on small-cell systems.
