This paper investigates joint antenna selection and optimal transmit power in multi cell massive multiple input multiple output systems. The pilot interference and activated transmit antenna selection plays an essential role in maximizing energy efficiency. We derived the closed-form of maximal energy efficiency with complete knowledge of large-scale fading with maximum ratio transmission while accounting for channel estimation and eliminated pilot contamination when the antennas approach infinity. We investigated joint optimal antenna selection and optimal transmit power under minimized reuse of pilot sequences based on a novel iterative low-complexity algorithm for Lagrange multiplayer and Newton methods. The two scenarios of achievable high data rate and total transmit power allocation are critical to the performance maximal energy efficiency. We propose new power consumption for each antenna based on the transmit power amplifier and circuit power consumption to analyze exact power consumption. The simulation results show that maximal energy efficiency could be achieved using the iterative low complexity algorithm based on the reasonable maximum transmit power when the noise power was less than the power received pilot. The proposed low complexity iterative algorithm offers maximum energy efficiency by repeating a minimized pilot signal until the optimal antenna selection and transmission power are achieved.
翻译:本文调查了多细胞大规模多输入多输出系统中的联合天线选择和最佳传输动力。试点干扰和激活传输天线选择在最大限度地提高能源效率方面发挥着至关重要的作用。我们从最大能效封闭形式中推导出,完全了解最大比率传输的大规模衰减,同时计及频道估计,并在天线接近无限时消除了试验污染。我们调查了联合最佳天线选择和最佳传输动力,在基于Lagrange多功能者和牛顿方法的新颖的迭接低复合算法的试验序列中最大限度地再利用试验序列。两种可实现的高数据率和总传输功率分配的情景对性能最大化能源效率至关重要。我们根据传输电源放大器和电路能消耗量提出每种天线的新电消耗量,以分析准确的电耗。模拟结果表明,在噪音功率低于所接受的试电量时,可以使用基于合理最大传输力的迭接低复杂性算法实现最大能源效率。提议的低复杂迭代算法通过重复最小的试验信号,实现最大能效。