论文标题
大规模量化通信系统中的基于培训的等效关系
Training-Based Equivalence Relations in Large-Scale Quantized Communication Systems
论文作者
论文摘要
我们表明，可以通过以规定的方式修改信号功率和噪声方差来检查具有未知参数和训练信号的量化大型系统和训练信号。显示了无线通信和信号处理中培训的应用。在无线通信中，我们表明训练信号的最佳数量可能明显小于传输元素的数量。只要接收元素的数量足够大，就可以在考虑信号处理应用中考虑符号错误率时得出类似的结论。我们表明，当热噪声高或系统接近其饱和速率时，量化系统中训练的线性分析可能是准确的。
We show that a quantized large-scale system with unknown parameters and training signals can be analyzed by examining an equivalent system with known parameters by modifying the signal power and noise variance in a prescribed manner. Applications to training in wireless communications and signal processing are shown. In wireless communications, we show that the optimal number of training signals can be significantly smaller than the number of transmitting elements. Similar conclusions can be drawn when considering the symbol error rate in signal processing applications, as long as the number of receiving elements is large enough. We show that a linear analysis of training in a quantized system can be accurate when the thermal noise is high or the system is operating near its saturation rate.
