Fixed low-resolution Analog to Digital Converters (ADC) help reduce the power consumption in millimeter-wave Massive Multiple-Input Multiple-Output (Ma-MIMO) receivers operating at large bandwidths. However, they do not guarantee optimal Energy Efficiency (EE). It has been shown that adopting variable-resolution (VR) ADCs in Ma-MIMO receivers can improve performance with Mean Squared Error (MSE) and throughput while providing better EE. In this paper, we present an optimal energy-efficient bit allocation (BA) algorithm for Ma-MIMO receivers equipped with VR ADCs under a power constraint. We derive an expression for EE as a function of the Cramer-Rao Lower Bound on the MSE of the received, combined, and quantized signal. An optimal BA condition is derived by maximizing EE under a power constraint. We show that the optimal BA thus obtained is exactly the same as that obtained using the brute-force BA with a significant reduction in computational complexity. We also study the EE performance and computational complexity of a heuristic algorithm that yields a near-optimal solution.
翻译:对数字转换器(ADC)的固定低分辨率分析有助于减少在大型带宽下运行的大型超载多发集成接收器(MA-MIMO)的电耗,然而,它们并不能保证最佳能源效率(EE)。已经表明,在MA-MIMO接收器中采用可变分辨率(VR)ADC可以改善中平方错误(MSE)和通量的性能,同时提供更好的EEE。在本文中,我们为装有VR ADC的MA-MIIMO接收器提出了一个最佳节能比特分配算法(BA),在电力限制下安装了VR ADC。我们在接收、组合和四分化信号的MSE中作为Cramer-Rao低光谱的函数,为EEEE提出了一种表达方式。一个最佳BA条件来自在电力限制下最大化EE。我们显示,由此获得的最佳BA与使用粗力BAA获得的结果完全相同,其计算复杂性大大降低。我们还研究了一种能产生近光量溶液的超振算法的 EE性算法的特性。