论文标题
对具有低分辨率的MIMO系统的粗量化感知块对角线化算法的研究
Study of Coarse Quantization-Aware Block Diagonalization Algorithms for MIMO Systems with Low Resolution
论文作者
论文摘要
众所周知，数字对模拟转换器（DAC）的估计能量消耗约为模拟转换器（ADC）消耗的能量的30％，保持固定的采样率和位分辨率。假设与ADC类似，DAC耗散会随着每一个额外的分辨率加倍，两个分辨率位减少，例如从4位到2位，代表75 $ \％$ $下的耗散。 1位量化的总和率的当前限制促使研究人员考虑额外的分辨率，以获得更高级别的总和率。此后，我们使用基于Bussgang定理的多个Antenna系统的广播通道来设计粗量化的预码。特别是，我们考虑了块对角线化算法，这些算法在迄今为止尚未在文献中被考虑。拟议的粗量化感知块对角线（CQA-BD）及其正则化版本（CQA-RBD）所达到的总和率优于文献中先前报道的。模拟说明了针对现有方法的拟议CQA-BD和CGA-RBD算法的性能。
It is known that the estimated energy consumption of digital-to analog converters (DACs) is around 30\% of the energy consumed by analog-to-digital converters (ADCs) keeping fixed the sampling rate and bit resolution. Assuming that similarly to ADC, DAC dissipation doubles with every extra bit of resolution, a decrease in two resolution bits, for instance from 4 to 2 bits, represents a 75$\% $ lower dissipation. The current limitations in sum-rates of 1-bit quantization have motivated researchers to consider extra bits in resolution to obtain higher levels of sum-rates. Following this, we devise coarse quantization-aware precoding using few bits for the broadcast channel of multiple-antenna systems based on the Bussgang theorem. In particular, we consider block diagonalization algorithms, which have not been considered in the literature so far. The sum-rates achieved by the proposed Coarse Quantization-Aware Block Diagonalization (CQA-BD) and its regularized version (CQA-RBD) are superior to those previously reported in the literature. Simulations illustrate the performance of the proposed CQA-BD and CGA-RBD algorithms against existing approaches.
