In this work, we present block diagonalization and power allocation algorithms for large-scale multiple-antenna systems with coarsely quantized signals. In particular, we develop Coarse Quantization-Aware Block Diagonalization ${\scriptstyle\mathrm{\left(CQA-BD\right)}}$ and Coarse Quantization-Aware Regularized Block Diagonalization ${\scriptstyle\mathrm{\left(CQA-RBD\right)}}$ precoding algorithms that employ the Bussgang decomposition and can mitigate the effects of low-resolution signals and interference. Moreover, we also devise the Coarse Quantization-Aware Most Advantageous Allocation Strategy ${\scriptstyle\mathrm{\left(CQA-MAAS\right)}}$ power allocation algorithm to improve the sum rate of precoders that operate with low-resolution signals. An analysis of the sum-rate performance is carried out along with computational complexity and power consumption studies of the proposed and existing techniques. Simulation results illustrate the performance of the proposed ${\scriptstyle\mathrm{CQA-BD}}$ and ${\scriptstyle\mathrm{CQA-RBD}}$ precoding algorithms, and the proposed ${\scriptstyle\mathrm{CQA-MAAS}}$ power allocation strategy against existing approaches.
翻译:在这项工作中,我们为大型多抗安那系统提供块分解和权力分配算法,这些算法使用Bussgang分解法,并能够减轻低分辨率信号和干扰的影响。此外,我们还设计了粗定量-软件块对立法(CQA-BDright) $和粗量化-软件对立法(CQA-BDright),以及粗量化-软件块对立法(CQA-BDright),以提高使用低分辨率信号运行的预装配商总和率(CQA-RBDright) 。在对拟议和现有技术的计算复杂性和动力消费研究的同时,还分析了拟议和现行QQQ-C的计算复杂性和动力消费方法。