AI 中文总结
针对混合近远场XL-MIMO系统，提出基于加权速率排序的连续干扰消除方案及集成LDPC编码与信道估计的迭代检测译码框架，数值验证其性能优于现有方法。
AI 中文摘要
超大规模多输入多输出（XL-MIMO）系统为近场和远场区域的用户提供服务，其球面波前传播相较于传统远场系统提供了增强的空间分辨率。在本工作中，我们提出了一种新颖的基于加权速率（WR）排序的连续干扰消除（SIC）方案，该方案利用了近场传播固有的空间自由度。我们还开发了一个迭代检测与译码（IDD）框架，将所提出的WR排序与低密度奇偶校验（LDPC）编码和信道估计相结合。随后，我们分析了信息速率以及近场信道特性的影响。数值结果表明，所提出的WR-SIC和IDD方案优于现有方法。
英文摘要
Extra-large multiple-input multiple-output (XL-MIMO) systems {serving users across near-field and far-field regions} experience spherical wavefront propagation that provides enhanced spatial resolution over traditional far-field systems. In this work, we propose a novel weighted rate (WR) ordering-based successive interference cancellation (SIC) scheme that exploits the spatial degrees of freedom inherent in near-field propagation. We also develop an iterative detection and decoding (IDD) framework that integrates the proposed WR ordering with low-density parity-check (LDPC) coding and channel estimation. We then analyze the information rates and the impact of near-field channel characteristics. Numerical results show that the proposed WR-SIC and the IDD scheme outperform existing approaches.
Comments3 figures, 6 pages
