4.7 Article

Capacity-Achieving MIMO-NOMA: Iterative LMMSE Detection

期刊

IEEE TRANSACTIONS ON SIGNAL PROCESSING
卷 67, 期 7, 页码 1758-1773

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2019.2896242

关键词

MIMO-NOMA; iterative LMMSE; capacity achieving; low-complexity multi-user detection; multi-user code

资金

  1. National Natural Science Foundation of China [61671345, 61750110529]
  2. Ministry of Education of People's Republic of China [6141A02022338]
  3. China Scholarship Council [20140690045]

向作者/读者索取更多资源

This paper considers a low-complexity iterative linear minimum mean square error (LMMSE) multiuser detector for the multiple-input and multiple-output system with nonorthogonal multiple access (MIMO-NOMA), where multiple single-antenna users simultaneously communicate with a multiple-antenna base station (BS). While LMMSE being a linear detector has a low complexity, it has suboptimal performance in multiuser detection scenario due to the mismatch between LMMSE detection and multiuser decoding. Therefore, in this paper, we provide the matching conditions between the detector and decoders for MIMO-NOMA, which are then used to derive the achievable rate of the iterative detection. We prove that a matched iterative LMMSE detector can achieve the optimal capacity of symmetric MIMO-NOMA with any number of users, the optimal sum capacity of asymmetric MIMO-NOMA with any number of users, all the maximal extreme points in the capacity region of asymmetric MIMO-NOMA with any number of users, and all points in the capacity region of two-user and three-user asymmetric MIMO-NOMA systems. In addition, a kind of practical low-complexity error-correcting multiuser code, called irregular repeat-accumulate code, is designed to match the LMMSE detector. Numerical results shows that the bit error rate performance of the proposed iterative LMMSE detection outperforms the state-of-art methods and is within 0.8 dB from the associated capacity limit.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据