首页|大规模离散MU-MIMO:低复杂度、信息理论最优检测与多用户编码

大规模离散MU-MIMO:低复杂度、信息理论最优检测与多用户编码

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研究了一种实际的大规模离散多用户多输入多输出(MU-MIMO)系统,涵盖了大规模天线与用户、实用的信道编译码、任意输入分布、仅接收机已知信道状态信息、一般右酉不变信道矩阵、模数转化器等实际通信约束.针对理想和低分辨率模数转换器下的大规模离散MU-MIMO系统,分别提出了低复杂度、信息理论最优接收机和多用户码设计准则,并给出实际多用户低密度奇偶校验码(LDPC)设计.数值实验证实所设计的多用户LDPC比现有的单用户LDPC获得了2～5 dB性能增益,同时还解决在信道恶劣和低分辨率模数转换器下单用户码无法准确恢复信息的难题,揭示了现有贝叶斯最优接收机与单用户码直接结合不再是最优方案.
Massive Discrete MU-MIMO:Low-Complexity Information-Theoretically Optimal Detection and Multi-User Coding
A practical massive discrete multi-user multiple-input multiple-output(MU-MIMO)system is studied,which includes massive an-tennas and users,practical channel coding and decoding,arbitrary input distributions,available channel state information at the receiver,gen-eral right-unitarily-invariant channel matrices,and the analog-to-digital converter.For massive discrete MU-MIMO systems with ideal and low-resolution analog-to-digital converters,the low-complexity and information-theoretically optimal receiver and multi-user code design principles are proposed,respectively,on which practical multi-user low-density parity-check codes(LDPC)are designed.Numerical results show that the designed multi-user LDPC can achieve a performance gain of up to 2～5 dB over the existing single-user LDPC.They also ad-dress the issue that single-user codes cannot successfully recover information under poor channel and low-resolution analog-to-digital converters,and reveal that the direct combinations of existing Bayes-optimal receivers with single-user codes are no longer optimal.

massive discrete MU-MIMOlow complexityinformation-theoretically optimaliterative receivermulti-user code

陈学辉、池育浩、刘雷

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西安电子科技大学,中国 西安 710071

浙江大学,中国 杭州 310058

大规模离散MU-MIMO 低复杂度 信息理论最优 迭代接收机 多用户码

国家自然科学基金重大项目国家自然科学基金重点项目国际自然科学基金青年项目国际自然科学基金青年项目中兴产学研项目国家重点研发计划陕西省重点研发计划

62394292621310166220142462301485IA202312130092021YFA10005002023-YBGY-218

2024

10.12142/ZTETJ.202401009

中兴通讯技术
中兴通讯股份有限公司,安徽科学技术情报研究所

中兴通讯技术

CSTPCD北大核心
影响因子：1.272
ISSN：1009-6868
年,卷(期)：2024.30(1)
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