摘要
本文研究了一个大规模单入多出上行链路系统,其中单天线节点需要将数据及时且可靠地传送给具有大规模天线阵列的基站。在该系统中,假设发送端与基站间的信道系数在连续两个符号周期内保持恒定,且每两个符号周期独立变化一次。针对该快速衰落信道模型,本文提出了一种针对大规模唯一可分解星座(Massive uniquely factorable constellation,MUFC)的映射方案,以解决系统瞬时信道状态信息获取与可靠性低的难题。具体地,本文首先基于黎曼测度准则对MUFC进行分割。然后,利用格状编码思想,给出MUFC星座的具体映射方案,理论仿真结果表明该映射方案能够增大调制输出信号序列间的最小黎曼距离(Riemannian distance,RD),从而提升接收端RD检测器的误差性能。最后,仿真结果进一步验证了所提方案的有效性。
This paper studies a massive single-input multiple-output uplink system,in which a single-antenna transmitter needs to transmit data to the receiver with a large-scale antenna array in a timely and reliable manner.In this system,the channel coefficients are assumed to remain constant during two consecutive symbol periods and change independently during the next two time symbol periods.For such a system model,we propose a mapping scheme for massive uniquely factorable constellation(MUFC),with an emphasis on avoiding the instantaneous channel state information acquisition as well as improving the system’s reliability.Specifically,we first perform constellation segmentation for the MUFC based on a Riemannian distance(RD)criterion.Then,using the trellis coding method,a specific mapping scheme for the MUFC constellation is provided.The theoretical simulation results show that the mapping scheme can increase the minimum RD between the modulated output signal sequences and improve the RD detector’s error performance at the receiving end.Finally,the simulation results verify the effectiveness of our proposed scheme.
作者
张美晨
李双志
陆晶晶
张建康
ZHANG Meichen;LI Shuangzhi;LU Jingjing;ZHANG Jiankang(School of Information Engineering,Zhengzhou University,Zhengzhou,Henan 450001,China;Guangdong Communications&Networks Institute,Guangzhou,Guangdong 510700,China)
出处
《信号处理》
CSCD
北大核心
2021年第3期374-382,共9页
Journal of Signal Processing
基金
国家自然科学基金项目(61901416,61571401)
中国博士后科学基金资助项目(2019M662529)
河南省科技攻关计划项目(192102210090,202102210138)
河南省博士后科研项目(201902010,1902012)
广东省重点领域研发计划(2018B010124001)。
关键词
大规模单输入多输出
非相干星座
星座映射
黎曼距离
massive single-input multiple-output
noncoherent constellation
constellation mapping
Riemannian distance
