Abstract
Internet of things (IoT) and machine-to-machine (M2M) communication are characterized by short periods and bursts. Traditional orthogonal frequency division multiplexing (OFDM) has not meet the demand for such traffic, while IoT and M2M communication will play an important role in the next fifth generation (5G) communication, so it is particularly urgent to study the small packet and low-latency wireless transmission technologies that satisfy IoT and M2M communication. Universal filter multi-carrier (UFMC) is a new kind of filtered wireless transmission mechanism that meets this requirement, but it faces a higher peak-to-average power ratio (PAPR) than OFDM, which affects the energy efficiency of UFMC. Based on the PAPR performance evaluation of several multi-carrier transmission technologies, a universal filtered multi-carrier based on selective mapping (SLM-UFMC) system is proposed, and the relationship between the number of candidate sub-bands and the performance or between the number of carriers and the performance is carried out. The simulation results show that SLM-UFMC can effectively reduce the PAPR of UFMC system, and the PAPR performance is improved by 1.8 dB comparing with the traditional UFMC. It also further indicates that SLM-UFMC is more suitable for IoT and M2M communication in 5G communication.
Highlights
关 键 词:SLM; UFMC; OFDM; PAPR; SLM⁃UFMC 中图分类号:TN929.5 文献标志码:A 文章编号:1000⁃2758(2019)06⁃1257⁃07
在 SLM⁃UFMC 中,总数为 N 的子载波首先被划 分为 B 个子带,然后将每一个子带扩展为 U 个不同 的候选子带,这样,发送端共产生了 BU 个不相同的 候选子带,这些候选子带都包含了原始传送的数据 信息,经过 IFFT 和滤波处理后从这 BU 个候选子带 选出 B 个具有最小 PAPR 的子带进行叠加传输。 图 2 给出了基于选择映射的通用滤波多载波系统的系 统框图,对于 BU 个候选子带,每个候选子带都乘以 一组旋转因子 B(u) = [ bu,0, bu,1,..., bu,N/ B-1 ] T,这里 u = 1,2,...,U。 不同的旋转因子可能带来不相同的 系统性能,比如循环移位序列,哈达玛序列或黎曼序 列等。 旋转后的信号可以表示为
Internet of things ( IoT) and machine⁃to⁃machine ( M2M) communication are characterized by short pe⁃ riods and bursts
Summary
关 键 词:SLM; UFMC; OFDM; PAPR; SLM⁃UFMC 中图分类号:TN929.5 文献标志码:A 文章编号:1000⁃2758(2019)06⁃1257⁃07 够降低 UFMC 的 PAPR 多达 1.8 dB 在 CPAPR = 10-4, 并且随着候选子带的增加,SLM⁃UFMC 的性能也进 一步提高。 这也使得 SLM⁃UFMC 更加符合 5G 绿色 通信的需求,而且本文方法很容易和非正交多址技 术结合进一步提高系统的容量。 对于接收到的信号 y, 常规做法是对其进行零 填充操作,也就是在接收信号的后面补上一定数目 的零, 使接收信号的长度达到发送信号的 2 倍即 2N。 然后对这 2N 点接收信号进行快速傅里叶变 换,将时域的信号转化到频域信号 Y,可以通过线性 均衡的方 法 ( 比 如: 迫零均衡或最小均方误差均衡。 ) 从接收信号中恢复出发送信号 Yi( i = 1,2, ...,B) 。
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