摘要
为降低广义频分复用(GFDM)系统的峰均功率比(PAPR)、实现复杂度,提出了基于T变换和选择性映射(SLM)的TSLM算法,该算法的设计思想是利用SLM算法增加GFDM时域备选信号的数量以降低其PAPR,利用T变换实现串联的沃尔什-哈达玛变换和离散傅里叶反变换以降低GFDM系统的复杂度。为进一步降低GFDM系统的PAPR,提出了将TSLM算法和转换向量(CV)相结合的TCSLM算法,利用CV向量进一步增加GFDM时域备选信号的数量。结果表明,在子载波数为64、子符号数为3、相位序列数为2时,与SLM算法相比,TSLM算法和TCSLM算法的实现复杂度分别降低约21.9%和60.9%;在互补累计分布函数(CCDF)为10^(−3)时,TSLM算法和TCSLM算法的PAPR分别降低约0.6 dB和1 dB;在误比特率为10^(−3)时TSLM算法和TCSLM算法的误码性能均改善约2 dB。
In order to reduce the peak-to-average power ratio(PAPR)and the implementation complexity of generalized frequency division multiplexing(GFDM)system,the TSLM algorithm based on T-transform and selective mapping(SLM)was proposed.The design idea of the TSLM algorithm was to use the SLM algorithm to increase the number of GFDM time-domain alternative signals to reduce the PAPR,and to use the T-transform to realize the joint operation of the Walsh-Hadamard transform and the inverse discrete Fourier transform to reduce the complexity of the system.To further reduce the PAPR of the GFDM system,the TCSLM algorithm combining the TSLM algorithm and the conversion vector(CV)was proposed,and the CV vector was used to increase the number of GFDM time-domain alternative signals.The results show that when the number of subcarriers is 64,the number of sub symbols is 3 and the number of phase sequences is 2,compared with the SLM algorithm,the implementation complexity of the TSLM and TCSLM algorithm decreases by about 21.9%and 60.9%,respectively.When the complementary cumulative distribution function(CCDF)is 10^(-3),the PAPR of the TSLM and TCSLM algorithm decreases by about 0.6 dB and 1 dB,respectively.The error performance of the TSLM and the TCSLM algorithm is improved by about 2 dB when the bit error rate is 10^(-3).
作者
蔡建辉
李光球
沈静洁
CAI Jianhui;LI Guangqiu;SHEN Jingjie(School of Communication Engineering,Hangzhou Dianzi University,Hangzhou 310018,China)
出处
《电信科学》
2021年第4期82-89,共8页
Telecommunications Science
基金
基金项目和3项省部级基金项目。
关键词
广义频分复用
峰均功率比
选择性映射
转换向量
误比特率
generalized frequency division multiplexing
peak to average power ratio
selective mapping
conversion vector
bit error rate