基于OFDM的DFT加扰矢量码分多址接入技术

发布时间：2018-08-24 21:17

【摘要】：为解决基于多载波的多址系统在出现子载波深度衰落时系统性能下降的问题,根据矩阵置换原理,提出了一种DFT加扰矢量多载波码分多址接入系统(DFT-VMC-CDMA).该系统利用张量积(Kronecker积)的矩阵分解性,引入矢量正交频分复用(V-OFDM)技术对发射信号进行组合排列,通过对张量积的矩阵向量求解获得分集增益抑制单一子载波上的衰落,并基于r循环信道矩阵的分解特性,加入DFT扩展和加扰前缀,减小系统复杂度和峰平比.通过仿真验证可知,该系统性能与传统的多载波系统相比,在20 d B高信噪比条件下,比上行链路的多载波直接序列码分多址(MC-DS-CDMA)平均提升6 d B,比下行链路的多载波码分多址(MC-CDMA)平均提升0.5 d B,达到了理论上的多径信道分集增益界;此外,新系统还降低了峰平比,提升了频谱效率,如当载波数为64,块长为8,保护间隔为12时,峰平比降低了2 d B,频谱效率提升了10%.
[Abstract]:In order to solve the problem of the performance degradation of multicarrier based multiple access system (MMA) in the presence of deep subcarrier fading, a DFT scrambling vector multicarrier code division multiple access system (DFT-VMC-CDMA) is proposed according to the matrix permutation principle. Based on the matrix decomposition of the tensor product (Kronecker product), the vector orthogonal frequency division multiplexing (V-OFDM) technique is introduced to combine the transmitted signals. By solving the matrix vector of the tensor product, the diversity gain is obtained to suppress the fading on a single subcarrier. Based on the decomposition of the r-cyclic channel matrix, the DFT extension and scrambling prefix are added to reduce the complexity of the system and the peak-to-average ratio. The simulation results show that the performance of the system is higher than that of the traditional multicarrier system under the condition of high signal-to-noise ratio (SNR) of 20 dB. Compared with uplink multicarrier direct sequence code division multiple access (MC-DS-CDMA) and downlink multicarrier code division multiple access (MC-CDMA), the average increase is 6 dB and 0.5 dB respectively, which achieves the theoretical multipath channel diversity gain bound. In addition, the new system also reduces the peak-to-average ratio. When the carrier number is 64, the block length is 8, the protection interval is 12:00, the peak-to-average ratio is reduced by 2 dB, and the spectrum efficiency is increased by 10%.
【作者单位】：西南交通大学信息科学与技术学院;西南交通大学信息编码与传输省重点实验室;
【基金】：国家自然科学基金资助项目(61032002,60872014) 高校学科创新引智计划资助项目(111工程)(111-2-14) 瑞典科学与技术合作项目(2008DFA12160)
【分类号】：TN929.5

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