针对长期演进(long time evolution,LTE)下行多输入多输出正交频分多址链路(multiple-input multiple-output orthogonal frequency division multiplexing,MIMO-OFDM)异步通信系统中的天线间干扰和多径干扰的问题,提出一种低复杂度的...针对长期演进(long time evolution,LTE)下行多输入多输出正交频分多址链路(multiple-input multiple-output orthogonal frequency division multiplexing,MIMO-OFDM)异步通信系统中的天线间干扰和多径干扰的问题,提出一种低复杂度的基于预编码矩阵的迭代均衡算法。在发射端,该算法通过预编码矩阵将信号扩展到所有子载波上,从而降低部分子载波深衰落对扩展前原始信号的影响。在接收端,利用最小均方差误差排序QR分解(minimum mean square error sorted QR decomposition,MMSE-SQRD)软输入软输出干扰消除均衡算法,一方面避免传统基于最小均方误差(minimum mean square error,MMSE)并行软干扰消除均衡算法中复杂的矩阵求逆运算,进而降低了算法复杂度,另一方面利用信道排列优先检测信噪比最大的传输符号提高检测准确性。同时通过预编码对重构信号中误差进行扩展,进而缓解在迭代干扰消除过程中的误差传播。仿真结果证明,在2发2收场景下,误码率在10-3时,算法经过5次迭代后系统性能相比于现有的迭代均衡算法改善约4dB。展开更多
针对LTE下行多输入多输出正交频分多址(MIMO-OFDM)系统中的天线间干扰和多径干扰问题,提出一种低复杂度的迭代均衡算法。该算法在接收端通过预编码矩阵将发射信号扩展到所有子载波上,从而减少部分子载波深衰落对扩展前原始发射信号的影...针对LTE下行多输入多输出正交频分多址(MIMO-OFDM)系统中的天线间干扰和多径干扰问题,提出一种低复杂度的迭代均衡算法。该算法在接收端通过预编码矩阵将发射信号扩展到所有子载波上,从而减少部分子载波深衰落对扩展前原始发射信号的影响。算法在接收端引入最小均方差误差排序QR分解(MMSE-SQRD)软干扰消除均衡算法,一方面避免传统基于最小均方误差(MMSE)并行软干扰消除均衡算法中矩阵求逆运算,进而降低了算法复杂度,另一方面利用信道排列,优先检测信噪比最大的传输符号进而提高检测准确性。同时通过预编码对重构信号进行预处理,进而缓解在迭代干扰消除过程中的误差传播。仿真结果表明:在4发4收场景下,误码率为10-5时,所提算法信噪比改善约0.7 d B。展开更多
VBLAST可以有效提高多发射天线系统容量,而STBC则具有较高的分集增益,通过将两种方案结合起来组成一个新的系统。根据已有的一种STBC-VBLAST模型,即通过在VBLAST的首层采用STBC编码,增加第一层信息符号的分集度,从而提高系统性能。由于...VBLAST可以有效提高多发射天线系统容量,而STBC则具有较高的分集增益,通过将两种方案结合起来组成一个新的系统。根据已有的一种STBC-VBLAST模型,即通过在VBLAST的首层采用STBC编码,增加第一层信息符号的分集度,从而提高系统性能。由于传统的VBLAST解码性能差,并且译码算法相对复杂,于是对原有的解码算法进行了改进,提出了一种SQRD(Sorted QR Decomposition)的解码算法。该算法比原有算法复杂性小很多,性能却相差不大,仿真结果也证实了这一点。展开更多
Aiming at the optimum path excluding characteristics and the full constellation searching characteristics of the K-best detection algorithm, an improved-performance K-best detection algorithm and several reduced-compl...Aiming at the optimum path excluding characteristics and the full constellation searching characteristics of the K-best detection algorithm, an improved-performance K-best detection algorithm and several reduced-complexity K-best detection algorithms are proposed. The improved-performance K-best detection algorithm deploys minimum mean square error （MMSE） filtering of a channel matrix before QR decomposition. This algorithm can decrease the probability of excluding the optimum path and achieve better performance. The reducedcomplexity K-best detection algorithms utilize a sphere decoding method to reduce searching constellation points. Simulation results show that the improved performance K-best detection algorithm obtains a 1 dB performance gain compared to the K- best detection algorithm based on sorted QR decomposition （SQRD）. Performance loss occurs when K = 4 in reduced complexity K-best detection algorithms. When K = 8, the reduced complexity K-best detection algorithms require less computational effort compared with traditional K-best detection algorithms and achieve the same performance.展开更多
文摘针对长期演进(long time evolution,LTE)下行多输入多输出正交频分多址链路(multiple-input multiple-output orthogonal frequency division multiplexing,MIMO-OFDM)异步通信系统中的天线间干扰和多径干扰的问题,提出一种低复杂度的基于预编码矩阵的迭代均衡算法。在发射端,该算法通过预编码矩阵将信号扩展到所有子载波上,从而降低部分子载波深衰落对扩展前原始信号的影响。在接收端,利用最小均方差误差排序QR分解(minimum mean square error sorted QR decomposition,MMSE-SQRD)软输入软输出干扰消除均衡算法,一方面避免传统基于最小均方误差(minimum mean square error,MMSE)并行软干扰消除均衡算法中复杂的矩阵求逆运算,进而降低了算法复杂度,另一方面利用信道排列优先检测信噪比最大的传输符号提高检测准确性。同时通过预编码对重构信号中误差进行扩展,进而缓解在迭代干扰消除过程中的误差传播。仿真结果证明,在2发2收场景下,误码率在10-3时,算法经过5次迭代后系统性能相比于现有的迭代均衡算法改善约4dB。
文摘针对LTE下行多输入多输出正交频分多址(MIMO-OFDM)系统中的天线间干扰和多径干扰问题,提出一种低复杂度的迭代均衡算法。该算法在接收端通过预编码矩阵将发射信号扩展到所有子载波上,从而减少部分子载波深衰落对扩展前原始发射信号的影响。算法在接收端引入最小均方差误差排序QR分解(MMSE-SQRD)软干扰消除均衡算法,一方面避免传统基于最小均方误差(MMSE)并行软干扰消除均衡算法中矩阵求逆运算,进而降低了算法复杂度,另一方面利用信道排列,优先检测信噪比最大的传输符号进而提高检测准确性。同时通过预编码对重构信号进行预处理,进而缓解在迭代干扰消除过程中的误差传播。仿真结果表明:在4发4收场景下,误码率为10-5时,所提算法信噪比改善约0.7 d B。
文摘VBLAST可以有效提高多发射天线系统容量,而STBC则具有较高的分集增益,通过将两种方案结合起来组成一个新的系统。根据已有的一种STBC-VBLAST模型,即通过在VBLAST的首层采用STBC编码,增加第一层信息符号的分集度,从而提高系统性能。由于传统的VBLAST解码性能差,并且译码算法相对复杂,于是对原有的解码算法进行了改进,提出了一种SQRD(Sorted QR Decomposition)的解码算法。该算法比原有算法复杂性小很多,性能却相差不大,仿真结果也证实了这一点。
基金The National High Technology Research and Develop-ment Program of China (863Program)(No.2006AA01Z264)the National Natural Science Foundation of China (No.60572072)
文摘Aiming at the optimum path excluding characteristics and the full constellation searching characteristics of the K-best detection algorithm, an improved-performance K-best detection algorithm and several reduced-complexity K-best detection algorithms are proposed. The improved-performance K-best detection algorithm deploys minimum mean square error （MMSE） filtering of a channel matrix before QR decomposition. This algorithm can decrease the probability of excluding the optimum path and achieve better performance. The reducedcomplexity K-best detection algorithms utilize a sphere decoding method to reduce searching constellation points. Simulation results show that the improved performance K-best detection algorithm obtains a 1 dB performance gain compared to the K- best detection algorithm based on sorted QR decomposition （SQRD）. Performance loss occurs when K = 4 in reduced complexity K-best detection algorithms. When K = 8, the reduced complexity K-best detection algorithms require less computational effort compared with traditional K-best detection algorithms and achieve the same performance.
