Improved Blind Multiuser Detection Algorithm Based on Minimum Output Energy

Based on minimum output energy,an improved blind multiuser detection algorithm is proposed by the use of Hopfield neural network.Compared with traditional algorithms,the proposed algorithm does not need the circuit for constraints.The resources are greatly saved and the complexity is reduced as well.The simulation results show that the performance of the improved algorithm is similar to that of the optimal multiuser detection algorithm which is not suitable for the mobile station.Compared with the traditional gradient blind multiuser detection algorithm,the convergence speed of the improved algorithm is quickened.

基于CMOE准则的盲自适应RLS检测器

针对直接递归最小二乘(RLS)算法存在的检测数值不稳定和收敛速度较慢等问题,将约束最小输出能量(CMOE)准则与直接RLS算法结合,提出一种基于CMOE准则的盲自适应RLS多用户检测算法。将该算法与直接RLS算法进行动、静态环境下输出信干比(SIR)、剩余输出能量(EOE)和误码率(BER)等方面的仿真,对比得出该算法具有更好的动态跟踪能力,更快的收敛速度和更高的稳定性。

MIMO MC-CDMA的简化CMOE递归自适应多用户检测

将约束最小输出能量(CMOE)准则应用于空时编码多输入多输出多载波码分多址(STBC MIMO MC-CDMA)系统,提出一种基于简化CMOE的联合信道估计与信号检测的递归自适应算法,解决了可变对角因子的自适应取值问题,所给出的最优步长半盲自适应信道估计可以提高信道估计的准确性和收敛速度.比较了不同环境下信道估计的误差和各种算法的误码率性能.

空时多用户检测器的级联结构

探讨了一种级联结构的空时多用户检测器。它可认为是改进的(或优化的)2D-RAKE接收机或改进的CMOE盲多用户检测器。其结构类似ST2D-RAKE接收机,但能充分利用所需用户的扩频码信息,用优化的方法生成解扩序列,从而大大改善了性能。