OFDM中利用酉变换和结构最小二乘的角度和时延联合估计

发布时间：2018-04-15 21:17

本文选题：无线通信 + 正交频分复用　；参考：《应用科学学报》2017年06期

【摘要】：在正交频分复用系统中,低信噪比条件下基于子空间分解的角度和时延联合估计算法的估计精度受限,为此提出一种利用酉变换和结构最小二乘的联合估计算法.利用酉变换将接收数据转换至实数域,然后用二维结构最小二乘建立目标优化函数,计算含有角度和时延信息的两个实对角矩阵.将这两个实矩阵构成一个复矩阵后对该复矩阵进行特征值分解,通过特征值实部和虚部的对应关系实现角度和时延的配对.该算法的目标函数合理地考虑了误差项之间的耦合关系,更加精确地修正了存在误差的信号子空间矩阵,因此估计结果更接近最优解.实验结果表明,该算法的估计精度和估计成功率比传统子空间算法高.
[Abstract]:In orthogonal frequency division multiplexing (OFDM) systems, the estimation accuracy of the joint estimation algorithm based on subspace decomposition and time delay is limited under the condition of low SNR. Therefore, a joint estimation algorithm based on unitary transformation and structural least squares is proposed.The received data is transformed into real number domain by unitary transformation, and then the objective optimization function is established by using two-dimensional structure least squares, and two real diagonal matrices with angle and delay information are calculated.After the two real matrices are formed into a complex matrix, the eigenvalue decomposition of the complex matrix is carried out, and the angle and delay pairing is realized by the corresponding relation between the real part and the imaginary part of the eigenvalue.The objective function of the algorithm reasonably considers the coupling relationship between the error terms, and corrects the signal subspace matrix with errors more accurately, so the estimation results are closer to the optimal solution.Experimental results show that the estimation accuracy and success rate of the proposed algorithm are higher than that of the traditional subspace algorithm.
【作者单位】：解放军信息工程大学信息系统工程学院;
【基金】：国家自然科学基金(No.61201381) 中国博士后科学基金(No.2016M592989) 信息工程学院杰出青年基金(No.2016603201)资助
【分类号】：TN929.53

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