CAJ | 학술논문

在异步条件下应用特征值分解算法估计变换域通信系统基函数时，分段得到的特征向量存在模糊现象，此时将造成系统接收性能的下降。为了解决此问题，提出了基函数周期序列的同步算法。详细分析估计基函数的特征值分解算法，推导接收数据的采样延时与其自协方差矩阵特征值的关系式，得到同步参数的最大似然估计方法，依据范数的等价性原理，进一步将最大似然估计中的最大特征值求解问题转化为F-范数的求解以降低算法复杂度。仿真结果表明：相比最大特征值算法，采用F-范数的估计算法性能一致，但计算时间明显减少，算法的估计精度与接收信噪比成正比。异步条件下当估计的基函数存在模糊时，系统接收性能在同步之后能得到较好的改善。
재이보조건하응용특정치분해산법고계변환역통신계통기함수시，분단득도적특정향량존재모호현상，차시장조성계통접수성능적하강。위료해결차문제，제출료기함수주기서렬적동보산법。상세분석고계기함수적특정치분해산법，추도접수수거적채양연시여기자협방차구진특정치적관계식，득도동보삼수적최대사연고계방법，의거범수적등개성원리，진일보장최대사연고계중적최대특정치구해문제전화위F-범수적구해이강저산법복잡도。방진결과표명：상비최대특정치산법，채용F-범수적고계산법성능일치，단계산시간명현감소，산법적고계정도여접수신조비성정비。이보조건하당고계적기함수존재모호시，계통접수성능재동보지후능득도교호적개선。
When the eigenvalue decomposition(EVD)algorithm is used to estimate the basic function for transform domain communication systems(TDCS)under the asynchronous condition,the eigenvector got by the algorithm is fuzzy,thus degrading the system performance.A synchronous method of basis function is proposed to solve this problem.Based on a detailed study of the EVD algorithm,the relational expres-sion of the data sampling delay and the eigenvalue of self-covariance matrix is deduced,and then a maxi-mum likelihood(ML)estimation algorithm of the synchronization parameter is obtained.According to the norm-equivalence theorem,the frobenius norm is introduced in the problem of finding the largest eigenval-ue in ML estimation algorithm,so the algorithm complexity is reduced.The simulation results show that the frobenius norm-based algorithm has the same performance as the largest eigenvalue-based algorithm but it only requires a less calculating time,and its estimation accuracy is in direct proportion to the signal-to-noise ratio(SNR).When the estimated basic function remains fuzzy under the asynchronous condition,the reception performance of the system can be improved by the use of basic function after synchronization.