现有MIMO中继通信系统中,基于张量分解的半盲信道估计不能有效地将信道先验信息引入估计过程中,为此提出一种基于变分贝叶斯推断的信道估计算法.该算法首先利用NP(Nested PARAFAC)张量模型,引入有效精度、噪声精度等隐性超参数,建立信...现有MIMO中继通信系统中,基于张量分解的半盲信道估计不能有效地将信道先验信息引入估计过程中,为此提出一种基于变分贝叶斯推断的信道估计算法.该算法首先利用NP(Nested PARAFAC)张量模型,引入有效精度、噪声精度等隐性超参数,建立信道估计概率图模型;由于所求信道参数后验概率分布较为复杂,传统最大似然和最大后验等点估计方法难以实现,算法采用变分贝叶斯推断,推导出信道矩阵、有效精度及噪声精度的递推公式,使具有因子分解形式的q分布逼近所求信道参数的后验分布;并分析了模型证据的下界、模型的初始化及算法复杂度等.该算法能利用信道先验信息以提高信道估计性能,有效精度和噪声精度等参数可自动调节,且计算复杂度与数据的维度呈线性关系.仿真结果表明:在平稳瑞利衰落信道条件下,与基于交替最小二乘(Alternating Least Square,ALS)的半盲估计算法相比,算法的计算复杂度较低,收敛速度较快;与带监督序列的双线性最小二乘(Bilinear Alternating Least Square,BALS)非盲估计算法,基于ALS及非线性最小二乘(Nolinear Least Square,NLS)的半盲估计算法相比,算法具有较高的估计精度.展开更多
Lifting scheme is a second-generation wavelet transform which is easier to understand than the first-generation wavelet transform. Fourier analysis is not necessary for the construction, and inverse transform can natu...Lifting scheme is a second-generation wavelet transform which is easier to understand than the first-generation wavelet transform. Fourier analysis is not necessary for the construction, and inverse transform can naturally be realized. Furthermore, it is faster than the first-generation wavelet transform. In terms of compression ratio and compression efficiency, SPIHT is the best algorithm based on EZW, but its theory is difficult to understand and come true. We carry out the SPIHT algorithm, and propose a reformed algorithm based on SPIHT, making the realization more easier. In the end, LSS algorithm composed of lifting scheme and SPIHT algorithm is presented, whose compression efficiency is the same as SPIHT, but running is 10% faster than SPIHT.展开更多
文摘针对经典的李氏指数法(Lyapunov Exponential Method)等混沌相变判别方法复杂度高的问题,提出了一种应用锁相环技术判别混沌相变的新方法。首先,理论推导了混沌系统的解析特性,分析了系统在不同相态下含有的频率成分;然后,构建了针对混沌系统的数字锁相环模型,研究锁相环下混沌态和大周期态呈现的频率特性;最后,提出了一种基于锁相环技术的混沌相变判别新方法。仿真实验显示,相比于李氏指数法,所提方法判别速度快一个数量级,检测差错率为0时,性能提高近2 d B。新方法应用锁相环技术,简便易行,判别速度快,为混沌相变判别的工程应用提供了新的手段。
文摘现有MIMO中继通信系统中,基于张量分解的半盲信道估计不能有效地将信道先验信息引入估计过程中,为此提出一种基于变分贝叶斯推断的信道估计算法.该算法首先利用NP(Nested PARAFAC)张量模型,引入有效精度、噪声精度等隐性超参数,建立信道估计概率图模型;由于所求信道参数后验概率分布较为复杂,传统最大似然和最大后验等点估计方法难以实现,算法采用变分贝叶斯推断,推导出信道矩阵、有效精度及噪声精度的递推公式,使具有因子分解形式的q分布逼近所求信道参数的后验分布;并分析了模型证据的下界、模型的初始化及算法复杂度等.该算法能利用信道先验信息以提高信道估计性能,有效精度和噪声精度等参数可自动调节,且计算复杂度与数据的维度呈线性关系.仿真结果表明:在平稳瑞利衰落信道条件下,与基于交替最小二乘(Alternating Least Square,ALS)的半盲估计算法相比,算法的计算复杂度较低,收敛速度较快;与带监督序列的双线性最小二乘(Bilinear Alternating Least Square,BALS)非盲估计算法,基于ALS及非线性最小二乘(Nolinear Least Square,NLS)的半盲估计算法相比,算法具有较高的估计精度.
文摘Lifting scheme is a second-generation wavelet transform which is easier to understand than the first-generation wavelet transform. Fourier analysis is not necessary for the construction, and inverse transform can naturally be realized. Furthermore, it is faster than the first-generation wavelet transform. In terms of compression ratio and compression efficiency, SPIHT is the best algorithm based on EZW, but its theory is difficult to understand and come true. We carry out the SPIHT algorithm, and propose a reformed algorithm based on SPIHT, making the realization more easier. In the end, LSS algorithm composed of lifting scheme and SPIHT algorithm is presented, whose compression efficiency is the same as SPIHT, but running is 10% faster than SPIHT.
