检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
机构地区:[1]江西理工大学信息工程学院,江西赣州341000
出 处:《电视技术》2017年第4期209-215,共7页Video Engineering
基 金:国家自然科学基金项目(61363076);江西省自然科学基金项目(2142BAB207020)
摘 要:针对传统LMMSE算法需要知道信道特性的问题,提出了一种加权系数平均法改进的小波域LMMSE信道估计算法。运用离散小波变换对LS初始估计和预滤波处理后的信号实行阈值量化去噪处理,然后结合时域信道能量分布的稀疏性特征,利用加权系数平均法求出各子载波的频域响应,从而克服了传统LMMSE算法需要预先知晓信道统计特性的缺陷。对算法的BER和MSE性能进行实验仿真,结果表明:文中所提改进算法的信道估计整体性能显然会更优于LS、SVDLMMSE以及加权平均改进后的LMMSE算法。另外,在信噪比较低且信道统计特性未可知的状况下,文中算法要优于传统的LMMSE算法,并能够较好地降低噪声的影响,有效提升信道估计的精确度。In view of the problem that the traditional LMMSE channel estimation algorithm is required to know the characteristics of the channel statistical. An improved LMMSE channel estimation algorithm based on weighted average method in wavelet domain is proposed. The DWT is used to quantify the threshold of the signal after LS channel estimation and pre-fiher in this algorithm. Then, together with the time-domain channel sparse characteristics of the energy distribution. And, the weighted coefficient aver- age method is used to get the frequency response of each subcarrier. Thus, the problem that the traditional LMMSE algorithm must be required to know the characteristics of the channel statistical is solved. Aim at the BER and the MSE performance of this algo- rithm, its performance is simulated. The simulation results show that : the performance of the improved algorithm is better than the traditional LS, SVD-LMMSE and the improved LMMSE algorithm by the weighted average method. Besides, under the condition of low SNR and unknown the channel statistical properties, this algorithm is better than the traditional LMMSE algorithm. It shows that this improved algorithm can preferably reduce the effect of noise, and improve the accuracy of channel estimation effectively.
关 键 词:正交频分复用 加权系数平均法 离散小波变换 均方误差 误码率
分 类 号:TN929.5[电子电信—通信与信息系统]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.31