共查询到20条相似文献,搜索用时 109 毫秒
1.
线性均衡和判决反馈均衡是单载波频域均衡技术中所采用的两种主要均衡算法.对它们的原理和结构进行了详细的分析和比较,并对其在无线局域网种SUI信道条件下不同调制方式对系统性能的影响进行了仿真研究.从仿真结果中可以看到通过选取合适的频域均衡算法能够有效地改善系统性能. 相似文献
2.
针对时变水声信道估计和均衡问题,该文提出基于叠加训练序列(ST)和低复杂度频域Turbo均衡(LTE)的时变水声信道估计和均衡(ST-LTE)算法.基于叠加训练序列方案,将训练序列和符号线性叠加,使得训练序列和符号信道信息一致;基于最小二乘算法,进行信道估计.基于频域训练序列干扰消除技术,在频域消除训练序列对符号的干扰;基于频域线性最小均方误差(LMMSE)均衡算法,通过先验、后验、外均值和方差的计算,实现低复杂度信道均衡(符号估计);基于Turbo均衡算法,软重构叠加训练序列和更新信道估计,进行均衡器和译码器的信息交换,利用编码冗余信息,大幅度提升信道均衡性能.进行仿真、水池静态通信试验(通信频率12 kHz,带宽6 kHz,采样频率96 kHz,符号传输速率4.8 ksym/s,训练序列和符号的功率比为0.25:1)和胶州湾运动通信试验(通信频率12 kHz,带宽6 kHz,采样频率96 kHz,符号传输速率3 ksym/s,训练序列和符号的功率比为0.25:1),仿真和试验结果验证了所提算法的有效性. 相似文献
3.
针对时变水声信道估计和均衡问题,该文提出基于叠加训练序列(ST)和低复杂度频域Turbo均衡(LTE)的时变水声信道估计和均衡(ST-LTE)算法。基于叠加训练序列方案,将训练序列和符号线性叠加,使得训练序列和符号信道信息一致;基于最小二乘算法,进行信道估计。基于频域训练序列干扰消除技术,在频域消除训练序列对符号的干扰;基于频域线性最小均方误差(LMMSE)均衡算法,通过先验、后验、外均值和方差的计算,实现低复杂度信道均衡(符号估计);基于Turbo均衡算法,软重构叠加训练序列和更新信道估计,进行均衡器和译码器的信息交换,利用编码冗余信息,大幅度提升信道均衡性能。进行仿真、水池静态通信试验(通信频率12 kHz,带宽6 kHz,采样频率96 kHz,符号传输速率4.8 ksym/s,训练序列和符号的功率比为0.25:1)和胶州湾运动通信试验(通信频率12 kHz,带宽6 kHz,采样频率96 kHz,符号传输速率3 ksym/s,训练序列和符号的功率比为0.25:1),仿真和试验结果验证了所提算法的有效性。 相似文献
4.
针对当前研究中的子载波干扰(ICI)消除算法不支持高速移动环境的缺点,提出一种基于线性时变模型的ICI迭代消除算法。使用相邻3个正交频分复用(OFDM)信号帧对信道进行近似处理,将时变的无线信道建模为基于每条信号径的线性时变信道,信道线性时变斜率可通过相邻的导频符号获得,这样就可以预先构造频域干扰矩阵,然后通过循环迭代的方法将接收符号中的干扰消除。仿真结果表明,本文提出的ICI迭代消除算法可有效消除高速移动信道中的ICI。在多普勒偏移小的条件下,此算法带来的性能提升更大。 相似文献
5.
6.
针对时变频率选择性衰落信道,研究了连续相位调制(CPM)信号的逐幸存检测算法。该算法在未知信道状态的条件下,利用训练序列对信道参数进行初始估计。在对CPM信号进行Viterbi解调过程中,采用PSP技术实现信道的无延时跟踪。基于频域均衡的CPM检测算法虽然可以有效抗多径干扰且计算复杂度较低,但不能对时变信道进行跟踪。仿真结果表明,在时变多径信道下,基于PSP均衡的CPM检测算法能有效地进行信道参数估计,比频域均衡算法具有更好的误码性能。 相似文献
7.
粒子滤波(Particle Filter, PF)是一种有效的参数估计方法。通过对单载波频域均衡(Single Carrier Frequency Domain Equalization, SC-FDE)系统数学模型和粒子滤波原理的分析,将时变信道建模成一阶AR过程,尝试把粒子滤波方法运用到单载波频域均衡系统基于UW的信道估计中去,并给出了算法详细步骤。然后,分别针对三种不同时变程度的信道进行了仿真,并在这三种信道下,分别与LS估计作了误码性能比较。结果表明,在时变条件下,基于粒子滤波的信道估计方法较之线性LS估计能获得良好的误码性能增益,且信道变化越缓慢,这种增益越明显。 相似文献
8.
小波建模在时变信道盲识别中的应用 总被引:1,自引:0,他引:1
当前的信道盲均衡与盲识别算法主要考虑的是线性时不变信道,而对于时变的信道,传统的自适应技术常忽略考虑相关的信道时变信息,从而不能很好地对信道进行均衡与识别,本文在考虑信道时变信息的同时,采用时变信道多分辨率分解小波模型对时变信道进行建模,并依此模型给出变信道的盲识别算法。 相似文献
9.
短波信道是一个典型的频率选择性衰落信道,需要在接收端采用均衡技术来补偿信道衰落的影响。针对短波信道的特性,介绍了能有效对抗多径干扰的MIMO单载波频域均衡的系统结构,并研究了传统的线性均衡。在此基础上提出了一种改进的频域均衡算法,对信号进行两次均衡,进一步消除了多径分量造成的干扰,并在中度短波信道下验证了改进算法的性能。Matlab仿真结果表明,提出的改进算法降低了误码率,提高了系统性能。 相似文献
10.
11.
12.
Amit Kumar Kohli Divneet Singh Kapoor 《Circuits, Systems, and Signal Processing》2016,35(10):3595-3618
This paper presents adaptive channel prediction techniques for wireless orthogonal frequency division multiplexing (OFDM) systems using cyclic prefix (CP). The CP not only combats intersymbol interference, but also precludes requirement of additional training symbols. The proposed adaptive algorithms exploit the channel state information contained in CP of received OFDM symbol, under the time-invariant and time-variant wireless multipath Rayleigh fading channels. For channel prediction, the convergence and tracking characteristics of conventional recursive least squares (RLS) algorithm, numeric variable forgetting factor RLS (NVFF-RLS) algorithm, Kalman filtering (KF) algorithm and reduced Kalman least mean squares (RK-LMS) algorithm are compared. The simulation results are presented to demonstrate that KF algorithm is the best available technique as compared to RK-LMS, RLS and NVFF-RLS algorithms by providing low mean square channel prediction error. But RK-LMS and NVFF-RLS algorithms exhibit lower computational complexity than KF algorithm. Under typical conditions, the tracking performance of RK-LMS is comparable to RLS algorithm. However, RK-LMS algorithm fails to perform well in convergence mode. For time-variant multipath fading channel prediction, the presented NVFF-RLS algorithm supersedes RLS algorithm in the channel tracking mode under moderately high fade rate conditions. However, under appropriate parameter setting in \(2\times 1\) space–time block-coded OFDM system, NVFF-RLS algorithm bestows enhanced channel tracking performance than RLS algorithm under static as well as dynamic environment, which leads to significant reduction in symbol error rate. 相似文献
13.
在平坦瑞利衰落信道下,异步V-BLAST系统中,现有检测算法随信噪比提高误码率性能改善缓慢。为此,该文提出一种基于预处理矩阵的迭代检测算法:在发射端,通过预处理矩阵将发射信号扩展到整个数据帧上,以获取空时分集度;在接收端,采用低复杂的迭代并行干扰消除方法,由于在迭代过程中干扰重建基于预处理矩阵,所以上次迭代的检测误差被扩展,降低了迭代过程中的误差传播。仿真验证了所提方法的有效性,在8发4收场景下,误码率为10-3时,与现有串行干扰消除方法相比,带来了约7 dB信噪比增益。 相似文献
14.
A new two-dimensional blind channel estimation scheme for coherent detection of orthogonal frequency-division multiplexing (OFDM) signals in a mobile environment is presented. The channel estimation is based on the a posteriori probability (APP) calculation algorithm. The time-variant channel transfer function is completely recovered without phase ambiguity with no need for any pilot or reference symbols, thus maximizing the spectral efficiency of the underlying OFDM system. The phase ambiguity problem is solved by using a 4-QAM (quadrature amplitude modulation) scheme with asymmetrical arrangement. The results clearly indicate that totally blind channel estimation is possible for virtually any realistic time-variant mobile channel. 相似文献
15.
16.
17.
18.
Nonlinear adaptive filtering techniques for system identification (based on the Volterra model) are widely used for the identification of nonlinearities in many applications. In this correspondence, the improved tracking capability of a numeric variable forgetting factor recursive least squares (NVFF-RLS) algorithm is presented for first-order and second-order time-varying Volterra systems under a nonstationary environment. The nonlinear system tracking problem is converted into a state estimation problem of the time-variant system. The time-varying Volterra kernels are governed by the first-order Gauss–Markov stochastic difference equation, upon which the state-space representation of this system is built. In comparison to the conventional fixed forgetting factor recursive least squares algorithm, the NVFF-RLS algorithm provides better channel estimation as well as channel tracking performance in terms of the minimum mean square error (MMSE) for first-order and second-order Volterra systems. The NVFF-RLS algorithm is adapted to the time-varying signals by using the updating prediction error criterion, which accounts for the nonstationarity of the signal. The demonstrated simulation results manifest that the proposed method has good adaptability in the time-varying environment, and it also reduces the computational complexity. 相似文献
19.
针对正交频分复用系统在时变信道中的均衡问题,提出了一种低复杂度的时变信道均衡算法。该算法首先运用一阶多项式基扩展模型对时变信道进行建模,利用频域信道矩阵能量主要集中在对角线附近的特点,将频域信道矩阵按梳状导频的位置沿对角线分块,然后运用高斯置信传播算法分别进行线性迫零均衡。算法避免了矩阵求逆运算,降低了计算复杂度,同时有效补偿了多普勒频移引起的载波间干扰,提高了系统性能。计算机仿真结果和算法复杂度分析表明,提出的分块迭代均衡算法有效降低了时变信道中系统的误码率,并且具有复杂度低,可分布式计算的特点,因此适用于专用集成电路等硬件实现。 相似文献