鲁棒的基于几何均值分解的矢量预编码算法

针对非理想信道的多输入多输出（MIMO）系统,提出了一种鲁棒的基于几何均值分解方法的矢量预编码算法.利用非理想信道误差矩阵的二阶统计信息,以最小化收发信号的均方误差为准则,求出基于几何均值分解矢量预编码的最优扰动矢量和预编码矩阵.仿真结果表明,该鲁棒算法优于现有的基于几何均值分解矢量预编码算法性能.在高信噪比时,误码率可提高2dB以上.     

Channel Capacity Estimation in TDMS-Based MIMO Measurements

Time-division multiplexed switching (TDMS)-based multiple-input multiple-output (MIMO) channel sounders are widely used for wireless channel measurements due to their effective costs. However, measurement noise such as phase noise in the local oscillators as well as additive white Gaussian noise (AWGN) can result in significant errors in channel capacity estimates. This study analyzes the impact of phase noise and AWGN on channel capacity in TDMS-based MIMO measurements, with a channel capacity estimator presented that reduces the impact of noise on both the spatial multiplexing gain and on the power gain. Simulations demonstrate that the estimator consistently obtains the true capacity for various MIMO channel scenarios, even if only a limited number of observations are available.     

MIMO系统中信道估计与序列联合检测

提出了MIMO系统中基于EM(Expectation Maximization)-SD(Sphere Decoding)相结合的信道估计和检测的联合处理算法。在采用EM-SD算法进行联合处理时,首先通过观测数据、训练序列及以前估计的符号对信道信息进行更新,随后把更新后的信道信息及观测数据重新送入SD算法中进行最小距离搜索,从而可以估计发送符号。仿真显示:这种联合估计及检测算法的性能属于次优算法,但是其复杂度会随着搜索而下降。在比较少的迭代次数下,可以获得理想的信道估计和检测结果。     

MIMO理论的改进方案研究

指出现有MIMO理论研究只是在所建立的基带数学模型基础上,依据空分复用(SDM)原理证明了MIMO可增加信道容量.但是它没有给出与该数学模型相适配的、合理的物理模型,导致所依据的SDM无法实现,使MIMO理论在数学层面所导出的信道容量公式在物理上是无法实现的.从天线的物理特性、各种天线阵的波束图、MIMO物理模型的不合...     

非完美CSI下大规模MIMO DF中继多用户对全双工通信系统性能研究

通过解码转发（DF）协议中继,研究了在非完美信道状态信息（CSI）下,多用户对双向全双工通信系统的性能.通过配备大量天线,可以大大增加通信系统的频谱效率（SE）.对到达中继端的信号采用迫零（ZF）线性接收处理并预编码,推导了SE的近似表达式,提出了与天线数量相关的功率缩放定律,讨论了在导频功率固定和变化条件下缩放因子的取值.所提的功率缩放定律可以在保持稳定的频谱效率的同时,将发射功率降低.研究了在非完美信道状态信息下,经过解码转发协议中继的多用户对双向全双工通信系统的性能.     

复数对偶格辅助预编码检测算法在多用户MIMO系统中应用

在LTE系统采用MIMO技术,使得系统容量提高,效率变快。为了消除多用户MIMO系统中一个用户来自其他用户之间的干扰,利用一种块对角化(BD)的预处理技术,将多用户信道分解为单用户信道,再结合对偶格基约减的方法代替原始的实数LLL算法来对信道矩阵进行处理。仿真结果表明,改进的算法在复杂度较低的情况下,可以获得更高的性能增益。     

多入多出非仿射系统的径向基网络逆控制方法

针对多入多出非仿射非线性系统, 提出了一种径向基网络补偿逆模型误差的自适应控制方法. 将难以求逆的非仿射项分解为可逆部分和不可逆部分, 可逆部分作为理想逆来近似系统的直接逆, 逆模型误差用径向基网络的自适应控制信号补偿, 网络权值利用不可逆部分非仿射信息更新, 应用均值理论和Lyapunov函数证明了自适应控制律的稳定性. 仿真结果验证了该方法的有效性.     

Improved MIMO-OFDM scheme for the next generation WLAN

The research and application of wireless local area networks (WLAN) technology are in a stage of rapid development. It has been one of research focuses of the wireless communications field. Through the use of enhanced single-user (SU)/multi-user (MU) multiple input multiple output (MIMO)-orthogonal frequency division multiplexing (OFDM) technology, the next generation WLAN IEEE 802.11ac dramatically increases the throughput. An improved MIMO-OFDM scheme based on modulation diversity is proposed for the next generation WLAN. It uses two-dimensional modulation diversity to the current IEEE 802.11ac transmission scheme. Through the space-time-frequency component interleaver and the rotational modulation, the proposed scheme exhibits high spectral efficiency and low error rate in fading channels. The simulation results show that the proposed scheme significantly outperforms the SU/MU MIMO-OFDM scheme in the current IEEE 802.11ac standard, which is up to 5 dB.     

Identifying Model Series of MIMO System via Grey Target Theory

This paper discusses the problem of identifying model series of multi-input multi-output system via grey target theory by taking, respectively, both having and not having reference systems into account, which may sever as general guidance to models identification in case of less data, small sample and uncertainty; and proposes the approach to determining the so-called revealed distinguishing field, which can increase the accuracy of models identification by decreasing possible field of distinguishing coefficient and improve the approach determining the distinguishing coefficient in classical grey relational theory.     

电加热锅炉系统神经网络PID解耦控制器

以多输入多输出系统电加热锅炉为被控对象 ,基于神经网络 PID控制 ,提出了一种可用于带有耦合时延的多输入多输出系统的比例、积分和微分参数自整定的多输入多输出神经网络 PID解耦控制器 ,可以实现多变量系统的解耦 ,定值跟踪控制 ,并使系统具有很好的动态及稳态性能.