MIMO-OFDM系统抗干扰信道估计算法

提出一种抗干扰信道估计(AICE)算法用于解决MIMO-OFDM系统信道估计问题。该算法在接收端通过对收到的累加信号进行分解,得到来自不同发射天线的信号,通过消除符号间干扰与子载波间干扰及采用期望值最大迭代算法进行信道估计来减小估计误差,提高信道估计的准确性。与ICE算法的性能比较证明了AICE算法在瑞利衰落信道下具有更好的信道估计均方误差及误比特率性能。     

基于自适应调制技术的MIMO UWB无线通信系统的研究

在对多输入多输出(MIMO)技术和超宽带(UWB)无线通信研究的基础上提出了一种基于自适应调制技术的时变多进制MIMO UWB系统。通过采用奇异值分解理论和速率分阶的方法对系统性能进行了分析,推导出了速率离散分阶情况下的功率和速率的分配公式,提出了相邻时隙平均功率控制(JTAPC)算法,并且对系统的性能进行了仿真。研究结果表明,功率控制算法的使用很大程度上提高了采用速率分阶的系统的性能,并且降低了系统实现的复杂度。     

Interference suppressing for cellular MIMO system based on turbo receiver

Space-Time Coding （STC）, which combines channel coding, modulation, and multiple transmit antennas, is a powerful scheme to achieve higher data rates and combat fading in wireless systems, in this paper, we propose a soil/cancellation turbo equalization scheme to suppress Co-Channel Interference （CCI） in STC systems. The simulation results show that the proposed method significantly improves the system＇s ability of interference suppression, while preserving the space-time structure.     

A novel indoor geo-location method using MIMO array

In a Multiple-Input Multiple-Output （MIMO） Orthogonal Frequency Division Multiplexing （OFDM） based Wireless Local Area Network （WLAN） system, both Access Points （APs） and Mobile Terminals （MTs） are configured with multiple antennas, to make novel indoor geo-location method possible. In this paper, we presented a novel Least Square Support Vector Machine （LS-SVM） based data fusion algorithm to fuse signal strength measurements for indoor geo-location using only a single AP with MIMO arrays. We evaluate our proposed algorithms under indoor environments by MATLAB simulations. Simulation results show that our MIMO-based algorithm is superior to conventional least square algorithm.     

MIMO-OFDM系统中一种有效的信道估计方法

在多输入多输出正交频分复用(MIMO-OFDM)系统中,采用梳型训练符号的传统信道估计技术在子载波边缘会产生相当大的均方误差(MSEs)。为了减少这些子载波上的MSEs,提出了一种循环的梳型训练结构。在这种结构中,所有类型的训练符号都在每个天线上循环地发送。在接受端,用每个训练符号来估计信道频域响应,并采用与MSEs相对应的权重因子来平均这些响应。计算机仿真结果表明,这种循环的训练结构能够提供比传统的结构更高的信噪比(SNR)。     

时间选择性衰落信道下的空时多普勒编码

利用分层的代数方法,提出了一种新型的应用于时间选择性平坦衰落信道下的多输入多输出系统的空时多普勒码字,该码字能在符号速率达到Nt的情况下同时获得最大分集增益NtNrNb（Q+1）,也就是发送天线数Nt、接收天线数Nr、编码符号块的数目Nb以及信道复指数基的个数（Q+1）的乘积。仿真结果表明,与已有空时多普勒码字相比,所设计的码字可以获得更高的分集增益。     

Estimation of carrier frequency offsets for MIMO systems with distributed transmit antennas

The problem of estimating the carrier frequency offsets in Multiple-Input Multiple-Output (MIMO) systems with distributed transmit antennas is addressed. It is supposed that the transmit antennas are distributed while the receive antennas are still centralized, and the general case where both the time delays and the frequency offsets are possibly different for each transmit antenna is considered. The channel is supposed to be frequency flat, and the macroscopic fading is also taken into consideration. A carrier frequency offset estimator based on Maximum Likelihood (ML) is proposed, which can separately estimate the frequency offset for each transmit antenna and exploit the spatial diversity. The Cramer-Rao Bound (CRB) for synchronous MIMO (i.e., the time delays for each transmit antenna are all equal) is also derived. Simulation results are given to illustrate the per- formance of the estimator and compare it with the CRB. It is shown that the estimator can provide satisfactory frequency offset estimates and its performance is close to the CRB for the Signal-to-Noise Ratio (SNR) below 20dB.     

Incremental-based Nonlinear Detection Algorithm for MIMO System

A novel incremental nonlinear detection algorithm is presented for Multiple-Input Multiple-Output （MIMO） system. In this algorithm, the received data at multiple receiver antennas are nonlinearly mapped and then summed with weights. The weight coefficients are incrementally computed to avoid direct computation of the inverse of a matrix, which greatly reduce the computational complexity. Simulation and comparison show that the proposed algorithm can obtain better performance of Bit Error Rate （BER） than linear Minimum Mean Square Error （MMSE）.