Semi-blind Adaptive Beamforming for High-throughput Quadrature Amplitude Modulation Systems

A semi-blind adaptive beamforming scheme is proposed for wireless systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, equal to the number of receiver antenna arrayts elements, are first utilised to provide a rough initial least squares estimate of the beamformer＇s weight vector. A concurrent constant modulus algorithm and soft decision-directed scheme is then applied to adapt the beamformer. This semi-blind adaptive beamforming scheme is capable of converging fast to the minimum mean-square-error beamforming solution, as demonstrated in our simulation study.

Semi-Blind Pilot-Aided Channel Estimation in Uplink Cloud Radio Access Networks

In this paper, a quasi-Newton method fbr semi-blind estimation is derived for channel estimation in uplink cloud radio access networks （C-RANs）. Different from traditional pilot-aided estimation, semiblind estimation utilizes the unknown data symbols in addition to the known pilot symbols to estimate the channel. An initial channel state information （CSI） obtained by least-squared （LS） estimation is needed in semi-blind estimation. BFGS （Brayben, Fletcher, Goldfarb and Shanno） algorithm, which employs data as well as pilot symbols, estimates the CSI though solving the problem provided by maximum-likelihood （ML） principle. In addition, mean-square-error （MSE） used to evaluate the estimation performance can be further minimized with an optimal pilot design. Simulation results show that the semi-blind estimation achieves a significant improvement in terms of MSE performance over the conventional LS estimation by utilizing data symbols instead of increasing the number of pilot symbols, which demonstrates the estimation accuracy and spectral efficiency are both improved by semiblind estimation for C-RANs.

Constant modulus semi-blind space-time equalizer based on structure risk minimum criterion

A new adaptive filtering principle based on capability control and semi-blind method is presented. A new semi-blind space-time equalizer based on constant modulus characteristic and structure risk minimum （SRM） criterion is also proposed. The equalizer sufficiently exploits the learning information of communication signals by using the structure information of filter itself through capability control technique. Namely, it maximizes the amount of learning information to im- prove filter tracking performance. Simulations are carried out and the result is compared with that of typical recursive least squares space-time equalizer （RLS-STE） and constant modulus semi-blind space-time equalizer （ CM-SB-STE ）. The results show that, even if with insufficient training data, the SRM constant modulus semi-blind space-time equalizer （SCM-SB-STE） keeps good tracking per- formance, showing promises in mobile wireless communications.

Semi-Blind Channel Estimation Algorithm for OFDM Systems

A semi-blind channel estimation algorithm based on subspace approach for orthogonal frequency division multiplexing（OFDM） systems over the frequency-selective channel is proposed. A linear preeoding is applied on each block before the IFFT operation and a low-rank structure is created in the received signal. Then subspace properties can be exploited to identify the channel up to a scalar ambiguity. The residual scalar ambiguities eliminated by inserting pilots into data stream. Simulation results illustrate the performance of the proposed semi-blind algorithm.

Adaptive Bit Loading Scheme with Semi-Blind Channel Estimation for OFDMSystems

An adaptive bit loading and power-allocation scheme is proposed in order to augment the performance of the system based on orthogonal frequency division multiplexing （OFDM）, which is based on the maximum power margin. Coinciding with the adaptive loading scheme, a semi-blind channel estimation algorithm using subspace decomposition method is proposed, which uses the information in the cyclic prefix. An initial channel state information is estimated by using the training sequences with the method of interpolation filtering. The proposed adaptive scheme is simulated on an OFDM wireless local area network（WLAN） system in a time-varying channel. The performance is compared to the constant loading scheme.

Semi-blind Channel Estimator for OFDM-STC

Channel state information of OFDM-STC system is required for maximum likelihood decoding.A subspace-based semi-blind method was proposed for estimating the channels of OFDM-STC systems.The channels are first estimated blindly up to an ambiguity parameter utilizing the nature structure of STC,irrespective of the underlying signal constellations.Furthermore,a method was proposed to resolve the ambiguity by using a few pilot symbols.The simulation results show the proposed semi-blind estimator can achieve higher spectral efficiency and provide improved estimation performance compared to the non-blind estimator.

A NOVEL SEMI-BLIND TIME-FREQUENCY DOMAIN TRACKING ALGORITHM SUITABLE FOR MPSK-OFDM

This paper presents a semi-blind tracking algorithm used for Multiple Phase Shift Keying based Orthogonal Frequency Division Multiplexing(MPSK-OFDM) system. By using special pream-bles to assist the decision of a feedback loop and to solve the problem of phase ambiguity,the tracking performance of the algorithm has been improved greatly. Only a few preambles are needed in the al-gorithm since the preambles are not used to estimate the frequency offset but used to provide the variation information of the phase due to the presence of frequency offset. Simulations verify that the algorithm has low SNR bound for tracking as well as high tracking accuracy and the tracking range is expanded to 30% of one subcarrier spacing.

Novel Semi-blind Channel Estimation Schemes for Rayleigh Flat Fading MIMO Channels

In this paper, we propose two novel semi-blind channel estimation techniques based on QR decomposition for Rayleigh flat fading Multiple Input Multiple output (MIMO) channel using various pilot symbols. In the first technique, the flat-fading MIMO channel matrix H can be decomposed as an upper triangular matrix R and a unitary rotation matrix Q as H = RQ. The matrix R is estimated blindly from only received data by using orthogonal matrix triangularization based house holder QR decomposition, while the optimum rotation matrix Q is estimated exclusively from pilot based Orthogonal Pilot Maximum Likelihood Estimator (OPML) algorithm. In the second technique, joint semi-blind channel and data estimation is performed using QR decomposition based Least Square (LS) algorithm. Simulations have taken under 4-PSK data modulation scheme for two transmitters and six receiver antennas using various training symbols. Finally, these two new techniques compare with Whitening Rotation (WR) based semi-blind channel estimation technique and results shows that those new techniques achieve very nearby performance with low complexity compare to Whitening rotation based technique. Also first technique with perfect R outperforms Whitening Rotation based technique.

AN INVESTIGATION ON SEMI-BLIND DECONVOLUTION BY USING NONLINEAR PROGRAMMING

The problem of using partial x(n) and (or) y(n) to solve thewhole x(n),y(n) from the convolved sequence z(n)=x(n)* y(n) is called Semi-blind Deconvolution (SBD) problem which is often encountered in many physical and engineering areas.

Optimization on semi-blind channel estimation for MIMO-OFDM systems

An orthogonal frequency division multiplexing （OFDM） is one of the effective techniques used in wireless communication. In OFDM systems, channel impairments due to multipath dispersive spreading can cause deep fades in wireless channels. Thus, the OFDM receiver requires channel state information when coherent detection is involved. Therefore, to overcome the impact of channel fades good channel estimation （CE） methods are needed in OFDM systems. And one of these CE methods is a semi-blind CE. However, the semi-blind method requires a large number of processing operations. In order to avoid the high computing complexity of the existing method, scaled least square （SLS） technique is applied to improve the performance of the semi-blind channel estimator which require less knowledge of the channel second-order statistics and have better performance than the least square （LS） which used in semi-blind CE. Simulation results shows, this proposed method of semi-blind CE has the capacity of elevating CE performance in multiple-input multiple-output （MIMO） OFDM systems.

Orthogonal procrustes based semi-blind MIMO channel estimation under space-time block code transmissions

This work investigates a novel semi-blind channel estimation for multiple-input multiple-output （MIMO） space-time block coding （STBC） systems. Algorithms for channel estimation based on whitening-rotation （WR） decomposition that provides a combined quality and spatial scalability is utilized. Using a space-time code-constrained input design, our approach exploits the orthogonality of the signal and noise subspaces in conjunction with orthogonal procrustes （OP） technique to obtain an accurate estimate of the unitary rotation matrix and, consequently, of the channel parameters. Unitary rotation matrices are parameterized a much fewer number of parameters, and significant estimation gains can then be achieved by estimation of such orthogonal matrices. Furthermore, the proposed semi-blind MIMO channel estimation approach is conducted to reduce the complexity of system design when the number of the receive antennas is no less than the number of transmit antennas. Computer simulations are conducted to corroborate the effectiveness of the proposed channel estimation, and they demonstrate the improved performance compared to the existing training-based estimation.

Recursive Least Squares Semi-blind Beamforming for MIMO Using Decision Directed Adaptation and Constant Modulus Criterion

A new semi-blind adaptive beamforming scheme is proposed for multi-input multi-output （MIMO） induced and spacedivision multiple-access based wireless systems that employ high order phase shift keying signaling. A minimum number of training symbols, very close to the number of receiver antenna elements, are used to provide a rough initial least squares estimate of the beamformer＇s weight vector. A novel cost function combining the constant modulus criterion with decision-directed adaptation is adopted to adapt the beamformer weight vector. This cost function can be approximated as a quadratic form with a closed-form solution, based on which we then derive the recursive least squares （RLS） semi-blind adaptive beamforming algorithm. This semi-blind adaptive beamforming scheme is capable of converging fast to the minimum mean-square-error beamforming solution, as demonstrated in our simulation study. Our proposed semi-blind RLS beamforming algorithm therefore provides an efficient detection scheme for the future generation of MIMO aided mobile communication systems.

Statistical assessment of selection-based dual-hop semi-blind amplify-and-forward cooperative networks

For multiple-relay cooperative networks with multiple antennas deployed at source and destination nodes,we investigate the outage performance of selection based semi-blind amplify-and-forward(AF) relaying,where transmit beamforming(TB) is conducted at source transmission and maximum ratio combining(MRC) at destination reception.Based on the Kolmogorov-Smirnov test,we analyze the impact of the configuration of destination antennas on the outage performance under arbitrary Nakagami-m fading channels.Results reveal that increasing the number of destination antennas is not necessary for an improvement of outage performance with any Nakagami-m parameter.Inspired by this fact,an approximation is proposed for the optimal selection.Simulation results show that the approximation is an efficient selection method.

适用于闭域或半闭域空间无线通信用泄漏电缆研究

以有线通信理论、无线通信理论及天线理论为核心理论体系,对适用于闭域或半闭域空间实现双工无隙通信用泄漏电缆的基本理论体系和可行性进行了定性和定量的分析与研究.给出了适用于甚高频和超高频带无线通信用泄漏电缆的基本原理和实现方案,详细地论述了泄漏电缆单模辐射方式的特点和实现手段.引入了泄漏电缆辐射方向、辐射损耗、传输损耗等主要特性参数的基础理论公式和数学模型,为闭域或半闭域空间实现双工无隙通信提供了一种行之有效的理论和实现方案.

基于H.264低比特率视频流的半脆弱盲水印算法实现

本文提出一种基于H·264低比特率视频流的半脆弱盲水印方法,通过在H·264特有的的帧内预测和运动向量预测中分别嵌入鲁棒水印和脆弱水印,达到版权保护和内容完整性认证的双重目的.通过在嵌入强度和预测模式选择的拉格朗日乘子中引入H·264量化因子,增强了水印对重量化编码的抵抗力,取得更好的率失真平衡,减小水印嵌入对视频流比特率的影响.该算法可以实现水印的快速嵌入提取,满足视频实时处理的要求,实验结果证明了该算法的有效性.

MIMO通信系统中QAM信号的快速半盲均衡算法研究

该文针对传输正交幅度调制(QAM)信号的多输入多输出(MIMO)系统的均衡问题,结合方环算法(SCA)的简单性和软决策(SDD)算法的精确性,提出了一种既比较精确又简单的算法(SCA+SDD)。在优化该算法的代价函数过程中,首先用很少的训练序列(等于接收天线数)得到均衡器权向量的一个粗略估计,然后提出利用共轭梯度法进行迭代优化该代价函数的方法,该算法具有近似的二次收敛性,与传统梯度类算法相比较,该方法有非常快的收敛速度和较少的计算量。最后通过误码率(BER)和收敛速度分析该算法的可靠性和有效性,并且通过计算机仿真证明了该算法的良好性能。

单用户无线信道盲均衡算法综述

无线信道盲均衡是近年来通信信号处理领域的研究热点。简要介绍了单用户无线信道盲均衡的数学描述,综述了基于Bussgang技术、高阶统计量、二阶矩、神经网络理论、信息理论盲源分离等几种典型算法,介绍了盲均衡的发展历程、研究现状,最后提出了发展半盲均衡算法及将信息熵理应用于盲均衡算法等有价值的研究方向。

频率选择性衰落OFDM的半盲信道估计算法研究

从系统性能分析和设计的角度详细地研究了基于无线HIPERLAN2通信协议的OFDM(orthogonal frequency division multiplexing,正交频分多路复用技术)系统信道估计与均衡的一种半盲算法,提出了结合直接法和Cholesky分解法的切换盲算法。这种半言算法综合了全盲算法得到的信息与已知导频符号,充分利用了原发信号的统计特性和OFDM帧结构中插入的导频符号,克服了全盲和导频训练序列存在的问题,且不需额外的带宽。仿真结果表明,在误比特率和收敛性方面,该算法比现有的主要三种全盲算法有更好的收敛和抗干扰特性。

针对OFDM系统的一种新的半盲信道估计方法

针对填补零的OFDM(ZP-OFDM)系统,提出了一种新的基于子空间的自适应半盲信道估计算法。该算法利用ZP-OFDM系统导频信息,给出精确的信道参数初始值。然后通过一种新的子空间跟踪以及功率方法,进行自适应信道估计。该算法不仅降低了计算复杂度,而且改善了盲信道估计收敛速度慢的缺点,仿真结果也表明其具有较好的估计精度。

CDMA中的半盲恒模算法

该文研究了应用于CDMA上行链路多用户检测中的半盲恒模算法。它首先利用非盲算法消除所有小区内干扰用户的影响,接着再利用盲算法抵消剩余的干扰。通过仿真实验,将之与盲恒模算法及解相关算法相比较,可以看出在于扰用户增多时,本文提出的半盲恒模算法的性能明显优于另外两种算法。