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

In this paper,a quasi-Newton method for semi-blind estimation is derived for channel estimation in uplink cloud radio access networks(C-RANs).Different from traditional pilot-aided estimation,semi-blind 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.

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.

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.

Low-complexity fractional phase estimation for totally blind channel estimation

To remove the scalar ambiguity in conventional blind channel estimation algorithms, totally blind channel estimation （TBCE） is proposed by using multiple constellations. To estimate the unknown scalar, its phase is decomposed into a fractional phase and an integer phase. However, the maximum-likelihood （ML） algorithm for the fractional phase does not have closed-form solutions and suffers from high computational complexity. By ex- ploring the structures of widely used constellations, this paper proposes a low-complexity fractional phase estimation algorithm which requires no exhaustive search. Analytical expressions of the asymptotic mean squared error （MSE） are also derived. The theo- retical analysis and simulation results indicate that the proposed fractional phase estimation algorithm exhibits almost the same performance as the ML algorithm but with significantly reduced computational burden.

CRAMER-RAO BOUND FOR BLIND CHANNEL ESTIMATION IN COMPLEX-VALUED CHANNEL

Compared with the traditional channel estimation methods, blind channel estimation methods can increase the bandwidth efficiency of the systems, but their precision is low and they converge slowly. In this paper, the Cramer-Rao Bound (CRB) for blind channel estimation in complex-valued Single-Input Multiple-Output (SIMO) channel is derived. In the simulations, the correctness of the CRB is validated and some channel estimation methods are evaluated by using the CRB.

Blind channel estimation for redundant precoded OFDM systems

Considering that channel estimation can play a crucial role in coherent detection of the information symbols in each data block, a blind channel estimation approach is proposed for redundant precoded orthogonal frequency-division multiplexing （OFDM） systems. A redundant linear frequency-domain precoder is applied to each pair of blocks before they enter the OFDM system. Because of the introduced structure, the frequency-selective channel can be identified at the receiver based on autocorrelation operations, singular value decomposition （SVD）, and by resolving the scalar ambiguity. The proposed channel estimation method has low computational complexity and requires no prior statistical information on channel or noise. And the proposed blind method has high spectral efficiency owing to exploiting no training sequence. Computer simulations confirm that this proposed blind channel estimation method can identify the frequency-selective channels perfectly and obtain a good performance.

Subspace-Based Blind Channel Estimation Method for MIMO-OFDM Systems

A subspace-based blind channel estination algo rithm for MIMO-OFDM systems is proposed. This algorithm exploits the cyclostationarity introduced by cyclic prefix of OFDM to estimate the channel parameters. The proposed new algorithm is found to be outperforming the other algorithm with respect to convergence rate and achievable mean square error and robustness to channel order over determination.

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 Blind Channel Estimation for a 2x2 MIMO System

A novel blind channel estimation method based on a simple coding scheme for a 2 by 2 multiple input multiple output (MIMO) system is described. The proposed algorithm is easy to implement in comparison with conventional blind estimation algorithms, as it is able to recover the channel matrix without performing singular value decomposition (SVD) or eigenvalue decomposition (EVD). The block coding scheme accompanying the proposed estimation approach requires only a block encoder at the transmitter without the need of using the decoder at the receiver. The proposed block coding scheme offers the full coding rate and reduces the noise power to half of its original value. It eliminates the phase ambiguity using only one additional pilot sequence.

BLIND CHANNEL ESTIMATION IN DELAY DIVERSITY FOR FREQUENCY SELECTIVE CHANNELS

Delay diversity is an effective transmit diversity technique to combat adverse effects of fading. Thus far, previous work in delay diversity assumed that perfect estimates of current channel fading conditions are available at the receiver and training symbols are required to estimate the channel from the transmitter to the receiver. However, increasing the number of the antennas increases the required training interval and reduces the available time with in whichdata may be transmitted. Learning the channel coefficients becomes increasingly difficult for the frequency selective channels. In this paper, with the subspace method and the delay character of delay diversity, a channel estimation method is proposed, which does not use training symbols. It addresses the transmit diversity for a frequency selective channel from a single carrier perspective in the form of a simple equivalent flat fading model. Monte Carlo simulations give the performance of channel estimation and the performance comparison of our channel-estimation-based detector with decision feedback equalization, which uses the perfect channel information.

BLIND CHANNEL ESTIMATION OF SPACE-TIME FREQUENCY-SHIFT KEYING

The decoupled coherent Maximum Likelihood (ML) detection algorithm presented in this letter can sharply reduce the complexity of the receiver as well as provide better error performance under the precondition that channel should be estimated first. Considering the bandwidth inefficiency of Frequency Shift Keying (FSK), the acquisition of channel state information through training sequences will further decrease the transmission efficiency. This letter presents a blind channel estimation algorithm based on noise subspace theory which can acquire channel information without any training symbols. The simulation shows that the algorithm brings about fewer channel estimation errors while the frequency efficiency can be increased.

ADAPTIVE BLIND ESTIMATION ALGORITHM FOR OFDM-MIMO RADIO SYSTEMS OVER MULTIPATH CHANNELS

This paper investigates the blind algorithm for channel estimation of Orthogonal Frequency Division Multiplexing-Multiple Input Multiple Output (OFDM-MIMO) wireless communication system using the subspace decomposition of the channel received complex baseband signals and proposes a new two-stage blind algorithm. Exploited the second-order cyclostationarity inherent in OFDM with cyclic prefix and the characteristics of the phased antenna, the practical HIPERLAN/2 standard based OFDM-MIMO simulator is established with the sufficient consideration of statistical correlations between the multiple antenna channels under wireless wideband multipath fading environment, and a new two-stage blind algorithm is formulated using rank reduced subspace channel matrix approximation and adaptive Constant Modulus (CM)criterion. Simulation results confirm the theoretical analysis and illustrate that the proposed algorithm is capable of tracking matrix channel variations with fast convergence rate and improving acceptable overall system performance over various common wireless and mobile communication links.

Equivalent Time-Domain Representation and Uplink Channel Estimator for Multicarrier CDMA Systems

Many blind channel estimation methods have been proposed for direct sequence (DS) code-division multiple access (CDMA) systems, so we can certainly use them to estimate the finite impulse response (FIR) channel for the multi-carrier (MC-) CDMA system. In this paper, the MC-CDMA system is interpreted as an equivalent time-domain DS-CD-MA system with specific spreading codes. Then, an equivalently time-domain blind channel estimator is derived for the uplink MC-CDMA, which is based on second-order statistics of the received data. By exploiting singular value decomposition (SVD) and the finite alphabet property of transmitted symbols, the time-domain channel impulse response (CIR) for the uplink MC-CDMA can be accurately identified. Computer simulations illustrate both the validity and the overall performance of the proposed estimator.

Joint Semi-Blind Channel Estimation and Data Sequence Detection of OFDM Systems

In this paper, a joint semi blind channel estimation and data sequence detection of OFDM systems over the multipath frequency selective fading channels is proposed and investigated. The basic idea of the algorithm is to first use the correlation among adjacent subchannels in the frequency domain to estimate the channel's parameters with an AutoRegressive (AR) process based on the decision directed estimation principle, and then to search the ML solution using the Viterbi algorithm. The algorithm realizes on line channel estimation and data detection of OFDM signals without any periodic pilot signal and statistic information about the channels, so it is suited to high data rate transmission over slow fading channels in the coming generation mobile communication systems.

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.

基于盲超分辨的超大规模MIMO-OFDM信道与感知参数联合估计

面向未来6G网络,ISAC与XL-MIMO技术有机结合、共同演进,有望进一步提升ISAC性能。然而,XL-MIMO-ISAC中部署大量天线会产生近场效应,为准确获取CSI和目标参数信息带来关键挑战。为此,采用线性修改的原子范数最小化方法,建模毫米波通信信道和感知阵列响应这两种盲源之间极坐标域的子空间一致关联,并提出了一种基于盲超分辨技术的CSI与感知参数并行估计方案,以避免从叠加信号中串行估计通信信道与目标参数信息造成误差传播。将联合盲源估计建模为非完全观测条件下的低秩矩阵重构问题,并引入PSWF将问题转化为SDP。仿真结果验证了提出的算法在CSI精度和目标参数分辨率方面的有效性。

基于FRFT与盲分离的扩频通信网络跳频信号时差估计

针对扩频通信网络跳频信号时差估计结果误差过高,导致信号定位追踪能力下降,多领域内信号传播停滞的问题,为增强扩频通信网络跳频信号的传播效率,提高辐射源跟踪和定位系统的信号探测能力,提出基于分数阶傅立叶变换(FRFT:Fractional Fourier Transform)与盲分离的扩频通信网络跳频信号时差估计算法的方法。采用盲分离方法获取满足跳频信号时差估计条件的两条信道,即平坦衰落信道和频率选择性衰落信道,利用FRFT估计两条信道特征,分别将平坦衰落信道特征和频率选择性衰落信道特征与最大似然块检测算法结合,实现扩频通信网络跳频信号的时差估计。实验结果表明,该方法无论是在正常环境中,还是在噪声干扰环境中,其均方根误差均处于较低水平、估计成功率均处于较高水平。