基于叠加训练序列快速信道辨识方法

信道状态信息(CSI)对于无线通信来说至关重要,而叠加训练序列的信道估计方法由于不占用额外的信号带宽和具有较高的估计精度而受到人们的注意.本文从算法的复杂度入手,分析了不同的训练序列对算法复杂度的影响,并且在训练序列为PN序列下,利用循环Toeplitz矩阵的特性,得到了信道估计的快速算法.仿真实验的结果表明,这种算法不需要矩阵求逆、计算量小,估计精度高,有很大的实际应用前景.     

基于叠加训练的非合作多用户/MIMO信道估计

提出一种基于叠加训练的单载波非合作多用户/MIMO系统的迭代信道估计与检测方案。首先利用变换域方法构造具有零周期互相关特性的训练序列,从而消除多天线间的相互干扰,实现基于一阶统计量的信道估计。然后采用联合符号检测的迭代信道估计方法,利用检测序列作为额外的“训练序列”来降低信息序列自身干扰。与现有的叠加训练信道估计方案比较,新方案中训练序列构造更加灵活,在低信噪比下信道估计均方误差和误码率性能更优,且复杂度更低,仿真结果表明了该方案的有效性。     

突发通信中基于叠加训练的信道估计方案

针对无线突发通信中频带利用率低、信道参数获取困难等问题,提出了一种应用于突发通信的叠加训练信道估计与检测方案。该方案将信息和训练叠加发送,通过预失真发送信息符号使得训练与信息在频域正交,收端采用一阶统计信道估计和最大似然符号检测,并设计了抗直流干扰的信道估计方案。仿真表明,新方案在消除训练序列的频带开销的情况下获得了较好的信道估计和符号检测性能,与采用时分复用训练的方案相比,其有效吞吐率更优。     

叠加训练序列OFDM系统的联合频偏与信道估计

频率偏移导致用于叠加训练序列系统中的一阶信道估计方法失效.文中提出一种利用叠加训练序列进行OFDM系统的联合频偏和信道估计的方案.在简单介绍所建立的OFDM系统后,文中利用训练序列的周期性推导出频偏特征向量,并根据阵列信号求子空间的原理,利用接收信号矩阵的奇异值分解求出上述向量所在的线性子空间,通过相关匹配求出频率偏移,最后获得时域信道参数.理论分析表明频偏估计范围反比于训练序列周期,因此算法具有估计范围大的优点,且适用于所有叠加周期训练序列系统.仿真分析表明了算法的有效性.     

On channel estimation using superimposed training and first-order statistics

Channel estimation for single-input multiple-output (SIMO) time-invariant channels is considered using only the first-order statistics of the data. A periodic (nonrandom) training sequence is added (superimposed) at a low power to the information sequence at the transmitter before modulation and transmission. Recently superimposed training has been used for channel estimation assuming no mean-value uncertainty at the receiver and using periodically inserted pilot symbols. We propose a different method that allows more general training sequences and explicitly exploits the underlying cyclostationary nature of the periodic training sequences. We also allow mean-value uncertainty at the receiver. Illustrative computer simulation examples are presented.     

On the performance of data-dependent superimposed training without Cyclic Prefix for SISO/MIMO systems

Compared with channel estimation method based on explicit training sequences,bandwidth is saved for those methods using superimposed training sequences,while it is wasted when Cyclic Prefix(CP) is added.In previous work of McLernon,the Mean Square Error(MSE) performance of Data-Dependent Superimposed Training(DDST) without CP for Single-Input Single-Output(SISO) system was analyzed under the assumption that the data-dependent sequence matrix was a circulant matrix and not interfered by others.In fact,for th...     

Joint estimation of the channel and I/Q imbalance for two-way relay networks

In modern day communication systems, the massive MIMO architecture plays a pivotal role in enhancing the spatial multiplexing gain, but vice versa the system energy efficiency is compromised. Consequently, resource allocation in-terms of antenna selection becomes inevitable to increase energy efficiency without having any obvious effect or compromising the system spectral efficiency. Optimal antenna selection can be performed using exhaustive search. However, for a massive MIMO architecture, exhaustive search is not a feasible option due to the exponential growth in computational complexity with an increase in the number of antennas. We have proposed a computationally efficient and optimum algorithm based on the probability distribution learning for transmit antenna selection. An estimation of the distribution algorithm is a learning algorithm which learns from the probability distribution of best possible solutions. The proposed solution is computationally efficient and can obtain an optimum solution for the real time antenna selection problem. Since precoding and beamforming are also considered essential techniques to combat path loss incurred due to high frequency communications, so after antenna selection, successive interference cancellation algorithm is adopted for precoding with selected antennas. Simulation results verify that the proposed joint antenna selection and precoding solution is computationally efficient and near optimal in terms of spectral efficiency with respect to exhaustive search scheme. Furthermore, the energy efficiency of the system is also optimized by the proposed algorithm, resulting in performance enhancement of massive MIMO systems.

     

Time‐varying channel estimation for MIMO/OFDM systems using superimposed training and basis expansion models

An approach of superimposed training (ST)‐aided time‐varying (TV) channel estimation for multiple‐input multiple‐output orthogonal frequency division multiplexing systems is presented. By modeling the TV channel with the truncated discrete basis expansion model, a two‐step approach is adopted to estimate the TV channel. In addition, the mean square error (MSE) of the proposed channel estimation is analyzed, and its closed‐form expression is derived, which is a function of the data‐to‐ST power ratio. Using the developed channel MSE, we case the problem of ST power‐allocation by minimizing the lower bound on the average channel capacity. To enhance the performance of channel estimation, a low‐complexity decision feedback mechanism is introduced to iteratively mitigate the unknown data interference. Numerical results verify the performances of the proposed approach. Copyright © 2012 John Wiley & Sons, Ltd.     

Joint estimation of carrier frequency offset, dc offset and I/Q imbalance for OFDM systems

Orthogonal frequency division multiplexing (OFDM) systems with direct-conversion receiver (DCR) are vulnerable to carrier frequency offset (CFO), dc offset (DCO) and in-phase/quadrature (I/Q) imbalance. In this paper, we propose blind estimator for joint estimation of CFO, DCO and I/Q imbalance in OFDM systems with DCR. Simulation results show that performance of proposed estimator approaches Cramér-Rao lower bound (CRLB) asymptotically, which demonstrates its effectiveness.     

Subcarrier allocation based compensation for carrier frequency offset and I/Q imbalances in OFDM systems

We propose a novel subcarrier allocation (SCA) based approach for compensating carrier frequency offset (CFO) and I/Q imbalances in direct-conversion OFDM receivers. From the matrix representation of OFDM signals with CFO and I/Q imbalances, maximum likelihood CFO estimation and the associated SCA are given. Then, an SCA-based algorithm is proposed for the I/Q imbalances compensation. Moreover, the proposed approach is extended to a blind compensation scheme for OFDM signals with asymmetric SCA.     

CDMA downlink interference suppression using I/Q projection

Interference suppression at the receiver can be used to improve performance and capacity in the downlink of direct-sequence code-division multiple-access systems. In this paper, an interference suppression technique is developed which uses partial knowledge of spreading sequences to cancel a group of interfering signals. Specifically, knowledge of a complex scrambling sequence is used to project the desired signal away from the interference in the in-phase/quadrature (I/Q) complex plane. A maximum likelihood receiver formulation is used, treating both the desired signal and interference as being conditionally noncircular. A zero-forcing equalization approach is used to preserve orthogonality between signals from the same base station. The development of the technique is based on the assumption that the group of signals corresponds to another base station that does not transmit the signal of interest. However, the technique is also applied to the path diversity scenario (dispersion, soft handoff, transmit delay diversity), in which the group of interfering signals includes a desired signal component. The approach, referred to as I/Q projection, provides significant gains when performance is interference limited.     

Channel estimation using implicit training

In this paper, a new method to perform channel estimation is presented. It is shown that accurate estimation can be obtained when a training sequence is actually arithmetically added to the information data as opposed to being placed in a separate empty time slot: hence, the word "implicit." A closed-form solution for the estimation variance is derived, as well as the Cramer-Rao lower bound. Conditions are derived for the training sequences that result in a channel estimation performance that is independent of the channel characteristics. In addition, estimation performance is shown to be independent of the modulation format. A procedure to synthesize optimal training sequences is presented, and the problem of synchronization is solved. The performance of the algorithm is then compared with other methods that use explicit training under GSM-like environmental conditions, and the new algorithm is shown to be competitive with these. Finally, comparisons are also carried out against blind methods over realistic bandlimited channels, and these show that the new method exhibits good performance.     

Joint parameter/state estimation

It is shown how the refined instrumental variable method of parameter/state estimation for single-input single-output (s.i.s.o.) systems proposed by Young1 can be extended to multi-input multi-output (m.i.m.o.) systems. As might be expected, the extension follows directly from the s.i.s.o. analysis, but involves some difficult and interesting matrix manipulations.     

OFDM零中频接收机I/Q不平衡的数字估计与补偿

由于零中频接收机的优点,其已经成为未来无线终端发展的方向.但它也有固有缺陷,即引入较大的射频损伤.首先分析了I/Q不平衡的系统模型,接着推导出其在OFDM系统中对接收机的影响.提出了一种硬件容易实现的简便时域估计和补偿I/Q不平衡的算法.最后通过仿真给出了该算法的性能,仿真表明在AWGN和频率选择性衰落信道下能够明显提高接收机的误码率性能.     

基于训练序列的MIMO信道估计

提出了一种基于隐训练序列的多输入多输出通信系统的信道估计方法,利用训练序列与信息序列的不相关特性,在没有带宽损失的情况下估计出信道参数。给出了信道估计算法,并对估计的均方误差性能进行了分析,讨论了隐训练序列的优化方案。与以往的隐训练序列估计方法比较,本算法不受接收端直流偏移的限制,且有更低的估计均方误差。计算机仿真结果表明了该估计方法的有效性。     

基于伪协方差矩阵的频率和角度联合估计算法

提出了一种计算简单并且具有很好统计性能的色噪声环境下频率和角度联合估计算法。假设噪声的时间相关长度小于信号的时间相关长度来消除噪声的影响，而后利用足够的时间相关来构成伪协方差矩阵，并对其进行奇异值分解获得信号频率，最后利用一一对应的一维搜索方法获得角度估计值。最后数值仿真结果证实了所提方法不仅由于阵列的扩展效应而使得角度估计性能的优越，而且在很小计算负担的条件下频率估计也给出较好的性能。     

Fast cell search using I/Q multiplexed code under hierarchical cellstructure

A novel I/Q multiplexed code assignment is proposed for asynchronous cell site operation under hierarchical cell structure, in which the I-channel code as a group code and the Q-channel code as a cell-specific code are assigned to a forward pilot channel. Simulation results show that cell search from macro to micro, or vice versa, can be accomplished in less than ~50 ms at 90% of the locations     

基于隐训练序列的信道估计与跟踪

提出了新的基于隐训练序列的频率选择性信道估计方法,利用训练序列与信息序列的不相关特性,在没有带宽损失的情况下估计出信道参数。文中对所提方法给予了证明,给出了信道估计算法,并提出了改进的自适应形式,可以用于跟踪时变信道。与以往的隐训练序列估计方法比较,文章中的算法具有更低的估计均方误差,不受接收端直流偏移的限制,且适用于时变信道。计算机仿真结果表明了该估计方法的有效性。     

Joint angle and delay estimation using shift-invariance techniques

In a multipath communication scenario, it is often relevant to estimate the directions and relative delays of each multipath ray. We derive a closed-form subspace-based method for the simultaneous estimation of these parameters from an estimated channel impulse response, using knowledge of the transmitted pulse shape function. The algorithm uses a two-dimensional (2-D) ESPRIT-like shift-invariance technique to separate and estimate the phase shifts due to delay and direction of incidence with automatic pairing of the two parameter sets. Improved resolution is obtained by enlarging the data matrix with shifted and conjugated copies of itself