Doubly-Selective Channel Estimation Using Data-Dependent Superimposed Training and Exponential Basis Models

Channel estimation for single-user frequency- selective time-varying channels is considered using superimposed training. The time-varying channel is assumed to be well- approximated by a complex exponential basis expansion model (CE-BEM). A periodic (non-random) training sequence is arithmetically added (superimposed) at low power to the information sequence at the transmitter before modulation and transmission. In existing first-order statistics-based channel estimators, the information sequence acts as interference resulting in a poor signal-to-noise ratio (SNR). In this paper a data-dependent superimposed training sequence is used to cancel out the effects of the unknown information sequence at the receiver on channel estimation. A performance analysis is presented. We also consider the issue of superimposed training power allocation. Several illustrative computer simulation examples are presented.     

叠加训练序列设计及其高效传输技术研究

采用训练序列与信息数据叠加的传输方案由于消除训练序列占用的频带开销而受到广泛关注。然而,如何高效的分离叠加信号是实现高效信道估计和可靠检测的基础。通过叠加周期训练序列,研究了基于数据依赖的叠加训练(DDST)方案的高效信道估计和检测方案。并结合信道编码技术,研究了编码条件下DDST方案与传统时分复用(TDM)方案的性能。仿真结果表明,在消除训练带宽开销的情况下,获得DDST方案与TDM的误码率基本保持一致。     

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。     

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。     

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...     

基于数据依赖的叠加训练序列信道估计

通过采用依赖于信息数据的叠加式周期训练序列发送机制,考虑到信道存在未知直流偏移的情况,提出了一种估计频率选择性信道的新算法。推导出信道估计的均方误差公式,获得了最优的训练序列所应满足的条件。理论分析和仿真结果表明,该算法大大提高了信道估计和信号检测的性能,从而验证了该算法的有效性和可靠性。     

Algorithms for coherent diversity combining of M-ary orthogonalsignals

This paper discusses the use of coherent demodulation for antenna array receivers employing direct sequence spread spectrum techniques and M-ary orthogonal modulation. Three different approaches are discussed. The first is a conventional receiver using training sequences and decision feedback for channel estimation. The other two techniques employ decisions from a simple noncoherent combining (O) receiver to circumvent the need for training sequences. The bit error ratio (BER) performance of coherent M-ary orthogonal modulation is derived. Some qualitative analysis is also presented for the algorithms, and simulation results are used to compare their performance in different scenarios     

Joint I/Q imbalances estimation using data-dependent superimposed training

In this paper, we address the joint estimation of the channel impulse response and frequency-dependent in-phase and quadrature-phase (I/Q) imbalances using data-dependent superimposed training (DDST). The analysis developed shows that it is possible to use the first-order statistics of the received process to achieve synchronization and identify the resulting widely linear system that encompasses the radio frequency impairments considered. Furthermore, it is also verified that for the joint estimation of the transmitter and the receiver I/Q imbalances, additional constraints than those required for strictly linear systems should be imposed on the training sequences employed. The results of numerical simulations show that DDST has comparable performance with methods reported in the literature.     

A Cyclodespreader Architecture for Detecting Multiple Downlink Aperiodic CDMA Signals

Although a code-division multiple-access (CDMA) system is spectrally efficient and has some immunity against intentional reception, its capacity and performance are generally limited by multiple access interference (MAI) caused by other users. For an aperiodic CDMA system, the spreading sequences span multiple symbol intervals, and the cross-correlations between these sequences, which are a measure of the MAI, are periodic over multiple symbols. In this paper, we present a receiver with a parallel architecture that converts an aperiodic CDMA sequence into a piecewise periodic sequence in each arm. We refer to this receiver as a cyclodespreader because the despreader exploits the cyclostationary property of an aperiodic signal. As a result, the transmitted data can be detected separately in each arm of the receiver using low-complexity conventional algorithms proposed for periodic CDMA systems. The goal of the receiver is to decode several signals received from different cochannel base stations. The performance of the system is evaluated using real aperiodic CDMA signals, and it is compared to that of a conventional matched filter (MF) receiver using the number of correctly decoded messages as the performance measure.     

EM-based joint data detection and channel estimation of DS-CDMA signals

We present two efficient iterative receiver structures of tractable complexity for joint multiuser detection and multichannel estimation (JDE) of direct-sequence code-division multiple-access signals. The schemes result from an application of the expectation-maximization (EM) and the space-alternating generalized expectation-maximization (SAGE) algorithms, respectively. The EM-JDE receiver updates the data bit sequences in parallel, while the SAGE-JDE receiver reestimates them successively. The channel parameters are updated in parallel in both schemes. The EM algorithm provides a set of free parameters, called weight coefficients, which can be selected to optimize its performance. Two optimality criteria are defined and analytical expressions for the corresponding optimized weight coefficients are given. Monte-Carlo simulations of a synchronous scenario show that the proposed JDE receivers have excellent multiuser efficiency and are robust against errors in the estimation of the channel parameters. Moreover, very short training sequences are required for the JDE schemes to converge. Simulation results further demonstrate that the SAGE-JDE receiver exhibits a better performance when the users' bit sequences are updated in the order of increasing signal strength, i.e., the bit sequence of the user with the weakest signal strength is updated first at each stage.     

基于DDST频域能量最大化的频偏估计方法

数据依赖叠加训练序列(Data-Dependent Superimposed Training,DDST)常用在正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)的信道估计中,由叠加训练序列和数据依赖序列组成,与信息序列并行发送,可以提高带宽利用率。提出了一种基于数据依赖叠加训练序列的OFDM载波频偏估计方法。叠加训练序列的周期性使其DFT能量间隔分布在特定的频点上,利用这个特性可进行频偏估计,只有得到正确的频偏估计时,这些特定频点的能量才得到最大值。仿真表明该方法在不降低传输速率的情况下,有着较好的频偏估计性能。     

Channel Estimation in OFDM Systems Using a Controlled Superimposition of Training Sequences

This work pertains to the use of superimposed training (ST) for channel estimation in orthogonal frequency division multiplexing (OFDM) based systems. A time domain coherent averaging based channel estimator is derived from the least squares criterion. By exploiting the periodicity of the training sequences in the time domain and inserting zeros instead of data at some of the training sequence subcarrier locations depending on the desired estimation accuracy, a controlled superimposition technique is proposed. This method includes the flexibility to trade off between bandwidth efficiency and performance. The mean squared estimation error (MSEE) performance of such a system is mathematically analyzed and a training sequence selection criterion optimizing the same is proposed. The simulation performance of the scheme is presented in terms of the MSEE and the bit error rate (BER) of the OFDM system. Such a scheme is attractive in high data rate scenarios in closed loop OFDM systems.     

Space-time signaling for high data rates in EDGE

Several space-time coding and processing techniques have been introduced in the literature for enhancing the capacity of wireless systems through antenna diversity or spatial multiplexing. We study the application of such techniques to an adaptive coded modulation system in multipath channels with intersymbol interference. One of the key requirements for application of these schemes is the use of appropriate training symbols for channel estimation at the receiver. We determine the training requirements for coherent receiver operation when multiple transmit antennas are used. We show that for the special case of the delay diversity scheme, transmitting the same training sequence from the two antennas is optimal. For more general schemes, we present training sequences that have good auto-correlation and cross-correlation properties that can be used in a practical system such as Enhanced Data for GSM Evolution (EDGE). We present detailed link level simulations that include channel estimation for the proposed schemes. We then determine the system throughput that is achieved for packet data with ideal link adaptation for deployment scenarios with 1/3, 3/9, 4/12, and 7/21 frequency reuse. We conclude that the gains from transmit diversity are not significant when there is frequency hopping as in an EDGE system and that a factor of 3 gain in throughput can be achieved when four transmit and four receive antennas are available using simple space-time transmission and receiver processing.     

基于部分数据的叠加序列慢时变信道估计

针对OFDMA通信系统,提出了一种基于部分数据的叠加序列慢时变信道估计算法,并在接收端给出了数据恢复的方法。时变信道采用复指数基扩展模型来描述,对OFDMA系统的导频序列进行了精心设计。提出在频域减去一个基于部分数据的序列,从而使发送数据经过反傅里叶变换后,特定位上的数据能量变低,进而大大减少了数据在信道估计时产生的误差。由于在发射端信号已经产生了畸变,在接收端采用特定的方法对数据进行补偿,消除了这种影响。实验仿真证明该方法在一定程度上提高信道估计的性能。     

Optimal insertion of pilot symbols for transmissions over time-varying flat fading channels

Two major training techniques for wireless channels are time-division multiplexed (TDM) training and superimposed training. For the TDM schemes with regular periodic placements (RPPs), the closed-form expression for the steady-state minimum mean square error (MMSE) of the channel estimate is obtained as a function of placement for Gauss-Markov flat fading channels. We then show that among all periodic placements, the single pilot RPP scheme (RPP-1) minimizes the maximum steady-state channel MMSE. For binary phase-shift keying (BPSK) and quadrature phase-shift keying (QPSK) signaling, we further show that the optimal placement that minimizes the maximum uncoded bit error rate (BER) is also RPP-1. We next compare the MMSE and BER performance under the superimposed training scheme with those under the optimal TDM scheme. It is shown that while the RPP-1 scheme performs better at high SNR and for slowly varying channels, the superimposed scheme outperforms RPP-1 in the other regimes. This demonstrates the potential for using superimposed training in relatively fast time-varying environments.     

Unification of MLSE receivers and extension to time-varyingchannels

Forney (1972) and Ungerboeck (1974) have each developed maximum-likelihood sequence estimation (MLSE) receivers for intersymbol interference (ISI) channels. The Forney receiver uses a whitened matched filter, followed by a sequence estimation algorithm using the Euclidean distance metric. The Ungerboeck receiver uses a matched filter, followed by a sequence estimation algorithm using a modified metric. A unified development of both receivers is given, in which each receiver is derived from the other. By deriving the Ungerboeck receiver from the Forney receiver, we show that the whitening operation is cancelled in the Euclidean distance metric, leaving the modified metric. In addition, the Ungerboeck receiver is extended to the case of a time-varying known channel. When the channel is unknown, decision-directed channel estimation is assumed, which requires channel prediction to account for the decision delay. It is shown that the Ungerboeck receiver requires additional channel prediction, degrading performance due to prediction uncertainty. To solve this problem, two alternative receiver forms are developed which do not require additional prediction, though the computational complexity is increased. Performance and complexity of the receiver forms are compared for the IS-136 digital cellular time-division multiple-access (TDMA) standard     

MUI-free receiver for a synchronous DS-CDMA system based on blockspreading in the presence of frequency-selective fading

We discuss a synchronous direct-sequence code division multiple-access (DS-CDMA) system based on block spreading in the presence of frequency-selective fading. Note that block spreading, which is also known as chip interleaving, refers to a spreading of a data block sequence, which is obtained by dividing a data symbol sequence into consecutive blocks. For such a system, we develop a simple new receiver that completely removes the multiuser interference (MUI) without using any channel information. The MUI-free operation is obtained by the use of a shift-orthogonal set of code sequences on which this receiver is based. Within the framework of the MUI-free receiver, we further present a subspace deterministic blind single-user channel estimation algorithm. As a benchmark for the MUI-free receiver and the corresponding subspace deterministic blind single-user channel estimation algorithm, we consider the linear multiuser equalizer and the corresponding subspace deterministic blind multiuser channel estimation algorithm developed by Liu and Xu (1996) for a standard synchronous DS-CDMA system in the presence of frequency-selective fading. We show that the complexity of the MUI-free receiver using the corresponding subspace deterministic blind single-user channel estimation algorithm is much smaller than the complexity of the linear multiuser equalizer using the corresponding subspace deterministic blind multiuser channel estimation algorithm. We further show that the performance of the MUI-free receiver is comparable with the performance of the linear multiuser equalizer. This is for the case in which the channels are known as well as for the case in which the channels are estimated with the corresponding subspace deterministic blind channel estimation algorithm     

一种基于DDST的频域能量最小化OFDM频偏估计方法

提出一种基于数据依赖叠加训练序列的OFDM载波频偏估计方法。叠加训练序列的周期性使其DFT能量间隔分布在特定的频点上,为了减小信息序列对叠加训练序列的影响,引入数据依赖序列使信息序列DFT在这些特定频点上为零,利用这个特性可进行频偏估计,只有得到正确的频偏估计时,这些旋转后的信息序列在这些特定频点的能量才得到最小值。仿真表明,该方法在不降低传输速率的情况下,有着较好的频偏估计性能。     

Data Aided Iterative Channel Estimation in OFDM Systems Using a Controlled Superimposition of Training Sequences

This work pertains to the use of superimposed training for channel estimation in orthogonal frequency division multiplexing (OFDM) based systems. An iterative time domain Least Squares based channel estimator is proposed. The estimator is generalized to provide scope for exploiting the coherence time and the coherence bandwidth of the channel. By exploiting the periodicity of the training sequences in the time domain and inserting zeros instead of data at some of the training sequence subcarrier locations depending on the desired estimation accuracy, a controlled superimposition technique is proposed. This method includes the flexibility to trade off between bandwidth efficiency and performance without any change in the structure of the channel estimator. The mean squared estimation error (MSEE) performance of such a system is mathematically analyzed and a training sequence selection criterion optimizing the same is proposed. The simulation performance of the scheme is presented in terms of the MSEE and also its impact on the bit error rate is shown. Such a scheme is attractive in high data rate scenarios in closed loop OFDM systems.     

MMSE interference suppression for timing acquisition anddemodulation in direct-sequence CDMA systems

It has been shown that minimum-mean-squared-error (MMSE) demodulators are effective means of interference suppression in code division multiple-access (CDMA) systems. The MMSE demodulator can be implemented adaptively using an initial training sequence, followed by decision-directed adaptation. This requires that the symbol-level timing of the desired user be known prior to training. We remove this requirement by providing a method for timing acquisition in which the output of the acquisition process is a near-far-resistant demodulator which automatically accounts for the delays and amplitudes of both the desired signal and the interference without explicitly estimating these parameters. The only requirements are a training sequence for the desired user and a finite uncertainty regarding the symbol timing. The latter condition can be realized by using a periodic training sequence even if the absolute timing uncertainty is arbitrarily large