Turbo channel estimation and equalisation for a superposition-based cooperative system

This study investigates the superposition-based cooperative transmission system. In this system, a key point is for the relay node to detect data transmitted from the source node. This issued was less considered in the existing literature as the channel is usually assumed to be flat fading and a priori known. In practice, however, the channel is not only a priori unknown but subject to frequency selective fading. Channel estimation is thus necessary. Of particular interest is the channel estimation at the relay node which imposes extra requirement for the system resources. The authors propose a novel turbo least-square channel estimator by exploring the superposition structure of the transmission data. The proposed channel estimator not only requires no pilot symbols but also has significantly better performance than the classic approach. The soft-in-soft-out minimum mean square error (MMSE) equaliser is also re-derived to match the superimposed data structure. Finally computer simulation results are shown to verify the proposed algorithm.     

Maximum a posteriori channel estimation for cooperative diversity orthogonal frequencydivision multiplexing systems in amplify-andforward mode

Transmit diversity-orthogonal frequency-division multiplexing (OFDM) systems have been proposed to mitigate the detrimental effects of channel fading. However, owing to the space and power limitations, the use of multiple transmit antennas is not practical in certain wireless devices, such as portable terminals and wireless sensors. Therefore cooperation among users at the physical layer has been proposed recently. Here, space-time block coded in amplify-and-forward (AF) relaying mode has been proposed as cooperative diversity for OFDM systems (CO-OFDM) in the presence of perfect channel-state information. Then, the channel estimation techniques for CO-OFDM systems in AF mode based on pilot symbols are investigated over frequency-selective channels. In particular, expectation-maximisation (EM) based maximum a posteriori (MAP) channel estimation is developed and compared with comp-type pilot-aided channel estimation (PACE) based the maximum likelihood (ML) estimator and the least minimum mean-square error (LMMSE) channel estimation techniques for CO-OFDM systems. To overcome the drawback owing to the receiver complexity, the Karhunen-Loeve expansion with the optimal truncation property is also considered. Simulation results that demonstrate the overall performance advantage of the EM-MAP based receiver over the PACE-ML and PACE-LMMSE based receivers are presented.     

Precoded orthogonal frequency division multiplexing with hidden pilots for ultrawideband wireless communications

The authors propose a new hidden pilot scheme equipped with precoding and its application to orthogonal frequency division multiplexing-ultra-wideband (OFDM-UWB) systems. The proposed scheme can be thought of as an improvement over conventional hidden pilot schemes. By carefully designing precoder and hidden pilot from the view point of frequency diversity, channel estimation and the peak-to-average power ratio (PAPR), more frequency diversity gain and reduced PAPR can be achieved. In addition, the authors can support more pilots to estimate a channel providing mitigated self-interference between data symbol and hidden pilot with almost no loss of bandwidth efficiency in OFDM-based UWB communication systems. The authors show improved performance of the proposed scheme over the multiband OFDM scheme through simulations in a realistic UWB channel environment.     

Blind channel estimation for multiple input multiple output uplink guard-band assisted code division multiple access systems with layered space frequency equalisation

Single carrier (SC) code division multiple access (CDMA) with block transmission has been shown to be more effective while utilising a low-complexity equaliser to combat frequency-selective fading channels, when compared with conventional direct sequence CDMA technology. It also has lower peak-to-average power ratio and lower frequency sensitivity compared with multicarrier CDMA. The authors propose two blind channel estimation methods for uplink multiple input multiple output SC-CDMA systems with block transmisssion-one is the subspace-based method and the other is the so-called autocorrelation contribution method (ACM). Both the methods provide close performance to the case with perfect channel knowledge at high signal-to- noise ratio (SNR) without any training data required. It is shown that ACM yields a better performance than the subspace method at a lower SNR, and a similar performance at a high SNR, with the advantages of avoiding rank determination and noise power estimation as in the subspace method. In addition, the authors integrate layered space frequency equalisation with blind channel estimation, which provides improved performance over the conventional linear equalisation, by employing successive interference cancellation.     

Decision-directed channel estimation based on iterative linear minimum mean square error for orthogonal frequency division multiplexing systems

A decision-directed (DD) channel estimation based on iterative linear minimum mean square error (LMMSE) is proposed for orthogonal frequency division multiplexing systems. Existing DD channel estimation is well known to have the problem of error propagation because of symbol-by-symbol detection. The proposed algorithm can estimate the correction term of current channel state information (CSI) according to the error vector of previous CSI by applying the orthogonality principle, and corrects the current CSI with this correction term. Analysis and simulation results have shown that this method has no error propagation problem. The performance of the proposed algorithm is much better than the conventional DD channel estimation, and close to the optimal LMMSE estimator, but with much less computational complexity compared with the optimal LMMSE estimator.     

Maximum likelihood signal-to-noise ratio estimation for coded linearly modulated signals

In this study, the authors propose an exact maximum likelihood (ML) signal-to-noise ratio (SNR) estimator for coded linearly modulated signals. The estimator is expressed in terms of the marginal a posteriori probabilities (APPs) of the coded symbols, which can be obtained efficiently by the Bahl-Cocke- Jelinek-Raviv (BCJR) algorithm for codes defined on trellises. Simulation results show that the proposed ML code-aided (CA) SNR estimator significantly outperforms the non-data-aided (NDA) estimators in the low SNR regime. The Cramer-Rao bound (CRB) for CA SNR estimator is also derived and evaluated numerically. It is shown that the proposed ML-CA estimator performs very close to the derived bound. Comparisons of the CRBs for CA and NDA scenarios with different linearly modulated signals further illustrate the intrinsic performance improvement by exploiting the channel coding constraints.     

High mobility orthogonal frequency division multiple access channel estimation using basis expansion model

Owing to the loss of subcarrier orthogonalities in high-speed applications, the use of conventional frequency-domain-based channel estimation in high mobility orthogonal frequency division multiple access (OFDMA) systems such as mobile WiMax may give rise to an unacceptable high channel estimation error floor. To alleviate this problem, the authors develop some basis expansion model (BEM)-based estimation schemes for the OFDMA uplink. Specifically, the authors express the time-varying channel as a superposition of a small number of complex exponential basis functions spanning the entire Doppler range, and then formulate least square (LS) and linear minimum mean square error (LMMSE) algorithms to estimate the basis coefficients for two different types of pilot patterns. The authors also derive the respective Cramer-Rao lower bounds for these estimators. It has been shown that the time domain BEM using a pilot scheme where pilots are placed over time axis will give better performance under a high Doppler scenario. Lastly, using simulation results, the proposed algorithms have been found to have better estimation accuracy over current frequency domain estimation techniques. This is in addition to the advantage that the proposed algorithms have in general a lower computational complexity.     

An informative subset-based estimator for censored quantile regression

Quantile regression in the presence of fixed censoring has been studied extensively in the literature. However, existing methods either suffer from computational instability or require complex procedures involving trimming and smoothing, which complicates the asymptotic theory of the resulting estimators. In this paper, we propose a simple estimator that is obtained by applying standard quantile regression to observations in an informative subset. The proposed method is computationally convenient and conceptually transparent. We demonstrate that the proposed estimator achieves the same asymptotical efficiency as the Powell??s estimator, as long as the conditional censoring probability can be estimated consistently at a nonparametric rate and the estimated function satisfies some smoothness conditions. A simulation study suggests that the proposed estimator has stable and competitive performance relative to more elaborate competitors.     

Tomlinson-Harashima precoding with imperfect channel state information

Nonlinear Tomlinson-Harashima precoding (THP) is an attractive solution for a scenario where the transmission system employs multiple antennas at transmitter and multiple users with a single antenna at the receiver, so that the cooperation among the receive antennas are impossible (downlink scenario). THP solution based on zero forcing (ZF) and minimum mean square error (MMSE) criteria is one of the important techniques to achieve near multiple input multiple output channels capacity with reasonable complexity. In this paper, the effect of channel imperfection on THP is considered. At first, the achievable rate of THP with respect to ZF criterion in an imperfect channel state information (CSI) scenario is calculated. Moreover, based on MMSE criterion, a new robust solution is derived which provides a significant improvement with respect to the conventional optimisation method. Then, the effect of channel estimation error on THP is considered as an improved optimisation where THP filters are optimised together with a channel estimator. Spatial power loading is found to be important to the THP performance. This loading for robust/joint optimisation of MMSE THP is developed by minimum average symbol error rate sense. Simulation results show the capacity loss, the performance advantage attained by the robust/joint optimisation and the power loading in an imperfect CSI scenario.     

Multi-user interference cancellation technology in the presence of multiple frequency offsets

The performance of multi-user detectors in the presence of multiple frequency offsets under a Rayleigh fading channel environment is analysed, and techniques to estimate and remove multiple frequency offsets (FOs) for successive interference cancellation (SIC) and parallel interference cancellation (PIC) receivers are also proposed. The closed form expressions derived for bit error rate (BER) of SIC and PIC schemes in the presence of multiple FOs have been verified using extensive simulation results. The PIC is shown to be less sensitive to frequency offsets as compared to SIC. It is demonstrated through analytical and simulation results that the proposed frequency offset estimation and correction techniques provide approximately 8 dB gain in the BER performance over conventional SIC and PIC schemes in the presence of multiple frequency offsets     

Joint maximum-likelihood frequency offset and channel estimation for multiple-input multiple-output?orthogonal frequencydivision multiplexing systems

The problem of joint maximum-likelihood estimation of the carrier-frequency offset (CFO) and channel coefficients in multiple-input multiple-output orthogonal frequency-division multiplexing systems is investigated, assuming that a training sequence is available. The exact solution to this problem turns out to be too complex for practical purposes. To overcome this difficulty, the authors resort to the expectation?maximisation (EM) algorithm and propose an iterative scheme which iterates between estimating the channel parameters and the frequency offset. This results in an estimation algorithm of a reasonable complexity which is suitable for practical applications. Moreover, the Cramer?Rao bounds (CRB) for both CFO and channel estimators are developed to evaluate the performance of the proposed scheme. Simulation results show that the proposed algorithm achieves almost ideal performance compared with the CRBs in all ranges of signal-to-noise ratio for both channel and frequency offset estimates.     

Wireless mesh networks channel reservation: modelling and delay analysis

In order to overcome the negotiation procedure bottleneck of the standard DCF in wireless mesh networks, the authors propose a new channel reservation function (CRF) that reduces the negotiation overhead of the DCF, which as a result reduces the overall transmission delay effectively without of any extra bandwidth consumption. Furthermore, the authors provide an analytical model for the proposed scheme for which the simulation results measure the amount that the new method can reduce the average total delay for both regular and fragmented mesh topologies demonstrating superiority of the new method over the classic 802.11 solution. Additionally, the authors extend the scheme to multichannel CRF upon which the proposed method can be used for multichannel applications.     

Channel estimation and interference cancellation in CP?CDMA systems

A novel iterative channel estimation approach is proposed for cyclic prefix-code division multiple access systems. Code-multiplexed pilots are used for channel estimation while maintaining bandwidth efficiency. The proposed method achieves a significant improvement when compared to the conventional correlation approach by reconstructing data signals for channel estimation. Simulation results demonstrate good estimation capability with an allocation of only 10% of the whole power to the pilot channel. In addition, an integrated channel estimator and parallel interference cancellation (PIC) detector are proposed. Data signals are reconstructed for channel estimation while the interference contributed by different data channels as well as the pilot channel are regenerated and subtracted from the received signal at the final stage. The channel estimation error reduces at each iteration and the PIC at the last stage enables further bit error rate performance improvement to be achieved for the system. The performance of the proposed scheme is studied through simulations and results verify its effectiveness     

Generalized Array Architecture with Multiple Sub-Arrays and Hole-Repair Algorithm for DOA Estimation

Arranging multiple identical sub-arrays in a special way can enhance degrees of freedom (DOFs) and obtain a hole-free difference co-array (DCA). In this paper, by adjusting the interval of adjacent sub-arrays, a kind of generalized array architecture with larger aperture is proposed. Although some holes may exist in the DCA of the proposed array, they are distributed uniformly. Utilizing the partial continuity of the DCA, an extended covariance matrix can be constructed. Singular value decomposition (SVD) is used to obtain an extended signal sub-space, by which the direction-of-arrival (DOA) estimation algorithm for quasi-stationary signals is given. In order to eliminating angle ambiguity caused by the holes of DCA, the estimation of signal parameters via rotational invariance techniques (ESPRIT) is used to construct a matrix that includes all angle information. Utilizing this matrix, a secondary extended signal sub-space can be obtained. This signal sub-space is corresponding to a hole-free DCA. Then, dealing with the further extended signal sub-space by multiple signal classification (MUSIC) algorithm, the unambiguous DOAs of all incident signals can be estimated. Some simulation results are shown to prove the improved performance of proposed generalized array architecture in DOA estimation and the effectiveness of corresponding hole-repair algorithm in eliminating angle ambiguity.     

Bootstrap variance estimation for Nadaraya quantile estimator

Under a suitable choice of bandwidth, Nadaraya’s estimator of the pth quantile yields smaller mean squared error than the unsmoothed pth sample quantile. We investigate the problem of bootstrap estimation of the variance of the Nadaraya quantile estimator and show that the error of the variance estimator can be reduced by smoothing the bootstrap. A novel approach, which calibrates the order p of the bootstrapped Nadaraya quantile estimates, is shown to reduce the error further. A simulation study is reported on the empirical performance of the proposed modified bootstrap variance estimators.     

Optimal training design for linearly time-varying MIMO/OFDM channels modelled by a complex exponential basis expansion

Time- and frequency-selective fading of propagating channels degrades the performance of multiple-input multiple-output/orthogonal frequency-division multiplexing (MIMO/OFDM) systems extensively by introducing double convolutions in both time-domain and frequency- domain. The author addresses the problem of linearly time-varying (LTV) channel estimation of MIMO/OFDM systems. First, the time-varying coefficients of the LTV channel are modelled by complex exponential basis expansions. Secondly, the LTV channel is estimated and the optimal pilot symbols are derived following the minimum mean square error criterion. It is shown that the optimal pilot strategy is to group consecutive pilot tones together as a pilot cluster and to distribute uniformly all pilot clusters in frequency-domain. In addition, the LTV channel estimation is further improved by imposing a window function on received signals. Finally, through simulations, it is shown that the new channel estimator can provide a considerable performance improvement in estimating MIMO-LTV channels, especially for the rapidly time-varying channel of a large Doppler frequency.     

Estimation of Weibull parameters with linear regression method

Abstract

Based on minimum mean square error, a modified probability estimator is proposed by a Monte Carlo simulation for estimating the Weibull parameters with the linear regression method. It is shown that compared with the commonly used estimators, the modified probability estimator gives a more accurate estimation of the Weibull modulus and the same estimation precision of the scale parameter. Furthermore, it is more conservative than the commonly used estimator recommended by previous authors and hence results in a higher safety in reliability predictions.     

基于多模型自适应技术的信道估计研究

提出了一种基于多模型自适应技术的信道估计方法.该方法通过设计动态信道模型库来覆盖未知信道的状态的改变,基于模型切换和动态规划(DP)进行模型变化检测及信道参数估计,从而在变化的信道环境中将有限个简单子集的估计算法有机地结合成一种在大信道范围内具有高度鲁棒性的信道估计器.仿真实验结果表明,此信道估计器比自适应信道估计器方法具有优势.     

Estimation of laser beam pointing parameters in the presence of atmospheric turbulence

The problem of estimating mechanical boresight and jitter performance of a laser pointing system in the presence of atmospheric turbulence is considered. A novel estimator based on maximizing an average probability density function (pdf) of the received signal is presented. The proposed estimator uses a Gaussian far-field mean irradiance profile, and the irradiance pdf is assumed to be lognormal. The estimates are obtained using a sequence of return signal values from the intended target. Alternatively, one can think of the estimates being made by a cooperative target using the received signal samples directly. The estimator does not require sample-to-sample atmospheric turbulence parameter information. The approach is evaluated using wave optics simulation for both weak and strong turbulence conditions. Our results show that very good boresight and jitter estimation performance can be obtained under the weak turbulence regime. We also propose a novel technique to include the effect of very low received intensity values that cannot be measured well by the receiving device. The proposed technique provides significant improvement over a conventional approach where such samples are simply ignored. Since our method is derived from the lognormal irradiance pdf, the performance under strong turbulence is degraded. However, the ideas can be extended with appropriate pdf models to obtain more accurate results under strong turbulence conditions.     

利用子空间的投影和跟踪改进OFDM信道估计

OFDM系统的LS信道估计可看作真实信道频率响应的一个有噪观察值，因此可采用子空间投影方法对噪声进行压缩。分析了利用子空间投影方法改进LSOFDM信道估计性能的实质，给出了利用子空间投影改进OFDM信道估计的一般框架，在此基础上将子空间投影推广到非LS信道估计方法。当信号子空间随时间变化时，需要采用子空间跟踪技术保持对信号子空间的良好估计，因此提出了一种基于子空间跟踪的参数化信道估计方法，仿真表明这种方法在性能上优于非参数化时的相应方法。