Blind equalization of time errors in a time-interleaved ADC system

To significantly increase the sampling rate of an analog-to-digital converter (ADC), a time-interleaved ADC system is a good option. The drawback of a time-interleaved ADC system is that the ADCs are not exactly identical due to errors in the manufacturing process. This means that time, gain, and offset mismatch errors are introduced in the ADC system. These errors cause distortion in the sampled signal. In this paper, we present a method for estimation and compensation of the time mismatch errors. The estimation method requires no knowledge about the input signal, except that it should be band limited to the foldover frequency /spl pi//T/sub s/ for the complete ADC system. This means that the errors can be estimated while the ADC is running. The method is also adaptive to slow changes in the time errors. The Cramer-Rao bound (CRB) for the time error estimates is also calculated and compared to Monte Carlo simulations. The estimation method has also been validated on measurements from a real time-interleaved ADC system with 16 ADCs.     

Blind equalization in antenna array CDMA systems

Multipath induced interchip-interference (ICI) alters waveforms of transmitted signals and presents a major obstacle to direct-sequence (DS) code-division-multiple-access (CDMA) communications. For systems with aperiodic pseudorandom (PN) spreading sequences, the primary way to counter fading is through employing RAKE receivers that enhance the signal-to-interference ratio (SIR) by combining multipath signals from the desired user. In this paper, we formulate a discrete-time model for antenna array CDMA systems and study the 2-D RAKE receiver problem by casting it into an optimum vector FIR equalizer design and estimation framework. A novel aspect of the present work is the full exploitation of the potential of 2-D RAKE receivers without requiring any detailed knowledge of the multipath channels     

Blind equalization and multiuser detection in dispersive CDMAchannels

The problem of blind demodulation of multiuser information symbols in a high-rate code-division multiple-access (CDMA) network in the presence of both multiple-access interference (MAI) and intersymbol interference (ISI) is considered. The dispersive CDMA channel is first cast into a multiple-input multiple-output (MIMO) signal model framework. By applying the theory of blind MIMO channel identification and equalization, it is then shown that under certain conditions the multiuser information symbols can be recovered without any prior knowledge of the channel or the users' signature waveforms (including the desired user's signature waveform), although the algorithmic complexity of such an approach is prohibitively high. However, in practice, the signature waveform of the user of interest is always available at the receiver. It is shown that by incorporating this knowledge, the impulse response of each user's dispersive channel can be identified using a subspace method. It is further shown that based on the identified signal subspace parameters and the channel response, two linear detectors that are capable of suppressing both MAI and ISI, i.e., a zero-forcing detector and a minimum-mean-square-error (MMSE) detector, can be constructed in closed form, at almost no extra computational cost. Data detection can then be furnished by applying these linear detectors (obtained blindly) to the received signal. The major contribution of this paper is the development of these subspace-based blind techniques for joint suppression of MAI and ISI in the dispersive CDMA channels     

Blind channel identification and equalization in OFDM-based multiantenna systems

Wireless systems employing multiple antennas at the transmitter and the receiver have been shown to have the potential of achieving extraordinary bit rates. Orthogonal frequency division multiplexing (OFDM) significantly reduces the receiver complexity in multiantenna broadband systems. We introduce an algorithm for blind channel identification and equalization in OFDM-based multiantenna systems. Our approach uses second-order cyclostationary statistics, employs antenna precoding, and yields unique channel estimates (up to a phase rotation for each transmit antenna). Furthermore, it requires only an upper bound on the channel order, it does not impose restrictions on channel zeros, and it exhibits low sensitivity to stationary noise. We present simulation results demonstrating the channel estimator and the corresponding multichannel equalizer performance.     

Electrical equalization for advanced optical communication systems

We investigate equalizers for electronic dispersion compensation (EDC) of dispersion limited optical fibre communication links in combination with different modulation formats. We show that the performance of conventional equalizers including feedforward equalizer (FFE) and decision feedback equalizer (DFE) are fundamentally limited by the nonlinearity of square-law detection of the photodiode in direct detection systems. Advanced modulation formats such as differential phase shift keying (DPSK) and optical duobinary further enhance this kind of nonlinearity and degrade further FFE/DFE performance. However, nonlinear FFE–DFE and maximum likelihood sequence estimation (MLSE) take into account the mitigation of nonlinear inter symbol interference (ISI) and hence can achieve much better performance. We show that in contrast to other modulation formats, optical single sideband modulation results in approximately linear distortions after detection and thus a simple linear FFE equalizer can achieve good compensation.     

Blind equalization/detection for OFDM signals overfrequency-selective channels

A novel equalization/detection algorithm for orthogonal frequency division multiplexing (OFDM) signals transmitted over frequency-selective channels is introduced and investigated. The algorithm stems from the recognition that the Fourier transform processing inherent in OFDM turns a single wideband frequency-selective channel into a set of correlated narrowband frequency-flat fading channels. This suggests that sequence detection techniques, such as those discussed by Vitetta et al. (see IEEE Trans. Commun., vol.43, p.2750-8, 1995, IEEE Trans. Commun., vol.43, pt.II, p.1256-9, 1995, and Proc. IEEE Commun. Theory Mini-Conf (Globecom '96), London, UK, p.153-7, 1996), for time-selective flat-fading channels, can be also profitably utilized for joint equalization and decoding of OFDM signals in the frequency domain. Simulation results show that the proposed detection strategy, implemented via a standard Viterbi algorithm, provides improved performance over differential detection, with a moderate increase in receiver complexity and without requiring the periodic transmission of training blocks     

数字通信系统中自适应均衡技术的研究

克服数字通信系统码间干扰的有效方法就是在接收端采用均衡技术。文中给出了均衡问题的数学描述，综述了实现均衡的方法，讨论了基于LMS和基于RLS的自适应均衡算法，并通过MATLAB仿真比较了两类算法的性能。     

Blind adaptive equalization of mismatch errors in a time-interleaved A/D converter system

To significantly increase the sampling rate of an A/D converter (ADC), a time-interleaved ADC system is a good option. The drawback of a time-interleaved ADC system is that the ADCs are not exactly identical due to errors in the manufacturing process. This means that time, gain, and offset mismatch errors are introduced in the ADC system. These errors cause distortion in the sampled signal. In this paper, we present a method for estimation and compensation of the mismatch errors. The estimation method requires no knowledge about the input signal except that it should be bandlimited to the Nyquist frequency for the complete ADC system. This means that the errors can be estimated while the ADC is running. The method is also adaptive to slow changes in the mismatch errors. The estimation method has been validated with simulations and measurements from a time-interleaved ADC system.     

Blind equalization of MIMO systems based on orthogonal Constant Modulus Algorithm

This paper investigates adaptive blind source separation and equalization for Multiple Input Multiple Output （MIMO） systems. To effectively recover input signals, remove Inter-Symbol Interference （ISI） and suppress Inter-User Interference （IUI）, the array input is first transformed into the signal subspace, then with the derived orthogonality between weight vectors of different input signals, a new orthogonal Constant Modulus Algorithm （CMA） is proposed. Computer simulation results illustrate the promising performance of the proposed method. Without channel identification, the proposed method can recover all the system inputs simultaneously and can be adaptive to channel changes without prior knowledge about signals.     

基于子空间的无线光通信副载波盲均衡算法研究

文中基于Gamma-Gamma光强起伏分布大气湍流信道模型,对无线光副载波相移键控调制系统进行了子空间盲均衡算法的研究。对比分析了经过大气湍流信道盲均衡前后的副载波调制信号星座图聚敛性,给出了均衡后不同光强起伏方差下的误码率曲线,当R2=0.1,信噪比为20 dB时,误码率从4.710-1降低到1.5610-3,均衡后误码率明显改善。同时采用两种典型实测天气数据(阴、中雨)模拟大气信道进行了子空间盲均衡实验,均衡后调制信号星座图聚敛性与相位可识别性明显优于均衡前。仿真结果表明,子空间盲均衡算法对大气湍流信道下的副载波调制信号有良好的均衡效果。     

Blind phase recovery for QAM communication systems

In this paper, a novel phase estimator that can be employed for both square and cross Quadrature Amplitude Modulation (QAM) based digital transmission is presented. It does not need gain control and requires only the knowledge of the type of the transmitted symbol constellation, i.e., square or cross. It is based on the evaluation of the fourth power of the received data and the measurement of the orientation of the concentration ellipses of the bivariate Gaussian distribution having the same second-order moments. The analytical evaluation of the estimation error as well as of the asymptotic variance is provided. Experimental results outline the good performance of the estimator described here, which is superior to that of well-known phase estimation methods. Finally, it is outlined how the eccentricity of the concentration ellipses can be used to devise a test for detecting the constellation type.     

Analysis of the multimodulus blind equalization algorithm in QAM communication systems

The constant modulus algorithm (CMA) for blind equalization requires a separate carrier-recovery system for phase recovery. This letter mathematically analyzes a modified CMA, called the multimodulus algorithm (MMA), which may perform joint blind equalization and carrier recovery without the need for a separate carrier-recovery system for quadrature amplitude modulation signal constellations. The analyses focus on five aspects of the MMA: 1) derivation of the general formulation of the MMA cost function; 2) stationary points of the MMA; 3) desired global minima of the MMA; 4) unstable equilibria (saddle points) of the MMA; and 5) analytic verification of a discrete-time first-order phase-locked loop hidden inside the MMA, which is absent from the conventional CMA. Analysis results indicate that the MMA alone may be able to remove intersymbol interference and simultaneously correct the phase error, because it implicitly incorporates a phase-tracking loop, which automatically recovers carrier phase.     

联合多脉冲检测的PSWF正交调制信号盲自适应均衡

卫星通信信道的复杂时变特性,使基于椭圆球面波函数(Prolate Spheroidal Wave Function,PSWF)的正交调制信号脉冲组的正交性受到破坏,已有均衡方法未能充分利用多脉冲干扰中的有用信息,效果有限。针对该问题,结合信道均衡与多脉冲检测各自的优势,提出一种联合多脉冲检测的PSWF时域正交调制信号自适应均衡方法,利用多脉冲检测消除脉冲间干扰的能力,降低均衡模块的阶数及算法难度;同时,利用均衡模块对信道的部分补偿作用,为多脉冲检测改善信道环境。在相同信道条件下,所提方法获得同等量级误比特率所需信噪比较自适应判决反馈均衡算法降低约2 dB。     

Blind equalization for broadband access

This article discusses the general principles of blind equalization and its use in emerging broadband access applications such as FTTC and xDSL. New results obtained for these applications are also presented     

Blind adaptive joint multiuser detection and equalization in dispersive differentially encoded CDMA channels

The problem of blind adaptive joint multiuser detection and equalization in direct-sequence code division multiple access (DS/CDMA) systems operating over fading dispersive channels is considered. A blind and code-aided detection algorithm is proposed, i.e., the procedure requires knowledge of neither the interfering users' parameters (spreading codes, timing offsets, and propagation channels), nor the timing and channel impulse response of the user of interest but only of its spreading code. The proposed structure is a two-stage one: the first stage is aimed at suppressing the multiuser interference, whereas the second-stage performs channel estimation and data detection. Special attention is paid to theoretical issues concerning the design of the interference blocking stage and, in particular, to the development of general conditions to prevent signal cancellation under vanishingly small noise. A statistical analysis of the proposed system is also presented, showing that it incurs a very limited loss with respect to the nonblind minimum mean square error detector, outperforms other previously known blind systems, and is near-far resistant. A major advantage of the new structure is that it admits an adaptive implementation with quadratic (in the processing gain) computational complexity. This adaptive algorithm, which couples a recursive-least-squares estimation of the blocking matrix and subspace tracking techniques, achieves effective steady-state performance.     

Blind per tone equalization of multilevel signals using support vector machines for OFDM in wireless communication

We present an efficient support vector machine (SVM)-based blind per tone equalization for OFDM systems. Blind per tone equalization using constant modulus algorithm (CMA) and multi-modulus algorithm (MMA) are used as the comparison benchmark. The SVM-based cost function utilizes a CMA-like error function and the solution is obtained by means of an iterative re-weighted least squares algorithm (IRWLS). Moreover, like CMA, the error function allows to extend the method to multilevel modulations. In terms of bit error rate (BER), simulation experiments show that the blind per tone equalization using SVM performs better than blind per tone equalization using CMA and MMA.     

Blind equalization in spatial multiplexing MIMO-OFDM systems based on vector CMA and decorrelation criteria

In this paper we address the problem of blind recovery of multiple OFDM data streams in a Multiple-Input Multiple-Output (MIMO) system. We propose an equalization algorithm which is based on a combined criterion designed to cancel both inter-symbol interference (ISI) and co-channel interference (CCI). ISI is minimized by using a modified Vector Constant Modulus criterion while CCI is minimized by a decorrelation criterion. We establish conditions for the existence of the stable minima corresponding to the zero forcing receiver which performs the joint blind equalization and the co-channel signal cancellation. The local convergence properties of the algorithm are proved under the assumption that the balance parameter weighting the two criteria is set appropriately. We also provide the optimal value for this parameter. Reliable performance is achieved with relatively fast convergence and small steady-state error. The implementation of the blind equalizer requires low-computational cost, without any matrix inversions or other expensive operations.     

移动通信中基于空时CM均衡的抗多径干扰技术

为补偿因空间角扩展和时延扩展同时存在而引起的多径干扰,将CM阵推广至二维结构,利用基于CMA恒模算法的空时联合信号处理技术对其进行均衡。基于包含信号到达方向（DOA）的信道模型,推导出了CMA空时联合恒模算法,并分析了其收敛特性。计算机仿真表明,该算法保持了CMA算法的盲均衡特性,算法简便。     

Blind FSR-LPTV equalization and interference rejection

We address the problem of synthesizing blind channel identification and equalization methods for digital communications systems, aimed at counteracting the presence of cochannel or adjacent-channel interference. Owing to the presence of the interfering signal, the minimum mean-square error equalizer turns out to be linear periodically time-varying, which is implemented by resorting to its Fourier series representation. Moreover, by exploiting the cyclic conjugate second-order statistics of the channel output, we propose a new weighted subspace-based channel identification method, which is asymptotically immune to the presence of high-level interference. Computer simulation results confirm the effectiveness of the proposed identification/equalization technique.     

Blind equalization using least-squares lattice prediction

Second-order statistics of the received signal can be used to equalize a communication channel without knowledge of the transmitted sequence. Blind zero-forcing (ZF) and minimum mean-square error (MMSE) equalization can be achieved with linear prediction error filtering. The equivalence with the equalizers derived by Giannakis and Halford (see ibid., vol.45, p.2277-92, 1997) is shown, and adaptive predictors that result in a lattice filtering structure are applied. The required channel coefficient vector is obtained with adaptive eigen-pair tracking. Either forward or backward prediction errors can be used. The performance of the blind equalizer is examined by simulations. The MMSE of the optimum FSE is approached, and the algorithm exhibits robustness to channels with common subchannel zeros