Impulse noise presents a severe performance bottleneck in multicarrier systems. For digital subscriber lines (DSL), the use of a common-mode (CM) sensor is a viable technique to mitigate the impulse noise that couples into the useful differential-mode (DM) signal. In this paper, we use time and frequency domain approaches to develop algorithms using the joint processing of CM and DM signals and analyze the performance of dual-sensor based interference cancellation schemes for downstream DSL systems. First, we consider the frequency domain approach and analyze the performance of a per-tone impulse noise canceler without requiring an impulse detector. We derive closed-form expressions on the performance of canceler in various interference scenarios in terms of system parameters. Next, we develop a novel per-symbol time-domain impulse noise canceler by simultaneous estimation of the CM2DM transfer function and the CM impulse noise using a limited number of null carriers. The proposed algorithm eliminates the issues of convergence of the per-tone canceler and stationarity of the impulse noise over multiple symbols. Using derived analytical expressions, we show that the proposed canceler effectively mitigates the impulse noise on a per-symbol basis. We also demonstrate the performance of the considered canceler schemes using measurement and simulation results.

We propose an iterative crosstalk cancellation scheme based on the generalized minimal residual (GMRES) algorithm for large-scale digital subscriber line (DSL) systems. The proposed scheme does not require channel inversion and stores fewer vectors for crosstalk cancellation. We analyze the convergence of the GMRES algorithm and derive computable bounds on the residual error and signal-to-noise ratio in terms of system parameters at each iteration for upstream DSL systems. We show that the GMRES algorithm typically requires a single iteration for very large vectored systems to achieve crosstalk-free performance for the very high-speed DSL (VDSL) frequencies and only a few more in the highest frequency bands of the G.fast spectrum. This yields significant complexity savings and reduction in memory storage, compared to the zero forcing scheme under certain conditions.

The adoption of precoding (vectoring) in VDSL2 at the central office has resulted in mitigation of the far-end crosstalk seen at the customer premises equipment (CPE). As a result, alien noise (including repetitive impulse noise) is the new dominant source of impairment for downstream VDSL. At the CPE, an additional common mode (CM) sensor can sense the electromagnetically coupled alien noise signal, which can then be used to cancel the alien noise coupling into the differential mode signal. The intermittent and repetitive nature of the noise sources necessitates that the CM sensor based noise cancellation algorithm be capable of training and adapting during data mode in the presence of the useful data signal, since the presence of alien noise cannot be guaranteed during the modem training phase. In this paper, we propose a novel two-stage frequency domain algorithm based on a per-tone cancellation model for this purpose. The proposed algorithm outperforms previously proposed time domain algorithms in terms of convergence speed in many practical scenarios due to the decision directed nature of the proposed algorithm. We also analyse the theoretical convergence of the algorithm, which is also validated by the simulation experiments.

For VDSL systems, alien noise cancellation using an additional common mode sensor at the customer premises equipment (CPE) receiver can be done by combining the differential-mode (DM) signal with the common-mode (CM) signal passed through a long linear filter. Frequency domain per-tone cancellation offers a low complexity approach to the problem but suffers from loss in cancellation performance due to approximations in the per-tone model. We analyze this loss and show that it is possible to minimize it by a post-training “delay” adjustment. We also address the problem of training such a noise canceller during data mode in the presence of a much stronger useful data signal in DM since noise events may not occur during modem train-up. We propose an algorithm based on the per-tone approach which is capable of fast convergence during data mode for intermittent alien noise sources, analyze its convergence behaviour and demonstrate the usefulness of the pertone approach and the proposed training algorithm over existing time domain methods.

Linear zero‐forcing (ZF) canceller does not perform well in the presence of alien crosstalk (AXT) while the receivers based on minimum‐mean‐square‐error (MMSE) criterion require perfect knowledge of the noise covariance matrices. In this study, the authors consider the use of a constrained linear minimum‐output energy (MOE) receiver in the presence of self‐crosstalk and AXT in upstream vectored very high‐speed digital subscriber line systems, that does not require knowledge of the noise correlation matrices and can be trained using the received signals without the use of training sequences. They derive bounds on the performance of the MOE receiver in the digital subscriber line environment and show that it reaches the MMSE performance for self‐crosstalk cancellation. They also show that the performance of the proposed receiver lies in between that of the ZF receiver and the non‐linear ZF generalised decision feedback equaliser receiver. An adaptation of the canceller coefficients using MOE algorithm shows comparable performance to that of the least mean squares algorithm. The effect of noise correlation on the capacity has also been highlighted via the Cramer‐Rao lower bound. Computer simulations are presented to verify the analytical results and demonstrate the performance of the proposed receiver.

Alien noise in the vectored very-high-speed digital subscriber line (VDSL) system is part of the additive noise at the receiver and exhibits strong correlation among users. We present a per-tone co-operative alien noise cancellation (CoMAC) algorithm for the upstream (US) VDSL that can be applied subsequent to any self far-end-crosstalk (FEXT) mitigation strategy. CoMAC operates by predicting the noise seen by a given user based on the error samples from the remaining users. These errors are conveniently obtained after slicing the self-FEXT canceled signal of all the vectored users. We show that if the estimation of these errors is accurate, the proposed alien canceler achieves the Cramer-Rao lower bound (CRLB). In practice, the seamless rate adaptation (SRA) operation, which enables increased bit rate by increasing the bit-loading per-tone, can cause decision errors in any decision directed strategy. We also analyze the impact of these decision errors - an issue not addressed in the literature. We propose a strategy for bit-loading during the SRA operation by formulating a max-min optimization problem and demonstrate a possibility of a guaranteed (minimum) improvement in the per-user rate. Simulations indicate that performance of the algorithm can exceed the minimum value significantly in practical situations.

We address the problem of blind multiuser detection in DS/CDMA systems that employ QPSK data modulation. We show that by suitable precoding (modification) of the phase of the QPSK data at the transmitter (before spectrum spreading), it is possible to detect the data of any user blindly using only the knowledge of the preceding sequence, regardless of the power of the interferes. The proposed method can be seen as an extension to our earlier preceding approach for BPSK signals in AKS Al Bayati et al. (2004). However, the phase preceding/decoding operation of QPSK signals is a more challenging problem, especially in its decoding procedure. The proposed detection scheme has a deterministic nature and is therefore shown to provide performance advantage in the medium-to-high SNR region.

A new approach for blind multiuser detection of binary phase-shift keying/direct-sequence code-division multiple-access signals is proposed, based on precoding the phase of the transmitted data uniquely for each user, over a block of data. This would enable separation and detection of a desired user's signal in an unknown multipath channel without channel estimation. The method does not involve any sacrifice in data rate or system bandwidth. The proposed method exhibits good performance, compared with some existing methods.

We propose a blind multiuser detector based on a new data precoding technique for direct-sequence code-division multiple-access signals. The modulus of all users' data is block encoded, using a sequence that is unique for each user. This precoding method, together with the analytical constant modulus algorithm for detection, enables a closed-form, one-shot detection of the desired user's signal in a multipath channel using one or more antennas. The detection process does not involve or require a channel estimation step. The proposed detector is shown to be extremely near-far resistant, and can operate properly in the presence of severe carrier frequency offset.

Constrained minimum variance (CMV) detection has been proposed for blind multiuser detection of DS/CDMA signals in multipath channels. We suggest a new approach for implementing the CMV detection when an antenna array is used at the receiver. A simple technique is used for restricting the domain of the CMV detector to a smaller subspace based on signals directions of arrivals (DOAs), in a beamformer-like formulation. The proposed technique requires prior knowledge of only the timing of the desired user's signal. It is seen that the proposed subspace restriction is useful for accurate path DOA estimation followed by efficient data detection in heavily loaded systems and over small block sizes of the input signal. This makes this method suitable for slowly time varying channels.

An attempt is made to develop algorithms for the adaptive autoregressive moving average (ARMA) modeling of a linear, slowly time-varying, multichannel system using scalar computations only. The multivariate ARMA process is mapped to an equivalent scalar, periodic ARMA process. By properly defining the input and output vectors corresponding to the scalar process, the problem is formulated as the order-recursive computation of the orthogonal projection of the input vector on an appropriate data subspace. This is carried out by first orthogonalizing the data vectors through the Gram-Schmidt procedure resulting in the least squares circular lattice (LSCL) algorithm. The LSCL algorithm evaluated all possible lower-order ARMA lattice filters. It consists of several identical sections, one for each channel, pipelined in a circular manner, and is therefore well suited for implementation in modular architecture.>

The authors propose a technique to compute signal bearings for the situation when the desired signal is corrupted by additive noise with unknown covariance. The noise covariance matrix is assumed to be a banded symmetric Toeplitz matrix. This algorithm eliminates the need for the evaluation of eigenvalues and eigenvectors. The algorithm is also computationally very efficient, since it requires the use of a simpler orthogonal decomposition, i.e. only the Householder decomposition. The number of computations required to perform this decomposition is of the order of O(2N/sup 3//3), while the eigendecomposition requires O(N/sup 4/) computations.>

The present paper aims to present an entirely new approach for the development of "exact" recursive least squares algorithms for ARMA filtering and modeling when the inputs (asssumed here to be "white") are not observable. The approach is heavily based on the recently proposed "predictor-space" representation of ARMA processes 131 and theu se of some new, moreg eneral projection operator update formulas, breifly summarized here.

In recent years a new, and very powerful technique for parameter estimation - the eigenstructure, or signal subspace method - has been developed. Eigenstructure algorithms are closely related to Pisarenko's method for estimating the frequencies of sinusoids in white Gaussian noise. In theory they yield asymptotically unbiased estimates of arbitrarily close parameters, independent of the signal-to-noise ratio (SNR). Although signal subspace methods have proven to be powerful tools, they are not without drawbacks. An important weakness of all signal subspace algorithmis their need to know the noise covariance explicitly. The important problem of developing signal subspace based procedures for signals in noise fields with unknown covariance has not been satisfactorily addressed. It is our intent to propose a solution to the problem of direction-of-arrival (DOA) estimation for a broad class of unknown noise fields. We will then briefly discuss other important estimation problems for which modified versions of this procedure can be applied.

Through both theoretical developement and simulation the method we have put forward has been shown to yield improved performance over the conventional spatial smoothing algorithm. Our discussion has demonstrated that for a given array length the proposed method can be used to increase the number of coherent signals that can be resolved and thus effectively increase array aperture. Our simulation results underscore this fact. As we will see this increase in aperture is obtained, to some extent, at the expense of robustness.

A state space modeling approach to equalization, which is applicable to both finite, as well as infinite impulse response channels, is presented. The order of the state space model is typically much Smaller than the length of the impulse response. It is shown by analysis and simulation that the proposed approach has considerably less digit mean square-error as compared to the conventional Kalman filter equalizers for much smaller model orders and, hence, computational efforts.

Digital design complexity and the advent of VLSI has increased the need for design automation techniques. This paper discusses the mapping of the data part specified at a behavioural level onto a canonical structure, Data Node Array (DNA). The DNA is a parameterized, regular structure which is capable of realizing an arbitrary, complex and parallel behavioural descriptions. The problem of transforming the input description to a layout is formulated using a graph model and an algorithm for the data synthesis is given. An example illustrates the algorithm and the capabilities of the structure.

When the signs of the alternate terms of a symmetric discrete time series are reversed and the resultant series is convolved with the original, the newly created time series will have alternate values equal to zero. This theory is shown here to have a potential application in the design of a single-shot zero-forcing equalizer (of the adjust and freeze type). The system can be easily generalized to handle partial response signals.

In this paper the problem of impulsive noise suppression in analog communication systems is considered. The problem of demodulation of amplitude and phase modulated signals in the presence of impulsive noise is formulated by introducing a binary random process to indicate the presence of impulsive noise. It is shown that sub-optimal receiver structures can be derived using this model and these are similar to some experimental receivers reported earlier in the literature. The receivers derived are non-linear in nature and their working is demonstrated through digital computer simulations.

In this paper we examine the problem of optimum demodulation of a class of pulse modulation schemes that employ Secondary frequency modulation-frequently used in satellite data transmission and remote control systems. We develop approximate zero-lag and finite-lag receivers using approximate nonlinear filtering and smoothing techniques and study their steady-state behavior for various pulse modulation schemes. Comparisons of performance are also presented, between the zero-lag and finite-lag receivers on the one hand and between various primary modulation schemes on the other.

The problem of designing optimum receivers with a finite built-in delay, for a class of stochastic signals, is considered. The approach used here is based on the so-called fixed-lag smoothing techniques. Specific cases of amplitude and phase modulation are considered in detail to illustrate the type of optimal (suboptimal in the nonlinear case) receivers which are obtained using this approach. The performance of these finite-delay demodulators is compared with that obtainable using the ideal infinite-delay and the common zero-lag demodulators. It is found that introduction of a nominal delay results in a significant improvement in performance over the zero-lag demodulators, of course, at the cost of increased complexity.