Search

This work investigates the problem of blind channel equalization in the presence of burst noise. Modeling impulsive noise distribution as generalized-Gaussian, we derive an appropriate criterion for blind equalization. Our method exploits Wijsman’s theorem and develops a maximal-invariant test of equally-likely pulsed signals against impulsive disturbance. We optimize the test and realize an adaptive equalizer, capable of not only mitigating intersymbol interference but also robust to impulsive disturbance. Numerical simulations, obtained on a baseband digital microwave radio system for amplitude-phase shift keying signaling in additive (generalized Gaussian and symmetric-alpha stable) impulsive environment, confirm the admissibility of the proposed equalizer in terms of robustness and steady convergence.

In this work, we address the target tracking problem for a coordinate-decoupled Markovian jump-mean-acceleration based maneuvering mobility model. A novel low-complexity alternative to the conventional interacting multiple model (IMM) filter is proposed for this class of mobility models. The proposed tracking algorithm utilizes a bank of interacting filters where the interactions are limited to the mixing of the mean estimates, and it exploits a fixed off-line computed Kalman gain matrix for the entire filter bank. Consequently, the proposed filter does not require matrix inversions during on-line operation which significantly reduces its complexity. Simulation results show that the performance of the low-complexity proposed scheme remains comparable to that of the traditional (highly-complex) IMM filter. Furthermore, we derive analytical expressions that iteratively evaluate the transient and steady-state performance of the proposed scheme, and establish the conditions that ensure the stability of the proposed filter. The analytical findings are in close accordance with the simulated results.

Multimodulus algorithms (MMA) based adaptive blind equalizers mitigate inter-symbol interference and recover carrier-phase in communication systems by minimizing dispersion in the in-phase and quadrature components of the received signal using the respective components of the equalized sequence in a decoupled manner. These equalizers are mostly incorporated in bandwidth-efficient digital receivers which rely on quadrature amplitude modulation (QAM) signaling. The nonlinearities in the update equations of these equalizers tend to lead to difficulties in the study of their steady-state performance. This paper presents originally the steady-state excess mean-square-error (EMSE) analysis of different members of multimodulus equalizers MMAp–qin a non-stationary environment using energy conservation arguments, and thus bypassing the need for working directly with the weight error covariance matrix. In doing so, the exact and approximate expressions for the steady-state mean-square-error of several MMA based blind equalization algorithms are derived, including MMA2–2, MMA2–1, MMA1–2, and MMA1–1. The accuracy of the derived analytical results isvalidated using Monte–Carloexperiments and found to be in close agreement. The authors acknowledge the support of COMSATS Institute of Information Technology (Islamabad and Wah Campuses), Pak-istan, the Deanship of Scientific Research at King Fahd University of Petroleum and Minerals under research grant RG1414, Saudi Arabia, and Brunel University London, UK towards the accomplish-ment of this work. They also acknowledge the Editor and anony-mous reviewers for their support and valuable feedback.

Multimodulus algorithms (MMA) based adaptive blind equalizers mitigate inter-symbol interference in a digital communication system by minimizing dispersion in the quadrature components of the equalized sequence in a decoupled manner, i.e., the in-phase and quadrature components of the equalized sequence are used to minimize dispersion in the respective components of the received signal. These unsupervised equalizers are mostly incorporated in bandwidth-efficient digital receivers (wired, wireless or optical) which rely on quadrature amplitude modulation based signaling. These equalizers are equipped with nonlinear error-functions in their update expressions which makes it a challenging task to evaluate analytically their steady-state performance. However, exploiting variance relation theorem, researchers have recently been able to report approximate expressions for steady-state excess mean square error (EMSE) of such equalizers for noiseless but interfering environment.In this work, in contrast to existing results, we present exact steady-state tracking analysis of two multimodulus equalizers in a non-stationary environment. Specifically, we evaluate expressions for steady-state EMSE of two equalizers, namely the MMA2-2 and the βMMA. The accuracy of the derived analytical results is validated using different set experiments and found in close agreement. HighlightsWe provide performance analysis of two multimodulus blind equalizers.The analysis evaluates EMSE performance in both stationary and non-stationary environments.The analysis can provide the optimal equalizer length for the given channel and step-size.We validate our analytical findings for both fixed and time-varying channels.

In this paper, we design and analyze a Newton-like blind equalization algorithm for the APSK system. Specifically, we exploit the principle of minimum entropy deconvolution and derive a blind equalization cost function for APSK signals and optimize it using Newton?s method. We study and evaluate the steady-state excess mean square error performance of the proposed algorithm using the concept of energy conservation. Numerical results depict a significant performance enhancement for the proposed scheme over well established blind equalization algorithms. Further, the analytical excess mean square error of the proposed algorithm is verified with computer simulations and is found to be in good conformation. HighlightsFormulation of a Newton-like blind equalization algorithm for APSK system.Discussion on stationary points of the cost in joint impulse response domain.Discussion on equalizer's tracking performance in non-stationary environment.Evaluation of moments in closed-form using Nuttal Q-function.

Exploiting the error variance relation, this letter discusses the evaluation of excess mean square error (EMSE) of constant modulus equalizers in a noise-free non-stationary environment. The EMSE analyses are presented for two equalizers - the CMA22 and the βCMA. Simulation results show a close match in theoretical and simulated errors for both algorithms.

In this letter, we adaptively optimize the equalizer output energy to obtain a joint blind equalization and carrier-phase recovery solution. The resulting (multimodulus) update algorithm possesses a particular zero-memory Bussgang-type nonlinearity. We provide evidence of good performance, in comparison to existing adaptive methods, like RCA, MMA and CMA, through computer simulations for higher-order quadrature amplitude modulation signalling on symbol- and fractionally-spaced channels.

A constant modulus algorithm is presented for blind equalization of complex-valued communication channels. The proposed algorithm is obtained by solving a novel deterministic optimization criterion which comprises the minimization of a priori as well as a posteriori dispersion error, leading to an update equation having a particular zero-memory continuous Bussgang-type nonlinearity. We also derive a stochastic bound for the range of step-sizes for a generic Bussgang-type constant modulus algorithm. The theoretical result is validated through computer simulations.

This letter presents two new blind equalization algorithms that are specifically designed for cross-QAM signals. Proposed algorithms minimize the dispersion of the equalizer output with respect to single or multiple cross-shaped zero error contour(s). Simulations and analysis demonstrate the good performance of the proposed algorithms

In this work, we present an adaptive non-data-aided compensator for the in-phase/quadrature-phase (I/Q) mismatch in low-intermediate frequency (heterodyne) receivers. In particular, the adaptive I/Q mismatch algorithm is derived by exploiting the uncorrelatedness between the desired and the image signals, and is used to compensate for gain imbalance and phase-offset error. Furthermore, the frequency-offset error is separately compensated by using an adaptive minimization of a fourth-order statistics based cost function.

We employ minimum entropy deconvolution principle for blind equalization of complex digital signals. In essence, we maximize the output energy, constrain the equalizer output not to exceed certain level and obtain an adaptive solution capable of opening a closed-eye with the recovery of true energy of signal. We provide evidence of good performance in comparison to existing adaptive methods, like CMA and its variants, through simulations.

In this article, we introduce the principle of minimum entropy in the context of blindly equalizing a digital communication channel. We discuss how to use this principle to design an inter-symbol-interference sensitive cost for an exemplary amplitude-phase shift-keying signaling. We also discuss the admissibility of the proposed cost and the stability of the derived adaptive algorithm.

Stop-and-go decision-directed (S-and-G-DD) equalization is the most primitive blind equalization (BE) method for the cancelling of intersymbol-interference in data communication systems. Recently, this scheme has been applied to complex-valued multilayer feedforward neural network, giving robust results with a lower mean-square error at the expense of slow convergence. To overcome this problem, in this work, a fast converging recursive least squares (RLS)-based complex-valued backpropagation learning algorithm is derived for S-and-G-DD blind equalization. Simulation results show the effectiveness of the proposed algorithm in terms of initial convergence.

This paper presents a new family of algorithms for blind equalization of cross-QAM signals. It is shown that the proposed Generalized Cross-Contour Algorithm (GCrCA) has a tendency to force the equalizer output to lie onto a cross-shaped contour, yielding a successful removal of ISI and recovering the correct orientation of the constellation simultaneously.

In this paper, some methods are examined for accelerating the convergence time of a recently proposed blind equalization algorithm [Abrar et al. (2004)]. It is shown that, as in conventional equalizers, the adaptive self-or pre-orthogonalization methods can be exploited to enhance the convergence of a blind equalization algorithm. An improvement in convergence time is reported.

A new method for blind phase estimation is proposed for cross QAM a communication system which uses the estimates of the sixteenth-order statistics of the received signal. Computer simulations reveal that the proposed estimator is capable of giving about the same root mean square error (RMSE) as that of Cartwright's eighth-order estimator while needing even less than half of the number of samples (for cross QAM constellations)