Adaptive blind source separation using constant modulus criterion and signal mutual information

We address the problem of adaptive blind source separation (BSS) from instantaneous multi-input multi-output (MIMO) channels. It is known that the constant modulus (CM) criterion can be used to extract unknown source signals. However, the existing CM based algorithms normally extract the source signals in a serial manner. Consequently, the accuracy in extracting each source signal, except for the first one, depends on the accuracy of previous source extraction. This estimation error propagation (accumulation) causes severe performance degradation. In this paper, we propose a new adaptive separation algorithm that can separate all source signals simultaneously by directly updating the separation matrix. The superior performance of the new algorithm is demonstrated by simulation examples

New blind source estimation methods based on constant modulus criterion

This thesis presents two novel algorithms for blind chancel equalization (BCE) and blind source separation (BSS). Beside these, a general framework for global convergent analysis is proposed. Finally, the open problem of equalising a non-irreducible system is answered by the algorithm proposed in this thesis.

Blind equalization of non-irreducible and non-column-reduced channels driven by constant modulus signals

We address the blind equalization of finite-impulse-response (FIR), multiple-input multiple-output (MIMO) channels excited by constant modulus (CM) signals. It is known that the algorithms based on the constant modulus (CM) criterion can equalize an FIR MIMO channel that is irreducible and column-reduced. We show in this paper that the CM property of signals can be exploited to construct a zero-forcing equalizer for a non-irreducible and non-column-reduced channel. We also give a lower bound for the order of the equalizer. Simulation examples demonstrate the proposed result.

OFDM joint data detection and phase noise cancellation for constant modulus modulations

This correspondence proposes a new algorithm for the OFDM joint data detection and phase noise (PHN) cancellation for constant modulus modulations. We highlight that it is important to address the overfitting problem since this is a major detrimental factor impairing the joint detection process. In order to attack the overfitting problem we propose an iterative approach based on minimum mean square prediction error (MMSPE) subject to the constraint that the estimated data symbols have constant power. The proposed constrained MMSPE algorithm (C-MMSPE) significantly improves the performance of existing approaches with little extra complexity being imposed. Simulation results are also given to verify the proposed algorithm.

Blind equalization of nonirreducible systems using the CM criterion

We address the blind equalization of finite-impulse-response (FIR) and multiple-input multiple-output (MIMO) channel systems excited by constant modulus (CM) signals. It is known that the algorithms based on the CM criterion can equalize an FIR MIMO system that is irreducible. The irreducible condition is restrictive as it requires all source signals to be received at sensors simultaneously. In this paper, we further show that the CM property of signals can be exploited to construct a zero-forcing equalizer for a system that is nonirreducible. Simulation examples demonstrate the proposed result.

Blind equalization of non-irreducible channels driven by MPSK signals

This paper deals with the problem of blind equalization of finite-impulse-response (FIR) and multiple-input multiple-output (MIMO) channels excited by M-ary phase shift keying (MPSK) signals. It is known that the algorithms based on the constant modulus (CM) criterion can equalize an FIR MIMO channel that is irreducible. The irreducible condition is restrictive since it requires that all source signals arrive at the receiving antennas simultaneously. In this paper, we show that the CM criterion can also be used to construct a zero-forcing equalizer for a channel that is non-irreducible. We also derive a lower bound for the order of the equalizer. The proposed result is validated by numerical simulations.

CM-based blind equalization of time-varying SIMO-FIR channel with single pulsation estimation

It is known that the constant modulus (CM) property of the source signal can be exploited to blindly equalize time-invariant single-inputmultiple-output (SIMO) and finite-impulse-response (FIR) channels. However, the time-invariance assumption about the channel cannot be satisfied in several practical applications, e.g., mobile communication. In this paper, we show that, under some mild conditions, the CM criterion can be extended to the blind equalization of a time-varying channel that is described by the complex exponential basis expansion model (CE-BEM). Although several existing blind equalization methods that are based on the CE-BEM have to employ higher order statistics to estimate all nonzero channel pulsations, the CM-based method only needs to estimate one pulsation using second-order statistics, which yields better estimation results. It also relaxes the restriction on the source signal and is applicable to some classes of signals with which the existing methods cannot deal.

A new blind equalization algorithm based on convex combination

The convex combination is a mathematic approach to keep the advantages of its component algorithms for better performance. In this paper, we employ convex combination in the blind equalization to achieve better blind equalization. By combining the blind constant modulus algorithm (CMA) and decision directed algorithm, the combinative blind equalization (CBE) algorithm can retain the advantages from both. Furthermore, the convergence speed of the CBE algorithm is faster than both of its component equalizers. Simulation results are also given to verify the proposed algorithm.

On the power amplifier nonlinearity in MIMO transmit beamforming systems

In this paper, single-carrier multiple-input multiple-output (MIMO) transmit beamforming (TB) systems in the presence of high-power amplifier (HPA) nonlinearity are investigated. Specifically, due to the suboptimality of the conventional maximal ratio transmission/maximal ratio combining (MRT/MRC) under HPA nonlinearity, we propose the optimal TB scheme with the optimal beamforming weight vector and combining vector, for MIMO systems with nonlinear HPAs. Moreover, an alternative suboptimal but much simpler TB scheme, namely, quantized equal gain transmission (QEGT), is proposed. The latter profits from the property that the elements of the beamforming weight vector have the same constant modulus. The performance of the proposed optimal TB scheme and QEGT/MRC technique in the presence of the HPA nonlinearity is evaluated in terms of the average symbol error probability and mutual information with the Gaussian input, considering the transmission over uncorrelated quasi-static frequency-flat Rayleigh fading channels. Numerical results are provided and show the effects on the performance of several system parameters, namely, the HPA parameters, numbers of antennas, quadrature amplitude modulation modulation order, number of pilot symbols, and cardinality of the beamforming weight vector codebook for QEGT.

A modified CM algorithm for blind equalization of MPSK signals

A new blind equalization algorithm for application to wireless communication employing MPSK signals is proposed in this paper.  Since the new cost function exploits the amplitude and phase information simultaneously, the proposed algorithm can provide a superior performance than the conventional constant modulus algorithm (CMA) which only use the amplitude knowledge in its cost function.  Theoretical analysis and numerical simulations both demonstrate that the steady-state mean square error (MSE) for the proposed algorithm is less than that of the CMA.

Adaptive blind channel equalization based on constellation information of MPSK signal

In this paper, we propose a new adaptive algorithm for the blind equalization of an FIR (finite impulse response) channel excited by an M-ary phase shift keying (MPSK) signal. Different from the conventional constant modulus algorithm (CMA), which exploits the amplitude information of the input signal, the proposed algorithm exploits the full constellation information of the input signal. Theoretical analysis shows that the new algorithm has less mean square error (MSE), namely better equalization performance, in steady state than the CMA. Numerical simulations show the effectiveness of the new algorithm