New normalized constant modulus algorithms with relaxation

Published versio

New block-based blind equalization algorithms

New block-based blind equalization algorithms are introduced based upon the cost function underlying the recently proposed soft constraint satisfaction blind equalization algorithm. The derivation of these .algorithms is based on mapping the original constrained optimization problem in CN into a much simpler optimization problem in W2. Versions of the new algorithms are also developed for fractionally-spaced equalizers. Simulations on a baud-spaced and a fractionally-spaced channel support the potential of the resulting block-based techniques

Blind fractionally spaced channel equalization for shallow water PPM digital communications links

Underwater acoustic digital communications suffer from inter-symbol interference deriving from signal distortions caused by the channel propagation. Facing such kind of impairment becomes particularly challenging when dealing with shallow water scenarios characterized by short channel coherence time and large delay spread caused by time-varying multipath effects. Channel equalization operated on the received signal represents a crucial issue in order to mitigate the effect of inter-symbol interference and improve the link reliability. In this direction, this contribution presents a preliminary performance analysis of acoustic digital links adopting pulse position modulation in severe multipath scenarios. First, we show how the spectral redundancy offered by pulse position modulated signals can be fruitfully exploited when using fractional sampling at the receiver side, which is an interesting approach rarely addressed by the current literature. In this context, a novel blind equalization scheme is devised. Specifically, the equalizer is blindly designed according to a suitably modified Bussgang scheme in which the zero-memory nonlinearity is replaced by a M-memory nonlinearity, M being the pulse position modulation order. Numerical results not only confirm the feasibility of the technique described here, but also assess the quality of its performance. An extension to a very interesting complex case is also provided

Optimum delay and mean square error using CMA

The performance of the constant modulus algorithm can suffer because of the existence of local minima with large mean squared error (MSE). This paper presents a new way of obtaining the optimum MSE over all delays using a second equalizer under a mixed constant modulus and cross correlation algorithm (CM-CCA). Proof of convergence is obtained for the noiseless case. Simulations demonstrate the potential of the metho

Signal Processing Design of Low Probability of Intercept Waveforms

This thesis investigates a modification to Differential Phase Shift Keyed (DPSK) modulation to create a Low Probability of Interception/Exploitation (LPI/LPE) communications signal. A pseudorandom timing offset is applied to each symbol in the communications stream to intentionally create intersymbol interference (ISI) that hinders accurate symbol estimation and bit sequence recovery by a non-cooperative receiver. Two cooperative receiver strategies are proposed to mitigate the ISI due to symbol timing offset: a modified minimum Mean Square Error (MMSE) equalization algorithm and a multiplexed bank of equalizer filters determined by an adaptive Least Mean Square (LMS) algorithm. Both cooperative receivers require some knowledge of the pseudorandom symbol timing dither to successfully demodulate the communications waveform. Numerical Matlab® simulation is used to demonstrate the bit error rate performance of cooperative receivers and notional non-cooperative receivers for binary, 4-ary, and 8-ary DPSK waveforms transmitted through a line-of-sight, additive white Gaussian noise channel. Simulation results suggest that proper selection of pulse shape and probability distribution of symbol timing offsets produces a waveform that is accurately demodulated by the proposed cooperative receivers and significantly degrades non-cooperative receiver symbol estimation accuracy. In typical simulations, non-cooperative receivers required 2-8 dB more signal power than cooperative receivers to achieve a bit error rate of 1.0%. For nearly all reasonable parameter selections, non-cooperative receivers produced bit error rates in excess of 0.1%, even when signal power is unconstrained

Low Probability of Intercept Waveforms via Intersymbol Dither Performance under Multipath Conditions

This thesis examines the effects of multipath interference on Low Probability of Intercept (LPI) waveforms generated using intersymbol dither. LPI waveforms are designed to be difficult for non-cooperative receivers to detect and manipulate, and have many uses in secure communications applications. In prior research, such a waveform was designed using a dither algorithm to vary the time between the transmission of data symbols in a communication system. This work showed that such a method can be used to frustrate attempts to use non-cooperative receiver algorithms to recover the data. This thesis expands on prior work by examining the effects of multipath interference on cooperative and non-cooperative receiver performance to assess the above method’s effectiveness using a more realistic model of the physical transmission channel. Both two and four ray multipath interference channel models were randomly generated using typical multipath power profiles found in existing literature. Different combinations of maximum allowable symbol delay, pulse shapes and multipath channels were used to examine the bit error rate performance of 1) a Minimum Mean Squared Error (MMSE) cooperative equalizer structure with prior knowledge of the dither pattern and 2) a Constant Modulus Algorithm (CMA) non-cooperative equalizer. Cooperative MMSE equalization resulted in approximately 6-8 dB BER performance improvement in Eb/No over non-cooperative equalization, and for a full range symbol timing dither non-cooperative equalization yields a theoretical BER limit of Pb=10−1. For 50 randomly generated multipath channels, six of the four ray channels and 15 of the two ray channels exhibited extremely poor equalization results, indicating a level of algorithm sensitivity to multipath conditions

CMA Channel Equalization Through An Adaptive MMSE Equalizer Based RLS Algorithm

The adaptive algorithm has been widely used in the digital signal processing like channel estimation, channel equalization, echo cancellation, and so on. One of the most important adaptive algorithms is the RLS algorithm. We present in this paper n multiple objective optimization approach to fast blind channel equalization. By investigating first the performance (mean-square error) of the standard fractionally spaced CMA (constant modulus algorithm) equalizer in the presence of noise, we show that CMA local minima exist near the minimum mean-square error (MMSE) equalizers. Consequently, CMA may converge to a local minimum corresponding to a poorly designed MMSE receiver with considerable large mean-square error. The step size in the RLS algorithm decides both the convergence speed and the residual error level, the highest speed of convergence and residual error level

Adaptive Blind Channel Equalization for Mobile Multimedia Communication

In the last decade much research effort has been dedicated to deal with the issues of wireless multimedia communications, in particular bandwidth limitation and channel impairment. We have recently proposed a new scheme for blind equalization called sinusoidally-distributed dither signed-error constant modulus algorithm (S-DSE-CMA). In this paper, we test this scheme for wireless image transmission. Simulation showed that the low complexity of implementation and fast convergence rate are the major advantages of employing the new scheme for multimedia applications. It is also shown, from perceptual-based analysis as well as objective measurements using peak signal-to-noise ratio (PSNR) of the recovered image, that the recently-proposed blind adaptive equalization algorithm outperforms existing methods, e.g., uniformly-distributed DSE-CMA

Blind adaptive equalization for QAM signals: New algorithms and FPGA implementation.

Adaptive equalizers remove signal distortion attributed to intersymbol interference in band-limited channels. The tap coefficients of adaptive equalizers are time-varying and can be adapted using several methods. When these do not include the transmission of a training sequence, it is referred to as blind equalization. The radius-adjusted approach is a method to achieve blind equalizer tap adaptation based on the equalizer output radius for quadrature amplitude modulation (QAM) signals. Static circular contours are defined around an estimated symbol in a QAM constellation, which create regions that correspond to fixed step sizes and weighting factors. The equalizer tap adjustment consists of a linearly weighted sum of adaptation criteria that is scaled by a variable step size. This approach is the basis of two new algorithms: the radius-adjusted modified multitmodulus algorithm (RMMA) and the radius-adjusted multimodulus decision-directed algorithm (RMDA). An extension of the radius-adjusted approach is the selective update method, which is a computationally-efficient method for equalization. The selective update method employs a stop-and-go strategy based on the equalizer output radius to selectively update the equalizer tap coefficients, thereby, reducing the number of computations in steady-state operation. (Abstract shortened by UMI.) Source: Masters Abstracts International, Volume: 45-01, page: 0401. Thesis (M.A.Sc.)--University of Windsor (Canada), 2006

New receiver for joint blind equalization and carrier phase recovery of QAM signals

Published versio