A new mulfitarget constantmodulus array is proposed for CDMA systems based on least squares constant modulus algorithm. The new algorithm is called pre-despreading decision directed least squares constantmodulus alg...
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A new mulfitarget constantmodulus array is proposed for CDMA systems based on least squares constant modulus algorithm. The new algorithm is called pre-despreading decision directed least squares constant modulus algorithm （D-DDLSCMA）. In the new algorithm, the pre-despreading is first applied for multitarget arrays to remove some multiple access signals, then the despreaded signal is processed by the algorithm which united the constant modulus algorithm and decision directed method. Simulation results illustrate the good performance for the proposed algorithm.
This paper proposes a new multitarget constantmodulus array structure for code division multiple access (CDMA) systems. The new algorithm for the structure is called pre-despreading and wavelet denoising constant mod...
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This paper proposes a new multitarget constantmodulus array structure for code division multiple access (CDMA) systems. The new algorithm for the structure is called pre-despreading and wavelet denoising constant modulus algorithm (D-WD-CMA). In the new algorithm, the pre-despreading is applied to multitarget arrays to remove some multiple access inter- ferences. After that the received signal is subjected to wavelet de-noising to reduce some noise, and used in CMA adaptive iteration for signal separation. Simulation results showed that the proposed algorithm performed better than the traditional CMA algorithm.
This paper proposes a modified signal processing structure based on the fractionally Nyquist sample spaced structure for passive bistatic *** recover the direct signal from the multipath clutter,an equalizer of the Au...
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This paper proposes a modified signal processing structure based on the fractionally Nyquist sample spaced structure for passive bistatic *** recover the direct signal from the multipath clutter,an equalizer of the Auto regressive moving average(ARMA)type is proposed based on the fractionally Nyquist sample spaced constantmodulus *** with the conventional Nyquist sample spaced equalizer,the equalizer of the fractionally Nyquist sample spaced ARMA structure is more effective in dealing with deep fading multipath channels with zeros near the unit *** simulations and real data tests indicate that the proposed approach outperforms the conventional processing structure in terms of both clutter residual and mean square error.
This contribution considers semi-blind adaptive equalization for communication systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, approximately equal ...
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This contribution considers semi-blind adaptive equalization for communication systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, approximately equal to the dimension of the equalizer, are first utilized to provide a rough initial least-squares estimate of the equalizer's weight vector. A novel gradient-Newton concurrent constant modulus algorithm and soft decision-directed scheme are then applied to adapt the equalizer. The proposed semi-blind adaptive algorithm is capable of converging fast and accurately to the optimal minimum mean-square error equalization solution. Simulation results obtained demonstrate that the convergence speed of this semi-blind adaptive algorithm is close to that of the training-based recursive least-square algorithm. Copyright (C) 2009 John Wiley & Sons, Ltd.
This paper addresses the problem of blind demixing of instantaneous mixtures in a multiple-input multiple-output communication system. The main objective is to present efficient blind source separation (BSS) algorithm...
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This paper addresses the problem of blind demixing of instantaneous mixtures in a multiple-input multiple-output communication system. The main objective is to present efficient blind source separation (BSS) algorithms dedicated to moderate or high-order quadratic-amplitude modulation (QAM) constellations. Four new iterative batch, BSS algorithms are presented dealing with the multimodulus (MM) and alphabet matched (AM) criteria. For the optimization of these cost functions, iterative methods of Givens and hyperbolic rotations are used. A prewhitening operation is also utilized to reduce the complexity of design problem. It is noticed that the designed algorithms using Givens rotations give satisfactory performance only for a large number of samples. However, for a small number of samples, the algorithms designed by combining both Givens and hyperbolic rotations compensate for the ill-whitening that occurs in this case and thus improves the performance. Two algorithms dealing with the MM criterion are presented for moderate-order QAM signals such as 16-QAM. The other two dealing with the AM criterion are presented for high-order QAM signals. These methods are finally compared with the state-of-the-art batch BSS algorithms in terms of signal-to-interference and noise ratio, symbol error rate, and convergence rate. Simulation results show that the proposed methods outperform the contemporary batch BSS algorithms.
The communication systems for Poisson channels require long pilot for channel estimation and may result in large percentage of overhead due to the signal-dependent noise of Poisson-distributed signal, i.e., both signa...
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The communication systems for Poisson channels require long pilot for channel estimation and may result in large percentage of overhead due to the signal-dependent noise of Poisson-distributed signal, i.e., both signal part and noise part experience random processes. In this paper, both blind and semi-blind channel estimation methods are studied to shorten the overhead and increase the transmission efficiency for Poisson channels. First, fractionally spaced equalizers are proposed based on modified constant modulus algorithm (CMA) and subspace (SS). Second, a data-aided iterative channel estimation (ICE) is designed and analyzed in terms of its asymptotic unbiasedness and convergence. The proposed methods are evaluated based on both a constant channel scenario and a varying channel scenario. Numerical simulation results show that the modified CMA has the worst bit-error rate performance but requires the lowest computational complexity. Besides, both SS based channel estimation and ICE have negligible overhead and comparable bit-error rate performances with respect to the conventional periodic pilot based channel estimation having 50% overhead.
A new approach to fractionally spaced blind equalisation of finite-duration impulse response (FIR) channels is proposed based on the method of least squares (LS) and the constant modulus algorithm (CMA). A nonlinear t...
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A new approach to fractionally spaced blind equalisation of finite-duration impulse response (FIR) channels is proposed based on the method of least squares (LS) and the constant modulus algorithm (CMA). A nonlinear transformation of the equaliser parameters is formulated and solved for, so as to avoid the potential problems associated with fractionally spaced CMA (FS-CMA) when the channel input is correlated. The new algorithm has a fast convergence rate in comparison with FS-CMA and the resulting equaliser setting is invariant to channel input correlation so long as all finite-length subsequences of the channel input sequence occur with nonzero probability. Although the algorithm is based on the assumption of constantmodulus channel inputs, its application to nonconstantmodulus constellations such as M-ary quadrature amplitude modulation (QAM) is also illustrated. The issue of channel noise enhancement is studied in connection with subchannel zeros, and a method for reducing inflated equaliser norms is proposed by way of reduced rank matrix approximation. A modified recursive least squares implementation of the algorithm is simulated to demonstrate its superior performance vis-a-vis FS-CMA. (C) 1997 Elsevier Science B.V.
Massive multiple-input multiple-output (MIMO) transmission, in which the number of antennas is considerably more than the number of user terminals, has attracted attention as a key technology in next-generation mobile...
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Massive multiple-input multiple-output (MIMO) transmission, in which the number of antennas is considerably more than the number of user terminals, has attracted attention as a key technology in next-generation mobile communication systems, because it enables improvements in the service area and interference mitigation with simple signal processing. Multi-beam massive MIMO employing high-power beam selection in the analog part and a blind algorithm in the digital part, such as the constant modulus algorithm that does not need channel state information, has been proposed and shown to offer high transmission efficiency. In this paper, in order to realize higher transmission rates and communication efficiency, we propose a beam-selection method that uses multi-beam amplitude information only. Furthermore, this method can be realized through signal processing with a simple configuration and is highly suitable for hybrid analog-digital massive MIMO, which is advantageous in terms of cost and power consumption. Here, the effectiveness of the proposed method is verified by computer simulation.
Decision feedback equalisers offer a good compromise between complexity and performance for channels with strong intersymbol interference. However, their blind or decision-directed adaptation may converge to degenerat...
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Decision feedback equalisers offer a good compromise between complexity and performance for channels with strong intersymbol interference. However, their blind or decision-directed adaptation may converge to degenerative solutions for which signal at the equaliser's output is independent of its input. The known algorithms proposed to solve this problem, are evaluated in this paper. It is shown that their main defect is a lack of well-defined criteria allowing the detection of degenerative solutions, so this paper introduces a criterion proved to be sufficient for reliable detection of such solutions. Using the new criterion, an algorithm of blind decision feedback equalisation, based on constrained optimisation, is proposed. The new algorithm does not admit degenerative solutions therefore should be preferred among the analysed algorithms. Also, the problem of false phase lock, characteristic of some modulations, is addressed and a solution to it is proposed. The results of the study are presented using the experimental data and simulation. (C) 2002 Elsevier Science B.V. All rights reserved.
A novel high precision adaptive equalization method is introduced and applied to dynamic equalization for quadrature phase shift keying (QPSK) coherent optical communication system in this paper. A frequency-domain co...
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A novel high precision adaptive equalization method is introduced and applied to dynamic equalization for quadrature phase shift keying (QPSK) coherent optical communication system in this paper. A frequency-domain constant modulus algorithm (CMA) method is used to equalize the received signal roughly. Then, some non-ideal output signals will be picked out through the error measurement, and they will be equalized accurately further in a fixed time-domain CMA equalizer. This high precision equalization method can decrease the equalization error, then it can reduce the bit error ratio (BER) of coherent communication system. Simulation results show that there is a 6% decrease for computation complexity by proposed scheme when compared with time-domain CMA. Furthermore, compared with time-domain CMA and frequency-domain CMA, about 2 dB and 2.2 dB in OSNR improvement can be obtained by proposed scheme at the BER value of 1e-3, respectively. (C) 2015 Elsevier B.V. All rights reserved.
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