Blind decision feedback equalization for VSB-based DTV receivers

Intersymbol interference (ISI) of the radio propagation through multipath fading channels is a major factor that limits the performance of mobile communication systems. Blind decision feedback equalization (DFE) is one of major methods for channel equalization. We propose a new method, based on a Hammerstein filter instead of DFE filters, for enhancing the performance of DFE, hence, blind HDFE. In this paper, we show the bit error rate (BER) performance of blind DFE and blind HDFE, in order to prove the superiority of BHDFE.

The simplified Gaussian clustering algorithm (SGCA) adopting a reduced constellation is derived, then the dual-variance Gaussian clustering algorithm (DVGCA) is proposed, which makes the soft or hard decisions using the SGCA. Since the DVGCA is extremely reduced-complexity and operates in the soft or hard decisions mode according to the variance for error level of the equalizer output, it is effective for blind equalization of high-order quadrature amplitude modulation (QAM) signals. In addition, the blind decision feedback equalizer (DFE) using the DVGCA is presented, which leads to superior performance to ones without a feedback path over the channel with in-band spectral nulls.

In digital wireless communications, blind equalization without training sequence or any priori knowledge of the channel dynamics has become a topic problem, and one of its most important performance criterions is the convergence speed. Traditional constant modulus algorithm (CMA) with many advantages is a popular blind equalization approach, but its slower convergence rate is unsuitable for the compensation of the multipath fading wireless channels. In this paper, a novel blind channel equalization algorithm is presented by introducing a decorrelation factor into the equalization process. The improvement in convergence rate as well as residual MSE of the proposed algorithm is confirmed by computer simulation results.

The Concept of Adaptive Equalization is to counter Intersymbol Interference (ISI) which severely degrades the performance of a Communication System. Adaptive Equalization can be classified into Supervised/Trained Equalization and Unsupervised/Blind Equalization. Supervised Equalization is carried out with the aid of a training sequence and Blind Equalization is done without the aid of a training sequence. Godard's Constant Modulus Algorithm (CMA) was the very first blind equalization algorithm that could be used in two dimensional digital communication systems. It requires the knowledge of statistical properties of the transmitted data symbols to perform channel equalization. Picchi and Prati by modifying the standard Decision-Directed Algorithm proposed a new Blind Equalization Algorithm known as "Stop-and-Go" Decision-Directed Algorithm. This paper compares the performance of Blind Equalization algorithms: CMA and Stop-and-Go. Simulation results indicate faster convergence rate of Stop-and-Go than CMA for 16 and 64 Quadrature Amplitude Modulated (QAM) transmitted constellations. The results also indicate negligible difference between the MSE's of Stop-and-Go after convergence and supervized equalizer.

A blind equalization algorithm may switch to a decision-directed (DD) equalization mode in order to speed up the convergence rate and improve the steady-state performance. The crux for this kind of equalization is the control of the switches between the two equalization mode. A new blind equalization scheme is proposed which automatically controls the switches between the blind equalization mode and DD equalization mode according to the estimated error variance, and the blind equalization mode used in the proposed scheme is the modified constant modulus algorithm. Simulation results shows that the proposed blind equalization scheme can present significant improvements in the convergence rates along with steady-state performance

This paper builds up the model of the multicarrier direct sequence-code division multiple access (MC DS-CDMA) system with time reversal space-time block coding (TR-STBC) transmit diversity, based on which steepest decreasing constant modulus algorithm (SDCMA) for blind equalization is studied. Simulations are performed and the conclusions are given. The conclusions show that the blind equalization based upon constant modulus algorithm (CMA) is simple and feasible in the MC DS-CDMA system with TR-STBC, and however CMA blind equalization can't improve system performance well when multiple access interference (MAI) is fairly severe.

All existing blind equalization algorithms rely on the non-Gaussianity of the input sequence. In recent years, a technique called shaping has been used in data transmission, in order to approach the capacity of Gaussian channels. The transmitted signal then has a Gaussian-like distribution and this will affect blind equalization algorithms. In this paper, we address the problem of blind equalization where the input of the unknown system is a shaped data signal. In particular, we demonstrate the effects of shaping on some of the widely known blind equalization schemes. Our results point to the need for more powerful blind equalization algorithms for shaped signals.

The constant modulus algorithm (CMA) for blind equalization requires a separate carrier-recovery system for phase recovery. A modified CMA, called the multimodulus algorithm (MMA), which may perform joint blind equalization and carrier recovery without the need for a separate carrier-recovery system for quadrature amplitude modulation (QAM) signal constellations. This letter mathematically analyzes the steady-state mean square error (MSE) of MMA. Analysis results indicate that MMA produces 50% fewer steady-state MSE than CMA.

With the surge of Internet of Things (IoT) applications using unmanned aerial vehicles (UAVs), there is a huge demand for an excellent complexity/power efficiency trade-off and channel fading resistance at the physical layer. In this paper, we consider the blind equalization of short-continuous-phase-modulated (CPM) burst for UAV-aided IoT. To solve the problems of the high complexity and poor convergence of short-burst CPM blind equalization, a novel turbo blind equalization algorithm is proposed based on establishing a new expectation–maximization Viterbi (EMV) algorithm and turbo scheme. Firstly, a low complexity blind equalization algorithm is obtained by applying the soft-output Lazy Viterbi algorithm within the EM algorithm iteration. Furthermore, a set of initializers that achieves a high global convergence probability is designed by the blind channel-acquisition (BCA) method. Meanwhile, a soft information iterative process is used to improve the system performance. Finally, the convergence, bit error rate, and real-time performance of iterative detection can be further improved effectively by using improved exchange methods of extrinsic information and the stopping criterion. The analysis and simulation results show that the proposed algorithm achieves a good blind equalization performance and low complexity.

Since cyclostationarity is inherent in many man-made signals, there is much to be gained in the signal processing and communication areas if this property is properly recognised and exploited. In particular, the authors propose a novel two-stage scheme which exploits second-order cyclostationary statistics for co-channel interference removal and blind equalisation. The first stage adopts the blind adaptive (BA) FRESH filter proposed by Zhang, to remove co-channel interference and channel noise. The second stage is based on a blind equalisation algorithm, proposed by Tong, which operates on the filtered cyclic signal to remove intersymbol interference. Simulation studies have demonstrated that this two-stage blind equalisation scheme has a fast rate of convergence and excellent performance in a high SNR environment.

There is no doubt about the growing interest for the underwater acoustic communications. Among all existing applications, the objective of the Groupe d'Etudes Sous-Marines de l'Atlantique (GESMA) is to develop a sufficiently robust high data rate acoustic link, named TRIDENT. For that purpose, different kinds of information (texts, images...) could be periodically transmitted through the acoustic channel. A realtime receiver, based on the spatio-temporal blind adaptive decision feedback equalizer, developed and patented by ENST Bretagne [J. Labet et al., 1995], was designed to cope with all perturbations induced by such harsh channels. Some sea trials have been carried out in June 2002. The first results are clearly convincing since most of the 48 sequences of 5 minutes are successfully detected by the DSP-based real-time receiver. This acoustic system allows transmission at data rates ranging from 8 to 25 kbps in horizontal configuration.

The project of ant colony algorithm optimization neural network combining blind equalization algorithm is proposed. The better initial weights of neural networks are provided because of the randomness, ergodicity and positive feedback of the ant colony algorithm. And then, a combination of optimal weights are found through BP algorithm, which is fast local search speed. Thus blind equalization performance is improved. Computer simulation show that, the novel blind equalization algorithm speeds up the convergence rate, reduces the remaining steady-state error and bit error rate, which is compared with the Neural Network Blind Equalization Algorithm(NNBE) and Genetic Algorithm optimization Neural Network Blind Equalization Algorithm(GA-NNBE) .

In this paper, a new blind equalization algorithm is proposed based on guard interval (GI)-restoral property for quadrature amplitude modulation (QAM) signals. The proposed algorithm utilizes existing redundancy in the time domain to completely eliminates inter-symbol-interference. We prove that the usage of GI-restoral property is sufficient to obtain a zero-forcing equalizer of the channel. The main advantage of this approach resides in its simplicity as the equalizer coefficients are estimated using a second-order least square fitting (LSF) scheme. The equalizer uses the LSF in the initial phase and then switches to a proposed constant modulus algorithm (CMA). The proposed CMA is constructed through the exploitation of a fully data information. To achieve a dramatic improvement in equalization performance, a modified CMA (MCMA) is proposed for OFDM systems based on cyclic prefixing approach. The resulting scheme provides a state-of-the-art low complexity with superior performance blind equalization. Extensive simulation shows that LSF-MCMA has a better steady-state equalization performance than LSF-CMA.

If the data are prewhitened, then gradient adaptive algorithms which are simpler than higher order statistics algorithm, can be used in blind equalization. In this paper, we propose a subband affine projection algorithm with improved convergence performance and reduced computational complexity for multiple-input multiple-output equalization in the blind environments. All of the adaptive filters in subband affine projection equalization are decomposed to polyphase components, and the coefficients of the decomposed adaptive subfilters are updated by defining the multiple cost functions. An infinite impulse response filterbank is designed for the data prewhitening. Prewhitening data through subband filtering can speed up the convergence rate without additional computation. Simulation results are presented showing the proposed algorithm's convergence rate and constellation equalization performance.

In this paper we propose a blind adaptive algorithm for the decision feedback equalizer based on high order MCMA (modified constant modulus algorithm) and decision directed adaptation. The originality of the proposed method is that the feedforward and the feedback filters are adjusted simultaneously by using the high order MCMA algorithm and by switching to the decision directed mode when the equalized symbols are in the convergence zones. This method reduces the propagation of error caused by the DFE structure. The mean square error (MSE) between the transmitted symbols and the equalized symbols is computed as performance metric. The proposed method is compared to the classic DFE based on second order MCMA. For all simulations, the ensemble-averaged MSE is obtained from 100 Monte Carlo runs. The obtained result show that the proposed method performs well for high constellations in the presence of Gaussian noise, comparatively with other methods.