In this paper we describe a new framework of feature compensation for robust speech recognition, which is suitable especially for small devices. We introduce Delta-cepstrum Normalization (DCN) that normalizes not only cepstral coefficients, but also their time-derivatives. Cepstral Mean Normalization (CMN) and Mean and Variance Normalization (MVN) are fast and efficient algorithms of environmental adaptation, and have been used widely. In those algorithms, normalization was applied to cepstral coefficients to reduce the irrelevant information from them, but such a normalization was not applied to time-derivative parameters because the reduction of the irrelevant information was not enough. However, Histogram Equalization (HEQ) provides better compensation and can be applied even to the delta and delta-delta cepstra. We investigate various implementation of DCN, and show that we can achieve the best performance when the normalization of the cepstra and the delta cepstra can be mutually interdependent. We evaluate the performance of DCN using speech data recorded by a PDA. DCN provides significant improvements compared to HEQ. It is shown that DCN gives 15% relative word error rate reduction from HEQ. We also examine the possibility of combining Vector Taylor Series (VTS) and DCN. Even though some combinations do not improve the performance of VTS, it is shown that the best combination gives the better performance than VTS alone. Finally, the advantage of DCN in terms of the computation speed is also discussed.

In this paper, the space time transmit diversity (STTD) decoding combined with minimum mean square error (MMSE) equalization is presented for MC-CDMA downlink and uplink in the presence of multiple receive antennas. The equalization weights that minimize the MSE for each subcarrier are derived. From computer simulation, it was found that the BER performance of STTD decoding combined with MMSE equalization and Mr-antenna diversity reception using the weights derived in this paper provides the same diversity order as 2Mr-antenna receive diversity with MMSE equalization but with 3 dB performance penalty and is always better than that with no diversity. The uplink BER performance can also be improved with STTD, but the error floor still exists. However, with 2-receive antennas in addition to 2-antenna STTD, the BER floor can be reduced to around 10-5 even for the uplink.

A time-domain equalization (TEQ) algorithm is presented to shorten the effective channel impulse response to increase the transmission efficiency of the 54 Mbps IEEE 802.11a orthogonal frequency division multiplexing (OFDM) system. In solving the linear equation Aw = B for the optimum TEQ coefficients, A is shown to be Hermitian and positive definite. The LDLT and LU decompositions are used to factorize A to reduce the computational complexity. Simulation results show high performance gains at a data rate of 54 Mbps with moderate orders of TEQ finite impulse response (FIR) filter. The design and implementation of the algorithm in field programmable gate array (FPGA) are also presented. The regularities among the elements of A are exploited to reduce hardware complexity. The LDLT and LU decompositions are combined in hardware design to find the TEQ coefficients in less than 4 µs. To compensate the effective channel impulse response, a radix-4 pipeline fast Fourier transform (FFT) is implemented in performing zero forcing equalization. The hardware implementation information is provided and simulation results are compared to mathematical values to verify the functionalities of the chips running at 54 Mbps.

For the reception of MC-CDMA signals in a frequency-selective fading channel, frequency-domain equalization is necessary before despreading. In this paper, joint antenna diversity combining and one-tap frequency-domain equalization is considered (simply referred to as the joint antenna diversity & equalization, in this paper). A receiver structure for joint antenna diversity & equalization is presented and the unified weights based on minimum mean square error (MMSE) criterion are found in the presence of multi-users with different spreading factors and transmit powers. For comparison, antenna diversity combining after despreading using MMSE combining (MMSEC) is also considered. The achievable bit error rate (BER) performances with joint antenna diversity & equalization and with antenna diversity after MMSEC despreading in a frequency-selective Rayleigh fading channel are evaluated by computer simulations and compared.

The channel noise in OFDM systems affects the accuracy of channel estimation, deteriorating the performance of equalization. We present a novel algorithm with MMSE (Minimum Mean Square Error) channel estimation based on Hadamard Transform, to mitigate the effects of noise. The performance of the proposed algorithm is proved to be better than that with LS (Least Square) estimation, and very close to that with the MMSE estimation based on Fourier Transform, while the computation required is pretty small due to the use of Hadamard Transform.

The purpose of this paper is to propose a novel cluster map based blind RBF equalizer for received signal constellation (RSC) independent channel, which belongs to RSC based blind equalization approach. Without channel estimator, firstly, the desired numbers of unlabeled RBF centers are obtained by an unsupervised clustering algorithm. Then a cluster map generated from the known RBF equalizer structure is used to partition the unlabeled centers into appropriate subsets merely by several simple sorting operations, which corresponds to the weight initialization. Finally, the weight is adjusted iteratively by an unsupervised least mean square (LMS) algorithm. Since the process of the weight initialization using the underlying structure of RBF equalizer is very effective, the proposed blind RBF equalizer can achieve almost identical performance with the optimal RBF equalizer. The validity of the proposed equalizer is also demonstrated by computer simulations.

Frequency-domain representation of the well-known time-domain rake combining for the antenna diversity reception of DS-CDMA signals is derived. Two receiver structures using frequency-domain rake combining are presented. Frequency-domain rake combining can alleviate the complexity problem of the time-domain rake arising from too many paths in a severe frequency selective fading channel at the cost of guard interval insertion. The results shown in this paper show a possibility that a DS-CDMA approach still remain to be promising for broadband wireless access technique.

Cochannel interference and multipath propagation reduce the performance of mobile communication systems. Multi-input MLSE with whitening processing can mitigate the influence of the interference and provide path diversity gain. In conventional considerations, however, the required complexity rapidly rises with the number of array elements. In this paper, we propose multi-input MLSE that whitens error signals in the signal space by using a multibeam adaptive array. This scheme can reduce the computational load of multi-input MLSE than the conventional type when using a large-element array. The results of an analysis show that the proposed type is equivalent to conventional one in the sense of the metric and provides less computational complexity.

In this paper, we propose a blind adaptive channel identification and equalization algorithm with phase offset compensation for single-input multiple-output (SIMO) channel. It is based on the one-step forward multichannel linear prediction error method and can be implemented by an RLS algorithm. Phase offset problem is inherent part of any second-order statistics-based blind identification and equalization. To solve this problem, we use a blind adaptive algorithm called the constant modulus derotator (CMD) algorithm based on constant modulus algorithm (CMA). Moreover, unlike many known subspace (SS) methods or cross relation (CR) methods, our proposed algorithms do not require channel order estimation. Therefore, our algorithms are robust to channel order mismatch.

In this paper, we discuss crosstalk equalization technique for high-speed digital transmission systems. This equalization technique makes use of the cyclostationarity of the crosstalk interferer. We first analyze the eigenstructure of the equalizer in the presence of cyclostationary crosstalk interference. It is shown that the eigenvalues of the equalizer depend upon the folded signal and interferer power spectra, and the cross power spectrum between the signal and the interferer. The expressions of the minimum mean square error (MMSE) and the excess MSE are then obtained by using the equalizer's eigenstructure. Analysis and simulation results indicate that such peculiar equalizer's eigenstructure in the presence of cyclostationary interference results in significantly different initial convergence and steady-state behaviors as compared with the stationary noise case. We also show that the performance of the equalizer varies depending on the relative clock phase of the symbol clocks used by the signal and the crosstalk interferer.

The problem of separating blindly independent sources from a convolutive mixture cannot be addressed in its widest generality without resorting to statistics of order higher than two. The core of the problem is in fact to identify the paraunitary part of the mixture, which is addressed in this paper. With this goal, a family of statistical contrast is first defined. Then it is shown that the problem reduces to a Partial Approximate Joint Diagonalization (PAJOD) of several cumulant matrices. Then, a numerical algorithm is devised, which works block-wise, and sweeps all the output pairs. Computer simulations show the good behavior of the algorithm in terms of Symbol Error Rates, even on very short data blocks.

This paper considers a link of two problems; multichannel blind deconvolution and multichannel blind identification of linear time-invariant dynamic systems. To solve these problems, cumulant maximization has been proposed for blind deconvolution, while cumulant matching has been utilized for blind identification. They have been independently developed. In this paper, a cumulant maximization criterion for multichannel blind deconvolution is shown to be equivalent to a least-squares cumulant matching criterion after multichannel prewhitening of channel outputs. This equivalence provides us with a new link between a cumulant maximization criterion for blind deconvolution and a cumulant matching criterion for blind identification.

In a wireless OFDM-CDMA system, the data-modulated symbol of each user is spread over multiple subcarriers in the frequency domain using a given spreading code. For the downlink (base-to-mobile) transmissions, a set of orthogonal spreading codes defined in the frequency domain is used so that different users data can be transmitted using the same set of subcarriers. The frequency selectivity of the radio channel produces the orthogonality destruction. There are several frequency equalization combining techniques to restore orthogonality, i.e., orthogonal restoration combining (ORC), control equalization combining (CEC) that is a variant of ORC, threshold detection combining (TDC), and minimum mean square error combining (MMSEC). The ORC can restore orthogonality among users but produces noise enhancement. However, CEC, TDC, and MMSEC can balance the orthogonality restoration and the noise enhancement. In this paper, we investigate, by means of computer simulation, how the BER performances achievable with ORC, CEC, TDC, and MMSEC are impacted by the propagation parameters (path time delay difference and fading maximum Doppler frequency), number of users, pilot power used for channel estimation, and channel estimation scheme. To acquire a good understanding of ORC, CEC, TDC, and MMSEC, how they differ with respect to the combining weights is discussed. Also, the downlink transmission performances of DS-CDMA and OFDM-CDMA are compared when the same transmission bandwidth is used. How much better performance is achieved with OFDM-CDMA than with DS-CDMA using ideal rake combining is discussed.

In OFDM-CDMA down link (base-to-mobile) transmissions, each user's transmit data symbol is spread over a number of orthogonal sub-carriers using an orthogonal spreading sequence defined in the frequency-domain. The radio propagation channel is characterized by a frequency- and time-selective multipath fading channel (which is called a doubly selective multipath fading channel in this paper). Frequency-domain equalization is necessary at the receiver to restore orthogonality among different users. This requires accurate estimation of the time varying transfer function of the multipath channel. Furthermore, the noise enhancement due to orthogonality restoration degrades transmission performance. In this paper, pilot-aided threshold detection combining (TDC) is presented that can effectively suppress the noise enhancement. If the estimated channel gain is smaller than the detection threshold, it is replaced with the detection threshold in the frequency equalization. There exists an optimal threshold that can minimize the bit error rate (BER) for a given received Eb/N0. The average BER performance of OFDM-CDMA down link transmissions using the TDC is evaluated by computer simulations. It is found that TDC using optimum detection threshold can significantly reduce the BER floor and outperforms DS-CDMA with ideal rake combining.

In this paper, a new approach is proposed to improve the channel estimation accuracy with channel tracking capability for adaptive multicarrier equalization systems under time-variant multipath fading channel. The improvement is carried out based on the assumption that the channel is static over a transmitted block period, and slowly linearly changing over several block periods. By applying IFFT to the concatenated channel transfer function derived from different blocks, the noise-averaging improvement is achieved, and a better estimation of the channel coefficients with some delay can be obtained. A multi-step channel predictor and a smoothing filter is utilized to compensate for the delay and make the system more robust in terms of channel tracking performance. Adaptive time domain equalization is jointly performed with this approach to avoid the channel invertibility problem found in the frequency domain approach. A short period of training sequences is utilized resulting in more efficient use of available communication capacity. The effectiveness of the proposed approach is evaluated through simulation for multicarrier systems in time-variant multipath fading channels. Results show improvement over previous channel estimation schemes.

A number of schemes have been proposed for communication using chaos over the past years. Regardless of the exact modulation method used, the transmitted signal must go through a physical channel which undesirably introduces distortion to the signal and adds noise to it. The problem is particularly serious when coherent-based demodulation is used because the necessary process of chaos synchronization is difficult to implement in practice. This paper addresses the channel distortion problem and proposes a technique for channel equalization in chaos-based communication systems. The proposed equalization is realized by a modified recurrent neural network (RNN) incorporating a specific training (equalizing) algorithm. Computer simulations are used to demonstrate the performance of the proposed equalizer in chaos-based communication systems. The Henon map and Chua's circuit are used to generate chaotic signals. It is shown that the proposed RNN-based equalizer outperforms conventional equalizers.

The starting point of this paper is the definition of a nonlinear model of the read out process in high density optical discs. Under high density condition, the signal read out is not a linear process, and suffers also from cross talk. To cope with these problems, the identification of a suitable nonlinear model is required. A physical model based on the optical scalar theory is used to identify the kernels of a nonlinear model based on the Volterra series. Both analysis and simulations show that a second order bidimensional model accurately describes the read out process. Once equipped with the Volterra channel model, we evaluate the performance of various nonlinear receivers. First we consider Nonlinear Adaptive Volterra Equalization (NAVE). Simulations show that the performance of classical structures for linear channels is significantly affected by the nonlinear response. The nonlinear NAVE receiver can achieve better performance than Maximum Likelihood Sequence Estimator (MLSE), with lower complexity. An innovative Nonlinear Maximum Likelihood Sequence Estimator (NMLSE), based on the combination of MLSE and nonlinear Inter-Symbol Interference (ISI) cancellation, is presented. NMLSE offers significant advantages with respect to traditional MLSE, and performs better than traditional equalization for nonlinear channels (like NAVE). Finally, the paper deals with cancellation of cross talk from adjacent tracks. We propose and analyze an adaptive nonlinear cross talk canceller based on a three spot detection system. For the sake of simplicity, all the performance comparisons presented in this paper are based on the assumption that noise is Additive, White, and Gaussian (AWGN model).

We propose using a soft decision-directed least-mean-square algorithm in a code-aided equalization scheme for fading channels. Soft-output Viterbi algorithm (SOVA) is modified and applied to strengthen the second-stage equalizer adaptation in the scheme. Simulation results are presented for bit error rate performance in a multipath environment for various normalized fade rates. The proposed equalizer scheme is shown to provide significant bit error rate improvement compared to conventional equalization schemes.

We propose a new receiver structure to mitigate interpath interference (IPI) in W-CDMA systems. We model IPI in RAKE combining as intersymbol interference (ISI) and use a two-stage receiver structure. The first stage is a RAKE receiver and the second stage is an equalizer. In cases of multi-code transmission, interference among code channels causes extra impairments which can not be modelled as ISI. Under these circumstances, they are estimated by using decisions from the first stage and then subtracted from the input of the equalizer. The residual interference is equivalent to ISI and can be mitigated by the equalizer. Simulation results show that the proposed receiver provides very promising performance in low spreading factor W-CDMA.

We consider equalizer initialization problems when the transmitted symbol rate is higher than the available channel bandwidth. In this case, the coefficients of an adaptive equalizer in the receiver can be updated only once per a predefined symbol period, requiring unacceptably long training time. The training time can be reduced significantly if the equalizer begins the training process from a properly initialized condition. In this letter, a fast initialization method is analytically designed for a minimum mean squared error (MMSE) type equalizer. Finally, the initialization performance is verified by computer simulation.