Low complexity decoding schemes are presented for combined space time block coding and V-BLAST options in Enhanced Wireless Consortium draft for IEEE 802.11n. the authors exploit the structure of the transmitted data in developing the schemes. They are introduced for a frequency flat fading scenario and the diversity orders they yield are analyzed. The techniques are extended to orthogonal frequency division multiplexing mode of baseband modulation, and the impact of spatial correlation among the antennas is studied. Simulations are used to validate the predicted performance of the proposed schemes, predicted from the diversity order analysis. Also, their performance is compared with that of zero forcing successive interference cancellation (ZF-SIC). Computational complexities of the proposed as well as that of ZF-SIC are evaluated. The results show that one of the proposed schemes performs like ZF-SIC while its computational complexity is about one-half of that of ZF-SIC. Simulations with TGn channels, which are frequency selective channels and have spatial correlation, show that the performance degrades with increasing correlation.

We propose a novel algorithm for the maximum-likelihood sequence estimation (MLSE) equalizer for the Global System for Mobile Communications (GSM) system. Specifically, we use a parametric model for the channel, along with a modified phase pulse-shaping function of Gaussian minimum shift keying (GMSK) modulation to obtain the modified Viterbi equalizer which we refer to as the parametric channel-Viterbi equalizer (PC-VE). In contrast to the conventional Viterbi equalizer with a finite impulse response (FIR) channel description, the PC-VE avoids the linear approximation error. The PC-VE also has a lower computational complexity if the number of the propagation paths is less than the number of the FIR channel taps multiplied by the number of antennas. The proposed algorithm is applicable to both single and multiantenna receivers. An analytical expression for the BER as a function of the SNR, path delays, and path DOAs has been derived. Some simulation results that illustrate the performance of the proposed algorithm are presented.

Recently, a number of classes of multipath channels which are not blindly identifiable from fractionally spaced samples and second-order cyclic spectra have been presented. In this paper, we consider the blind identification problem of these channels using multiple antennas and show that they will not in general give rise to any common roots among the sub-channels formed from the antennas, and hence, they can be identified from second-order statistics.

Following the information theoretic approach to model selection, criteria for detecting the number of sinusoids are developed. The criteria are well matched to singular-value-decomposition (SVD-) based methods of spectral estimation in that the additional computations required over and above those needed for the SVD calculation are marginal. The detection performance of these criteria is compared with that of the J.J Fuchs (1988) method. The results show that the minimum description length (MDL)-based criterion, developed in the paper, and the Fuchs method perform similarly. However, the latter method involves substantially more computations than the former.>

In this paper, we present a novel method for generating a set of Hadamard matrices from a single set of four sequences, where one sequence forms the root sequence and the remaining three sequences can be generated easily from this root sequence. Further, the root sequence can be generated recursively. As an interesting by-product, the above procedure has lead to the construction of a set of constant-minimum distance code dictionaries of different block lengths.

We propose the application of modified recursive least-squares algorithms and least-squares lattice algorithms to echo cancellation problems to provide fast convergence and overcome the effects of the double-talking. The modified algorithms run continuously, but the gain updates become negligibly small during the double-talking intervals. Thus, detection of the double-talking and virtual freezing of the adaptive filter weights are both built into the algorithm. Simulations are used to verify the performance of the proposed algorithms, And the results confirm the theoretical predictions. A comparison of performances of different algorithms applied to real speech signals is also given in the paper.

This short paper presents a performance comparison of several recently proposed spectral estimation methods for short data lengths. The performance measures used are bias and variance of the estimate as obtained in simulations. The results show that the forward and backward prediction method is better than the forward prediction method, and Ulrych and Clayton's method [11 appears to perform better than Cadzow's ARMA technique [ Z ] . A modified form of Ulrych and Clayton's method, which exploits the symmetry in the AR coeffiecients that exists in the special case of sinusoids, is proposed and its performance is evaluated.

In this paper, an attempt is made to analyze the fixed point error performance of the normalized ladder algorithm for autoregressive system identification, assuming rounding arithmetic. The paper contains two main results; i) A simplified theoretical expression for predicting the average bias in the estimated reflection coefficients at any stage, and ii) a recursive relation for the average error, arising from finite precision arithmetic, in the squared residuals. The second result illustrates how the errors made in one stage affect the errors in the succeeding stages. Simulations are performed to check the theorical predictions.

While deriving rectangular transforms Agarwal and cooley have used polynomial factors with real integer coefficients which resulted in real convolution matrices. In this paper, it is shown that the use of polynomial factors with complex integer coefficients yields new algorithms with complex convolution matrices, which require less number of multiplications than rectangular transforms. The paper outlines the derivation of the new algorithms and presents the convolution matrices for N = 4,5,7,8 and 9. The results show that the new approach yields smaller theoretical minimum number of multiplications for N = 4 and 8, and the corresponding algorithms are optimum. In view of the simplest factors used in deriving the algorithms for N = 5,7 and 9, it is believed that the corresponding algorithms are the best among those which achieve the theoretical minimum number of multiplications. The matrices have been verified to satisfy the necessary and sufficient condition derived by Agarwal and Cooley.

A technique based on the partitioning of the impulse response is proposed to overcome the length restriction and the overflow problem that are encountered when Fermat number transforms are used to implement digital convolutions. Two different schemes are proposed to implement this method which require less hard-ware than that of two-dimensional technique. The method, when implemented on a general purpose computer, yields less number of arithmetic operations compared to two-dimensional approach. Further, the method offers more flexibility with regard to the length of the filter to be simulated.

This correspondence presents some results in fixed-point error analysis of fast Fourier transform algorithms. Two kinds of schemes for preventing overflow are considered in the analysis. The results, obtained for the decimation-in-frequency form of the algorithm, are compared with those of decimation-in-time. The results show that the error performance of the decimation-in-frequency algorithm is better than that of decimation-in-time.

An expression for the output noise-to-signal ratio is derived, taking into account the correlation between the truncation errors, when fast Fourier transform is computed in fixed-point arithmetic. A few assumptions, made in the analysis, are verified by computer simulations. The output noise-to-signal ratios predicted by the new expression and the old expression (which is derived under the assumption that the truncation errors are uncorrelated) are compared with the experimental results. It is shown that the predicted values based on the new results fall short of the experimental results by atmost 22%, while those predicted by the old results fall short by as much as 135.7%.