This paper studies the comparative tracking performance of the recursive least squares (RLS) and least mean square (LMS) algorithms for time-varying inputs, specifically for linearly chirped narrowband input signals in additive white Gaussian noise. It is shown that the structural differences in the implementation of the LMS and RLS weight updates produce regions where the LMS performance excee...

Our society where communication through modern technology is prominent, seeking high speed voice, video and data in quantities that could not be imagined even a decade ago. The mobility and channel impairments have added more challenges. Multi Carrier Code Division Multiple Access (MC-CDMA) system is an attractive choice for high speed wireless communication as it avoids the problem of Inter Sy...

This paper proposes wavelet packets for use in ultra wideband communications. The pulse shapes that are generated are quasi orthogonal and have almost identical time duration. After normalization, an M-ary signaling set can be constructed allowing higher data rate. Finally, the performance of such a system when multipath propagation occurs is investigated by computer simulations. In order to co...

The digital Fourier transform (DFT) and the adaptive least mean square (LMS) algorithm have existed for some time. This paper establishes a connection between them. The result is the “LMS spectrum analyzer,” a new means for the calculation of the DFT. The method uses a set of N periodic complex phasors whose frequencies are equally spaced from dc to the sampling frequency. The phasors are weigh...

In this paper, a robust adaptive MMSE Rake-equalizer receiver scheme is presented with channel estimation that has been transmitted in Direct Sequence-Ultra Wideband (DS-UWB) system. The DS-UWB has a fine path resolution by transmitting information with ultra short pulses. The Rake receiver is known as a technique that can effectively combine paths with different delays and obtain the path dive...

This paper studies the mean and mean square convergence behaviors of the normalized least mean square (NLMS) algorithm with Gaussian inputs and additive white Gaussian noise. Using the Price’s theorem and the framework proposed by Bershad in IEEE Transactions on Acoustics, Speech, and Signal Processing (1986, 1987), new expressions for the excess mean square error, stability bound and decoupled...

Autoregressive (AR) modeling is widely used in signal processing. The coefficients of an AR model can be easily obtained with a least mean square (LMS) prediction error filter. However, it is known that this filter gives a biased solution when the input signal is corrupted by white Gaussian noise. Treichler suggested the -LMS algorithm to remedy this problem and proved that the mean weight vect...

This paper presents the least-mean-square (LMS) adaptive filter for deriving its Architectures for high-speed and low complexity implementation. Among many adaptive algorithms that exist in the open literature, the class of approaches which are derived from the minimization of the mean squared error between the output of the adaptive filter and some desired signal seems to be the most popular. ...

Three adaptive multichannel L-lters based on marginal data ordering are proposed. They rely on well-known algorithms for the iterative minimization of the mean square error (MSE), namely, the least mean squares (LMS), the normalized LMS (NLMS), and the LMS-Newton (LMSN) algorithms. We treat both the unconstrained minimization of the MSE and the minimization of the MSE when structural constraint...

This paper proposes an iterative maximum a posteriori probability (MAP) receiver for multiple-input-multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM) mobile communications. For exploiting the space, time, and frequency diversity, the lowdensity parity-check code (LDPC) is used as a channel coding with a builtin interleaver. The receiver employs the expectation maximiz...