Search

This paper presents an algorithm to design jointly interpolation filters and decision feedback equalizers in the sense of minimum mean-square error such that the joint capacity which is neglected in conventional design is explored to improve the receiver performance. The algorithm comprises an iteration of two alternating simple quadratic minimizing operations and ensures convergence. A simulation example for the raised-cosine channel demonstrates that via this approach an improvement over the conventional design can be achieved. Index Terms--Alternating coordinates minimization algorithm, decision feedback equalizers, interpolation filters.

The identification of the model parameters of a high-density recording channel generally requires solution of nonlinear equations. In this paper, we apply the expectation and maximization (EM) algorithm to realize the maximum likelihood estimation of the parameters of a simple partial erasure model, including the reduction parameters and the isolated transition response. The algorithm that results from this approach iteratively solves two least-squares problems and, thus, realization is simple. Computer simulations verify the feasibility of the EM algorithm, and show that the proposed algorithm has fast convergence and the resulting estimator is asymptotically efficient. Index Terms--Expectation and maximization algorithm, least-squares methods, maximum-likelihood estimation, Monte Carlo methods, simple partial erasure model.

The modified discrete cosine transform/inverse modified discrete cosine transform (MDCT/IMDCT) algorithm is examined using a matrix representation.

The identification of model parameters of a high-density recording channel is usually difficult and complicated. In this paper, we successfully apply the alternating coordinates minimization (ACM) algorithm for estimating parameters of a partial erasure plus transition shift model (PETSM). The resulting algorithm turns out to iteratively solve two least square problems and is guaranteed to converge. Furthermore, the obtained model for a nonlinear partial response channel is more accurate than conventional models such that the maximum likelihood (ML) detector has better bit error rate (BER) performance without increasing its realization complexity. Computer simulations show that the ACM algorithm can accurately estimate the model parameters and the BER for the detector is significantly improved especially when the transition shift parameter is large. Index Terms--Alternating coordinates minimization, maximum likelihood detector, partial erasure ratio, partial response channel, transition shift parameter.