To eliminate the influence of the inconsistency on the cycle life and the available capacity of the battery pack, and improve the balancing speed, a novel inductor-based layered bidirectional equalizer (IBLBE) is proposed. The equalizer is composed of the bottom balancing circuits and the upper balancing circuits, and the two layer circuits both consist of a plurality of balancing sub-circuits,...

A new type of blind decision feedback equalizer (DFE) incorporating fixed lag smoothing is developed in this paper. The structure is motivated by the fact that if we make full use of the dependence of the observed data on a given transmitted symbol, delayed decisions may produce better estimates of that symbol. To this end, we use a hidden Markov model (HMM) suboptimal formulation that offers a...

In this report, we address M-QAM blind equalization by fitting the probability density functions (pdf) of the equalizer output with the constellation symbols. We propose two new cost functions, based on kernel pdf approximation, which force the pdf at the equalizer output to match the known constellation pdf. The kernel bandwidth of a Parzen estimator is updated during iterations to improve the...

Channel estimate based equalizers are those for which observations of the received signal are used to estimate the channel impulse response and possibly the statistics of the interfering noise field, and these estimates are used to calculate the equalizer filter coefficients. Channel estimate based decision feedback equalizers (CE-DFE), linear MMSE equalizers (L-MMSE), and Passive Time-Reversal...

The achievable bit error rate of a linear equalizer is crucially determined by the choice of a decision delay parameter. This brief paper presents a simple method for the efficient determination of the optimal decision delay parameter that results in the best bit error rate performance for a linear equalizer.

The relevance vector machine (RVM) technique is applied to communication channel equalization. It is demonstrated that the RVM equalizer can closely match the optimal performance of the Bayesian equalizer, with a much sparser kernel representation than that is achievable by the state-of-art support vector machine (SVM) technique.

We investigate a sub-optimal iterative receiver for joint equalization and decoding called Turbo-equalizer. We view the evolution of the error variance of the transmitted symbols through the iterative processing, obtaining convergence analysis. This allows us to predict the asymptotic performance (when the Turbo-equalizer has converged) but also the trigger point observed in its performance.

An adaptive reinitialization algorithm for the constant modulus algorithm is proposed that relies on the similarities between the constant modulus and the Wiener equalizer and expands the capabilities of a previous algorithm. The proposed algorithm determines adaptively if the CMA will benefit through reinitialization, and if so, it will calculate new equalizer coefficients leading to the globa...

We propose a computationally e cient version of the Decision Feedback Equalizer (DFE) and compare its performance with the conventional DFE. The proposed equalizer requires fewer taps than the conventional one. This reduces the computational load proportionally and leads to faster adaptation. Identical performance of the two structures in terms of probability of error is also demonstrated using...