Adaptive channel equalization algorithms are commonly used in wireless communications receivers to counter intersymbol interference, multi-path dispersion, and other time varying channel degradations. In this paper we obtain approximate expressions for the increase in mean square error of the LMS adaptive algorithm when the total processing power is decreased by reducing the number of data and ...

Electronic equalizers, which have been used widely in wireless and wireline communications, have recently been recognized as effective solutions for mitigating the impairments in the optical communications channel as well. Now with the increasing availability of voltage-tunable integrated circuits for high speed operation, equalizers, in particular those based on the minimum mean-square error (...

Neural networks add a degree of flexibility to the design of equalizers for digital communications. In this work several decision-feedback (DF) neural equalizers (DFNE) are compared with classical DF equalizers and Viterbi demodulators. It is shown that the choice of a cost functional based on the Discriminative Learning (DL), coupled with a fast training paradigm, can provide neural equalizers...

Block based linear equalizers are used in communication systems for removing the effects of the channel degradation. Researchers have developed linear equalizers using different modulations techniques. This paper evaluates the BER performance of communication system for different over sampling factor of pulse shaping filters. The effect of the different number of transmitting blocks is also eva...

The widely-used LMS algorithm for coefficient updates in adaptive (feedforward/decision-feedback) equalizers is found to be suboptimal for ASE-dominant systems but various coefficient-dithering approaches suffer from slow adaptation rate without guarantee of convergence. In view of the non-Gaussian nature of optical noise after the square-law optoelectronic conversion, we propose to apply the h...

Neural receiver structures have been developed for adaptive discrete-signal detection in telecommunication applications. Neural networks combined with conventional equalizers improve the performance especially in compensating for nonlinear distortions. These distortions may result, for instance, from nonlinear ampliication implemented for reducing the power consumption. In this paper, the behav...

Mobile stations in high-tier Personal Communication Systems (PCS) are intended for high-mobility users and must thus operate in fast-changing environments. The first generation of high-tier PCS in North-America will be based on existing digital cellular standards including IS-I 36 TDMA. Moreover, dual-band receivers will be needed for extensive roaming. Adaptive equalizers were devised for IS-5...

In this contribution we present a new family of soft equalizers for multiple input multiple output (MIMO) systems with frequency selective fading. The proposed equalizers are based on soft successive interference cancellation (SIC) of both intersymbol interference (ISI) and multiple antenna interference (MAI), and are applicable to both single user MIMO systems with ISI and MIMO multipath chann...

In previous work, we have shown that in the case of multiple antennas and/or oversampling, FIR ZF equalizers exist for FIR channels and can be obtained from the noise-free linear prediction (LP) problem. The LP problem also lead to a minimal parameterization of the noise subspace, which was used to solve the deterministic maximum likelihood (DML) channel estimation problem. Here we present furt...