In communication systems, the transmitted signals often experience various forms of corruption, and a very destructive one is the inter-symbol interference (ISI), resulting from the signals travelling through multiple paths and arriving with different delays. To compensate for the multipath propagation effect, equalization is often required at the receiver and as a very powerful candidate, the ...

We propose using Hidden Markov Models (HMMs) associated with the cepstrum coefficients as a speech signal model in order to perform equalization or noise removal. The MUlti-path Stochastic Equalization (MUSE) framework allows one to process data at the frame level: it is an on-line adaptation of the model. More precisely, we apply this technique to perform bias removal in the cepstral domain in...

There has been great interest in the design of filterbank transceivers. Usually, with proper time domain equalization, the channel is modeled as an FIR filter. It is known that for FIR channels, the introduction of certain redundancy allows the receiver to cancel intersymbol interference (ISI) completely, and channel equalization is performed implicitly using FIR transceivers. This scheme allow...

In this paper, we propose the pre-equalization technique for the uplink burst transmission under the intersymbol interference (ISI) channel and the rain attenuation channel existed in the Ka-Band (20~30GHz) of the B-WLL system. We compare the mean-square-error (MSE) convergence properties of standard leastmean-square (SLMS) and discrete cosine transform (DCT)-based transform-domain least-mean-s...

In this paper we present a simple efficient local unsupervised learning algorithm for on-line adaptive multichannel blind deconvolution and separation of i.i.d. sources. Under mild conditions, there exits a stable inverse system so that the source signals can be exactly recovered from their convolutive mixtures. Based on the existence of the inverse filter, we construct a two-stage neural netwo...

Faster-than-Nyquist signaling (FTNS) has emerged as a promising technique to increase communication capacity in bandwidth-limited channels. However, the presence of FTN-induced inter-symbol interference (FTN-ISI) received observations, is detrimental channel estimation (CE) and data detection terms computational complexity performance. This paper copes with these problems by incorporating linea...

An enhanced power-line communications channel estimation method in discrete multi-tone (DMT) communication system based on sparse Bayesian regression is presented. By exploiting a probabilistic Bayesian learning framework, the sparse model used provides an accurate model for channel estimation in presence of noise and consequently equalization. We consider frequency domain equalization (FEQ) us...

In this letter, we propose a computationally effient equalization technique that employs block minimum mean squared error (MMSE) depending on LDLH factorization. Parallel interference cancellation (PIC) is executed with preobtained output to provide more reliable symbol detection. In particular, the band structure of the frequency domain channel matrix is exploited to reduce the implementation ...

This paper proposes a new multiple-input multiple-output (MIMO) eigenmode transmission technique in frequency selective multipath channels. The proposed scheme exploits the two-dimensioned (spatial and path domain) signal separability in frequemcy selective MIMO channels, for which different data streams are transmitted on each path component’s eigenmodes. A soft interference canceling minimum ...

A loss of subchannel orthogonality due to timevariant multipath channels in orthogonal frequency-division multiplexing (OFDM) systems leads to interchannel interference (ICI) which increases the error floor in proportion to the Doppler frequency. In this paper, a simple frequency-domain equalization technique which can compensate for the effect of ICI in a multipath fading channel is proposed. ...