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In this paper, we make use of a blind adaptive linear predictor for channel shortening in single input multiple output (SIMO) channels. We compare our approach to the so-called MERRY blind channel shortener. We assess through simulations that our proposed approach provides faster convergence rate and it better exploits the spatio-temporal diversity present in the SIMO channels.

In this work, we propose a novel structure and criterion for joint transmit diversity and multi-user downlink beamforming. The proposed structure can be seen as an extension of the purely spatial downlink beamforming and is a transformation that, for each user, transforms K real antennas into L virtual antennas, with L ≤ K. Classical transmit diversity is then applied to these virtual antennas. We propose a design criterion to optimize the precoders in order to find the best tradeoff between minimizing the interference generated towards the other users and maximizing the channel diversity for the desired user. This criterion is based on the minimization of the total transmit power subjected to a target BER constraint for each user. Applied to a multiple-antenna transmitter, the proposed technique outperforms the purely-spatial downlink beamformer by about 5 dB for a target BER of 10−2 and by 9 dB for 10−3 in a simple scenario.

This paper presents an adaptive equalization method based on the use of a watermark as reference signal. Instead of interrupting communication periodically to transmit training sequences, a watermark is transmitted continuously through the channel along with the user signal. By analyzing the received watermark, the equalization filter is continuously adapted to match the channel characteristics. When dealing with correlated user signals, a prediction-error filter is introduced to whiten the equalizer output before comparing it to the reference signal (the watermark), allowing for the appropriate inversion of the channel transfer function. Simulation results are presented to demonstrate the viability of this approach.

Crosstalk is one of the main limiting factors in the data rates achievable by digital subscriber line (DSL) systems, and several algorithms have been proposed to mitigate this impairment. In this paper, we compare the capacity of binders under different crosstalk-mitigating techniques. When computing capacity, we also compare two different power constraints: either on the total power in the binder or on the power in each pair. We will see that, for the scenarios considered in this paper, the fact that the signals are jointly processed in one or both ends of the DSL link leads to roughly the same performance, which is far superior to that of systems with no cooperation between the users. Both power constraints also lead to similar achievable rates.