When the transmitter of a communication system disposes of some Channel State Information (CSI), it is possible to design linear precoders that optimally allocate the power inducing high gains either in terms of capacity or in terms of reliable communications. In practical scenarios, this channel knowledge is not perfect and thus the transmitted signal suffers from the mismatch between the CSI at the transmitter and the real channel.
In that context, this thesis deals with two different, but related, topics: the design of a feasible transmitter channel tracker for time varying channels, and the design of optimal linear precoders robust to imperfect channel estimates.
The first part of the thesis proposes the design of a channel tracker that provides an accurate CSI at the transmitter by means of a low capacity feedback link. Historically, those schemes have been criticized because of the large amount of information to be transmitted from the receiver to the transmitter. This thesis focuses, thus, the attention in an accurate design of the return link. The proposed solution is based on the Kalman filter and follows a scheme that reminds the well known DPCM transmitter. The channel variability is processed by two identical linear predictors located at the transmitter and at the receiver, and a feedback link that assists the transmitter with the prediction error. The interest of this differential scheme is that allows to track the channel variations with only two or four bits per complex channel coefficient even in fast time-varying channels.
The rest of the thesis covers the second topic, studying different robust power allocation algorithms when the CSI is not perfectly known at the transmitter. For the sake of generality, the problem is formulated for the general MIMO OFDM case, encompassing the single antenna transmission, the beamforming schemes and the frequency-flat fading channels as particular cases.
First, the minimum MSE and the minimum uncoded BER parameters are chosen to be optimized, evaluating the performance of the algorithms in terms of uncoded BER. The basic novelty with respect to previous works that considers the same strategies of design is the proposal of a Bayesian approach for the design of the robust algorithms.
Next the study is extended by proposing robust power allocation strategies focused on the minimization of the coded BER. For this purpose, information-theoretic criteria are used. Probably, one of the main contributions in the thesis is the proposal of the cut-off rate as a parameter of design whose maximization is directly related to the coded BER. This criterion is introduced as an alternative to the channel capacity and the mutual information for the design of optimal transceivers in the presence of any channel coding stage.
The last part of the thesis proposes a low complexity adaptive interleaver that, making use of the CSI available at the transmitter, reallocates the bits not only to combat the bursty channel errors but also to combat the specific distribution of the faded subcarriers as a function of the channel response. The design of this interleaver, named as "RCPC interleaver", is based on the Rate-Compatible Punctured Convolutional Codes. As shown by numerical results, the use of this interleaver improves the performance of the algorithms when they are compared with the classical block interleavers and pseudo-random interleavers.