With the advent of the wireless broadband era, multicarrier technology such as orthogonal frequency division multiplexing (OFDM), and multiple transmit and receive antennas in the physical layer of communication systems appear to be favorable solutions to achieving higher data rates within the costly and scarce frequency spectrum. In communication systems, acquisition of the channel state information (CSI) via training is desirable to remove the distortions experienced by the subsequent information symbols. In this dissertation, the performance of OFDM systems is analyzed over a quasi-static fading channel where the channel is estimated through training and used for decoding. The expressions for bit-error probability (BEP) and pairwise error probability (PEP) for uncoded and coded OFDM systems, respectively, are obtained in the presence of equispaced and equipowered training and the loss of performance clue to training is quantified. It is observed from the novel training-based PEP expression that although the code design criteria along with the achievable diversity remain unchanged, there is a loss of coding gain due to channel estimation error (CEE). In order to mitigate the loss of performance attributed to CEE, a power allocation scheme that distributes the total power optimally between the training and data symbols is devised to minimize the BEP and PEP expressions, separately. The proposed optimal power allocation scheme performs between the equal power allocation and perfectly known channel cases, and converges to the latter when the number of subcarriers to the channel length ratio increases.; The analyses are also extended to multiple-input-multiple-output (MIMO) systems. In particular, under the optimal training scenario, the performances of space-time codes and orthogonal space-time block codes with linear decoding for MIMO systems in flat fading channels are analyzed. Also, space-time-frequency codes for MIMO-OFDM systems in frequency-selective fading channels in the presence of optimal training are considered. For all these MIMO systems, the expressions for optimal power allocation ratio and loss of performance due to training are obtained. Simulations and numerical examples are presented to further clarify and confirm our analytical findings.
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