Training sequence optimization for frequency selective channels with MAP equalization
In this paper, we address the problem of optimization of the training sequence length for frequency selective channels when a maximum a posteriori (MAP) equalizer is used. The optimal length of the training sequence is found by maximizing an effective signal-to-noise ratio (SNR) and an effective channel capacity of the training-based transmission scheme. We study these problems of optimization when the training and data powers are equal and when they are allowed to be different. When the powers can be different, we give the optimal power allocation.