Bandwidth Efficient Pilot Assisted Transmission over Doubly-Selective Wireless Fading Channels Using Superimposed Training

نویسنده

  • MOUNIR GHOGHO
چکیده

We propose to estimate time-varying frequency-selective channels using data-dependent superimposed training (DDST) and a basis expansion model (BEM). The superimposed training consists of the sum of a known sequence and a data-dependent sequence, which is unknown to the receiver. The data-dependent sequence cancels the effects of the unknown data on channel estimation. Symbol detection is performed using MMSE equalization. The method is compared to time-division-multiplexing-based methods. 0.

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تاریخ انتشار 2006