Channel Estimation and Data Detection for Insufficient Cyclic Prefix MIMO-OFDM

In this paper, we propose an iterative structure for channel estimation and data detection for multiple-input-multiple-output orthogonal frequency-division multiplexing systems (MIMO-OFDM) with insufficient cyclic prefix (CP) and a limited number of pilot subcarriers. Insufficient CP leads to increased intersymbol interference (ISI) and intercarrier interference (ICI). The interference corrupts pilot subcarriers used for channel estimation and affects the detection process. We propose a multistep channel estimation process, which is assisted by a small number of pilot subcarriers. First, the channel covariance matrix and the number of channel paths are acquired from the channel least square estimates at the pilot subcarriers. We then formulate a maximum likelihood process to approximate the time-domain channel. For data detection, a high-performance bidirectional M-algorithm (BDMA) is proposed for trellis-based equalization. Simulation results show that the channel estimate mean square error converges to the Cramer-Rao bound (CRB) after a few iterations. In addition, the achieved bit error rate (BER) can reach that of the sufficient CP case, even when the delay spread is much longer than the CP.
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