Doubly-Selective Channel Estimation for MIMO-OFDM Systems with Experimental Verification

Abstract

Multiple-input multiple- output (MIMO) and orthogonal frequency division multiplexing (OFDM) are two key techniques for broadband wireless mobile communications and channel state information (CSI) is critical for the realization and performance of MIMO-OFDM systems in doubly-selective fading channels. Channel estimation based on two-dimensional discrete-time Fourier transform interpolation (2D-DFTI) is a promising solution to obtain accurate CSI for MIMO-OFDM systems in theory because of both its robustness and high computational efficiency, however, its performance will degrade significantly in practical MIMO-OFDM systems due to the two-dimensional Gibbs phenomenon caused by virtual subcarriers and burst transmission. In this paper, we propose a novel channel estimation method based on the two-dimensional enhanced DFT interpolation (2D-EDFTI), i.e., the frequency-domain EDFTI (FD-EDFTI) concatenated with the time-domain EDFTI (TD-EDFTI), for practical burst-mode MIMO-OFDM systems with virtual subcarriers, which can increase the channel estimation accuracy effectively by mitigating the Gibbs phenomenon in frequency-domain and time-domain, respectively, while keeping good robustness and high computational efficiency. In addition to computer simulations, we further implement the 2D-EDFTI channel estimator into our real-time FPGA testbed of 4 × 4 MIMO-OFDM transmission via spatial multiplexing, together with different MIMO detectors. Both computer simulations and RF experiments demonstrate the superior performance of 2D-EDFTI channel estimation in doubly-selective fading channels, therefore, high-throughput MIMO-OFDM transmission based on different MIMO detection algorithms can always be well supported. Also, it can be applied to other MIMO-OFDM transmission schemes straightforwardly.