MIMO-OFDM channel estimation via probabilistic data association based TOAs

The multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) is one of the most promising techniques to achieve broadband wireless communications. Channel estimation is critical in the design of MIMO OFDM systems, since channel parameters are required for coherent detection and decoding. In this work, we propose a channel estimation scheme based on the time of arrivals (TOAs) estimation. The TOAs are first determined using a variant of probabilistic data association (PDA) and employing the minimum description length principle, then the PDA is augmented by group decision feedback to refine the TOA estimates. The proposed algorithm is compared with the Fourier transform based method and the alternating projection (AP) algorithm. Simulation results show that the proposed scheme provides the performance comparable to that of AP and much better than that of the Fourier based method, meanwhile it requires much lower computational cost than that of AP.

I. Introduction

The future wireless communications are characterized by broadband, high data rate capabilities, integration of services, and flexibility. The multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) is a promising technique to achieve these requirements, since OFDM is greatly resistant to the multipath introduced inter-symbol interference (ISI) and transmitter/receiver diversity is effective for combating fading. However, the enhancements in capacity, diversity, and coding gains depend on the availability of the underlying channel information at the receiver, since channel parameters are required for coherent detection and decoding. Without channel information, differential space-time coding (STC) or non-coherent detection has to be used at the expense of performance loss or extra power. Therefore, channel estimation is essential in OFDM system design.