Experimental Demonstration of Compressive Sensing-Based Channel Estimation for MIMO-OFDM VLC

The combination of optical multiple inputs multiple outputs (MIMO) and orthogonal frequency division multiplexing (OFDM) is a viable option to overcome the bandwidth limitation and increase the transmission data rate in visible light communications (VLC). In MIMO-VLC systems with pre-coders and equalizers it is essential to know the perfect channel state information. Traditional channel estimation (CE) techniques such as least square (LS) are widely used in MIMO-VLC systems. However, the LS algorithm is subject to noise enhancement, which results in lower estimation accuracy. Besides, the pilot tones between different transmitters should be orthogonal either in time or frequency domains, which increase the overhead. Since the physical VLC channel model exhibits strong sparsity, we propose a CE method based on compressive sensing (CS) for MIMO-OFDM VLC systems. The feasibility of the proposed CS-CE method is verified by experimental demonstration of a 2\times 2 MIMO-OFDM VLC system. The experimental results show that, the proposed method offers improved bit error rate performance with reduced overhead compared with the LS-CE scheme.