Compressive Sensing Based Time Domain Synchronous OFDM Transmission for Vehicular Communications

Time domain synchronous OFDM (TDS-OFDM) has higher spectral efficiency and faster synchronization than standard cyclic prefix OFDM (CP-OFDM), but suffers from the difficulty of supporting 256QAM in low-speed vehicular channels with long delay spread and the performance loss over fast time-varying vehicular channels. This paper addresses how to efficiently use the compressive sensing (CS) theory to solve those problems. First, we break through the conventional concept of cancelling the interferences if present, and propose the idea of using the inter-block-interference (IBI)-free region of small size to reconstruct the high-dimensional sparse multipath channel, whereby no interference cancellation is required any more. In this way, without changing the current signal structure of TDS-OFDM at the transmitter, the mutually conditional time-domain channel estimation and frequency-domain data detection in conventional TDS-OFDM receivers can be decoupled. Second, we propose the parameterized channel estimation method based on priori aided compressive sampling matching pursuit (PA-CoSaMP) algorithm to achieve reliable performance over vehicular channels, whereby partial channel priori available in TDS-OFDM is used to improve the performance and reduce the complexity of the classical CoSaMP signal recovery algorithm. Simulation results demonstrate that the proposed scheme can support the 256QAM and gain improved performance over fast fading channels.