Time domain synchronous OFDM based on compressive sensing: A new perspective

This paper exploits compressive sensing (CS) theory to solve the open problems of time domain synchronous OFDM (TDS-OFDM): the difficulty of supporting 256QAM in long-delay channels and the obvious performance loss over fast fading channels. First, we break through the conventional concept of cancelling the interferences if present in TDS-OFDM, and propose the idea of using the small-size inter-block-interference (IBI)-free region of the received training sequence to reconstruct the high-dimensional sparse multipath channel without any interference cancellation under the CS framework. This new perspective could decouple the mutually conditional time-domain channel estimation and frequency-domain data detection in conventional TDS-OFDM without changing its signal structure. Second, we propose the parameterized channel estimation method based on priori aided compressive sampling matching pursuit (PA-CoSaMP) algorithm, 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.