Priori-Information Hold Subspace Pursuit: A Compressive Sensing-Based Channel Estimation for Layer Modulated TDS-OFDM

Time-domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) has been widely recognized as a fundamental OFDM block transmission scheme because of its advantages in spectral efficiency. However, it suffers from severe performance loss under strong frequency selective channels and thus has difficulty supporting high-order modulations such as 256QAM. In this paper, we proposed a compressive sensing (CS)-based channel estimation (CE) algorithm for layer modulated TDS-OFDM (LM-TDS-OFDM). In the proposed CE algorithm, the low-order modulated symbols will be recovered and then sent to a feedback loop for precise CE. The priori-information hold subspace pursuit algorithm is investigated to achieve accurate estimation of channel. Analyses and simulations show that the proposed algorithm can successfully obtain high-accuracy CE and significantly reduce the computational complexity. Based on the proposed CE scheme, LM-TDS-OFDM can well support 256QAM transmission under severe channel conditions.

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