Compressive Sensing Based Channel Estimation for OFDM Systems Under Long Delay Channels
Time-domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) outperforms the classical cyclic prefix OFDM (CP-OFDM) in higher spectral efficiency and faster synchronization.However, it has the difficulty to support high-order modulations like 256QAM and suffers from performance loss especially under severely fading channels with long delays in the single frequency network environment,which may not accommodate the emerging ultra-high defmition television (UHDTV) service.To solve this problem, a channel estimation method for the time-frequency training OFDM (TFT-OFDM) is proposed under the framework of compressive sensing (CS) in this paper.Firstly, by exploiting the signal structure of TFT-OFDM, the auxiliary channel information is obtained.Secondly, we propose the auxiliary information based subspace pursuit (A-SP) algorithm to utilize a very few frequency-domain pilots embedded in the OFDM block for the exact channel impulse response estimation.Moreover, the obtained auxiliary channel information is adopted to reduce the complexity of the classical SP algorithm.Simulation results demonstrate that the CS-based TFT-OFDM outperforms the conventional dual pseudo noise padded OFDM and CS-based TDS-OFDM schemes in both static and mobile environments, especially when the channel length is close to or even exceeding the guard interval length, where the conventional schemes usually fail to work completely.
Orthogonal frequency division multiplexing (OFDM) time-frequency training (TFT) channel estimation (CE) compressive sensing (CS) long delays
Wenbo Ding Fang Yang Changyong Pan Linglong Dai Jian Song
IEEE
国内会议
广州
英文
494-503
2015-05-01（万方平台首次上网日期，不代表论文的发表时间）