Compressive sensing based channel estimation for layered modulation OFDM scheme

Time-domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) is widely recognized as an orthogonal frequency division multiplexing (OFDM) transmission scheme with high spectral effciency. However, it suffers from severe performance loss over strong frequency selective channels, thus has difficulty supporting high-order modulations such as 256 QAM. To improve the channel estimation (CE) performance and support high-order modulation in TDS-OFDM system, we divide the OFDM block into several independent layers which are encoded and modulated separately. In the receiver, the pseudorandom noise (PN) sequence can give a coarse CE and then the low-order modulated symbols can be accurately decoded. By using the auxiliary information based subspace pursuit (A-SP) algorithm on the demodulated data, a precise CE can be given to support high-order modulated data's decoding. Simulations show that the proposed compressive sensing based channel estimation scheme performs well under different channels.

[1]  Jian Song,et al.  Novel Decision-Aided Channel Estimation for TDS-OFDM Systems , 2008, 2008 IEEE International Conference on Communications.

[2]  Xiaojun Yuan,et al.  Evolution analysis of low-cost iterative equalization in coded linear systems with cyclic prefixes , 2008, IEEE Journal on Selected Areas in Communications.

[3]  Xianbin Wang,et al.  Robust channel estimation and ISI cancellation for OFDM systems with suppressed features , 2005, IEEE Journal on Selected Areas in Communications.

[4]  Jian Song,et al.  Compressive Sensing Based Channel Estimation for OFDM Systems Under Long Delay Channels , 2014, IEEE Transactions on Broadcasting.

[5]  Chao Zhang,et al.  A Layered Modulation OFDM Scheme Using Differential Symbols as Pilots , 2010, 2010 IEEE 72nd Vehicular Technology Conference - Fall.

[6]  Zhigang Cao,et al.  Channel estimation for OFDM transmission in multipath fading channels based on parametric channel modeling , 2001, IEEE Trans. Commun..

[7]  Jun Wang,et al.  Iterative padding subtraction of the PN sequence for the TDS-OFDM over broadcast channels , 2005, IEEE Transactions on Consumer Electronics.

[8]  Georgios B. Giannakis,et al.  Cyclic prefixing or zero padding for wireless multicarrier transmissions? , 2002, IEEE Trans. Commun..

[9]  Jian Song,et al.  Technical Review on Chinese Digital Terrestrial Television Broadcasting Standard and Measurements on Some Working Modes , 2007, IEEE Transactions on Broadcasting.

[10]  Robert D. Nowak,et al.  Compressed Channel Sensing: A New Approach to Estimating Sparse Multipath Channels , 2010, Proceedings of the IEEE.

[11]  Donald C. Cox,et al.  Robust frequency and timing synchronization for OFDM , 1997, IEEE Trans. Commun..

[12]  Robert D. Nowak,et al.  Toeplitz Compressed Sensing Matrices With Applications to Sparse Channel Estimation , 2010, IEEE Transactions on Information Theory.

[13]  Shengli Zhou,et al.  Sparse channel estimation for multicarrier underwater acoustic communication: From subspace methods to compressed sensing , 2009, OCEANS 2009-EUROPE.

[14]  Alberto Morello,et al.  CD3-OFDM: a novel demodulation scheme for fixed and mobile receivers , 1996, IEEE Trans. Commun..

[15]  Jintao Wang,et al.  Novel channel estimation method based on PN sequence reconstruction for Chinese DTTB system , 2008, IEEE Transactions on Consumer Electronics.

[16]  Fumiyuki Adachi,et al.  New direction of broadband wireless technology , 2007, Wirel. Commun. Mob. Comput..

[17]  Linglong Dai,et al.  Time-Frequency Training OFDM with High Spectral Efficiency and Reliable Performance in High Speed Environments , 2012, IEEE Journal on Selected Areas in Communications.