Fractionally-sampled blind channel estimation for a mobile communication system
Mobility '08 Proceedings of the International Conference on Mobile Technology, Applications, and Systems
A Novel Technique for Channel Estimation and Equalization for High Mobility OFDM Systems
Wireless Personal Communications: An International Journal
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WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
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Proceedings of the International Conference and Workshop on Emerging Trends in Technology
Cyclic prefix based enhanced data recovery in OFDM
IEEE Transactions on Signal Processing
A frequency domain subspace blind channel estimation method for trailing zero OFDM systems
Journal of Network and Computer Applications
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MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume II
Semiblind channel estimation for IFDMA in case of channels with large delay spreads
EURASIP Journal on Advances in Signal Processing - Special issue on advances in single carrier block modulation with frequency domain processing
A novel subspace-based semi-blind channel estimation scheme for MIMO ZP-OFDM systems
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
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This paper proposes a new blind channel estimation method for orthogonal frequency division multiplexing (OFDM) systems. The algorithm makes use of the redundancy introduced by the cyclic prefix to identify the channel based on a subspace approach. Thus, the proposed method does not require any modification of the transmitter and applies to most existing OFDM systems. Semi-blind procedures taking advantage of training data are also proposed. These can be training symbols or pilot tones, the latter being used for solving the intrinsic indetermination of blind channel estimation. Identifiability results are provided, showing that in the (theoretical) situation where channel zeros are located on subcarriers, the algorithm does not ensure uniqueness of the channel estimation, unless the full noise subspace is considered. Simulations comparing the proposed method with a decision-directed channel estimator finally illustrates the performance of the proposed algorithm