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The decoupled coherent Maximum Likelihood (ML) detection algorithm presented in this letter can sharply reduce the complexity of the receiver as well as provide better error performance under the precondition that channel should be estimated first. Considering the bandwidth inefficiency of Frequency Shift Keying (FSK), the acquisition of channel state information through training sequences will further decrease the transmission efficiency. This letter presents a blind channel estimation algorithm based on noise subspace theory which can acquire channel information without any training symbols. The simulation shows that the algorithm brings about fewer channel estimation errors while the frequency efficiency can be increased.
The decoupled coherent Maximum Likelihood (ML) detection algorithm presented in this letter can sharply reduce the complexity of the receiver as well as provide better error performance under the precondition that channel should be estimated first. Considered the bandwidth inefficiency of Frequency Shift Keying (FSK) The acquisition of channel state information through training sequences will further decrease the transmission efficiency. This letter presents a blind channel estimation algorithm based on noise subspace theory which can acquire channel information without any training symbols. The simulation shows that the algorithm brings about fewer than channel estimation errors while the frequency efficiency can be increased.