Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes an extended Kalman filter (EKF)-based and training symbol aided carrier frequency offset (CFO) estimation scheme for the uplink OFDM systems. Typically, in EKF-based estimation scheme, the measurement equation is a function of the CFO and channel coefficients. Therefore, a vector EKF has to be employed to estimate all the unknowns, which may sometime result in convergence problems. To avoid these problems, the proposed scheme uses a scalar EKF. The user signals are first separated by using multiple-access interference cancellation. Then, the unknown channel coefficients in the measurement equation are replaced with a non-linear function of the CFO so that the scalar EKF can be employed. The observation noise por is analyzed and its approximation is used in the EKF algorithm. Several numerical examples are presented to validate the efficacy of the proposed scheme. It is shown that the proposed scheme can achieve the Cramer-Rao lor bound (CRLB) when the number of users is small, whereas it degrades when the number of users increases.  also compare its computational complexity with several existing schemes.
['Xiang Nian', 'Ali Ghrayeb']
I am writing a research paper on a idea A Carrier Frequency Offset Estimation Scheme Based on a Scalar Extended Kalman Filter for Uplink OFDM Systems
[{"from": "human", "value": "I am writing a research paper on a idea A Carrier Frequency Offset Estimation Scheme Based on a Scalar Extended Kalman Filter for Uplink OFDM Systems"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes an extended Kalman filter (EKF)-based and training symbol aided carrier frequency offset (CFO) estimation scheme for the uplink OFDM systems. Typically, in EKF-based estimation scheme, the measurement equation is a function of the CFO and channel coefficients. Therefore, a vector EKF has to be employed to estimate all the unknowns, which may sometime result in convergence problems. To avoid these problems, the proposed scheme uses a scalar EKF. The user signals are first separated by using multiple-access interference cancellation. Then, the unknown channel coefficients in the measurement equation are replaced with a non-linear function of the CFO so that the scalar EKF can be employed. The observation noise por is analyzed and its approximation is used in the EKF algorithm. Several numerical examples are presented to validate the efficacy of the proposed scheme. It is shown that the proposed scheme can achieve the Cramer-Rao lor bound (CRLB) when the number of users is small, whereas it degrades when the number of users increases.  also compare its computational complexity with several existing schemes."}]