Moment-Based Joint Estimation of Ricean K-Factor and SNR Over Linearly-Modulated Wireless SIMO Channels

Nondata-Aided Rician Parameters Estimation With Redundant GMM for Adaptive Modulation in Industrial Fading Channel

“…The Auto-Correlation Function (ACF) was adopted in [11] to avoid the data aided requirement, but it cannot be applied to M-ary Phase Shift Keying (M-PSK) due to the null ACF. The fourth-order cross moment statistic has been utilized in [13], [14] to avoid the aiding data, which can only work in the specified Single Input Multiple Output (SIMO) scenarios, i.e., not applicable in other common scenarios, especially the industrial scenario. In [15], an estimator of Rician factor is derived with constellation constrained GMM method, which waives the requirement of aiding pilot symbols but still needs prior information of modulation order.…”

“…In recent years, many efforts have been focused on the nondata aided Rician parameters estimation [11], [13], [14]. A state of the art work in [15] employs the Gaussian Mixture Model (GMM) to design a more general framework for the Rician parameter estimation with modulation interference.…”

The research on channel estimation and signal‐noise ratio estimation based on minimum error entropy kalman filter for single carrier frequency domain equalization system

“…Because the KF needs to estimate the channel noise, and the channel response coefficient needs to be known when the channel noise is estimated, the results of both can be made more accurate by iteration. At present, the commonly used SNR estimation methods mainly include maximum‐likelihood (ML) estimator for SNR, 22 second‐ and fourth‐order moments (M2M4) estimator, 23 higher order moment‐based SNR estimator, 24 and signal‐to‐variation ratio (SVR) estimator 25 . Quite a number of scholars have deduced and verified the effectiveness of the above SNR estimation method in many scenarios, but it is undeniable that no matter which scheme has a large amount of calculation, it is not suitable for engineering implementation.…”

Signal-to-noise ratio estimation for M-QAM signals in η−μand κ−μfading channels

“…The estimation of SNR by the MOM has been the considered technique, as shown, for example, in references [24,25] and more recently in reference [26] in which the transmitted signal is modeled by a complex Gaussian random variable with zero mean by component. In [27], the MOM is proposed in a process of joint estimation of both the K parameter of the Rice fading distribution and SNR in a SIMO communication system.…”