A combined stochastic/decision-aided SNR estimator
A problem of a blind stochastic SNR estimator and a principle of SNR estimation combining a blind estimator and decision-aided estimator are presented. Signal and noise can be detected from the received signal by a decision depending on a decision threshold that is made available by using the second and fourth-order moments of the received signal. Subsequently, the SNR is computed from the detected signal and the detected noise. The bias of SNR estimation (based on detection errors) is removed by applying analytically bias correction.
An SNR estimation algorithm using fourth-order moments
An algorithm is presented that allows an estimation of the SNR just by the observation of the noisy signal. For the estimation, shape factors of the signal's and the noise's probability density functions are used. The algorithm is based on the second and fourth order moments of the observed noisy signal.<<ETX>>
A digital transmission system using quaternary partial response CPM: principle structure and measurement results
The traditional drawbacks of continuous phase modulation (CPM) a high complexity decoder and difficult synchronization have been overcome by state reduction techniques and a suitable representation of the CPM signal by time-limited base functions. An implementation of quaternary partial response CPM schemes using this approach together with an extended synchronization strategy to combat frequency offsets is reported. Measurement results confirm simulation results, especially the predicted negligible loss due to application of reduced state sequence estimation algorithms. The proposed implementation leads to CPM schemes with complexity and efficiency comparable or even superior to trellis-coded PSK schemes.<<ETX>>