Multiple Importance Sampling for Efficient Symbol Error Rate Estimation

Importance sampling simulation for evaluating lower-bound symbol error rate of the Bayesian DFE with multilevel signaling schemes

For the class of equalizers that employs a symbol-decision finite-memory structure with decision feedback, the optimal solution is known to be the Bayesian decision feedback equalizer (DFE). The complexity of the Bayesian DFE, however, increases exponentially with the length of the channel impulse response (CIR) and the size of the symbol constellation. Conventional Monte Carlo simulation for e...

Minimum Symbol-Error-Rate Equalisation

The equalisation topic is well researched and a variety of solutions are available. The MAP sequence detector provides the lowest symbol error rate (SER) attainable, and the MLSE offers a near optimal solution. However, these optimal techniques are not yet practical for high-level modulation schemes, due to their computational complexity. Linear equaliser or linear-combiner DFE are practical sc...

Efficient importance sampling for ML estimation of SCD models

The evaluation of the likelihood function of the stochastic conditional duration model requires to compute an integral that has the dimension of the sample size. We apply the efficient importance sampling method for computing this integral. We compare EIS-based ML estimation with QML estimation based on the Kalman filter. We find that EIS-ML estimation is more precise statistically, at a cost o...

Symbol Rate Estimation for DVB-S2 Broadcasting

Fast Algorithm for Symbol Rate Estimation

The cyclic autocorrelation of common digital modulation is researched, and the relationship between the cyclic autocorrelation and the delay, corresponding to the symbol rate, is deduced, then a searching algorithm for the symbol rate is proposed. Theoretical analyses and simulation results show that this method has less computation complexity and is also quite accurate. The estimation result i...