Abstract :
The filters constituting the minimum mean square error decision-feedback equalizer (MMSE-DFE), as well as related performance measures, can be computed by assuming perfect knowledge of the channel impulse response and the input and noise second-order statistics (SOS). In practice, we estimate the unknown channel and SOS, and inevitable estimation errors arise. We model estimation errors as small perturbations, i.e., of order ε, with ε a sufficiently small positive number, and we study the behavior of the MMSE-DFE under mismatch by performing a first-order perturbation analysis. We prove that the excess MSE induced by O(ε) estimation errors is O(ε 2), uncovering important robustness properties associated with the MMSE-DFE
Keywords :
decision feedback equalisers; digital filters; error analysis; estimation theory; least mean squares methods; multipath channels; statistical analysis; transient response; SOS; channel estimation errors; channel impulse response; filters; finite-length MMSE-DFE; first-order perturbation analysis; minimum mean square error decision-feedback equalizer; robustness; second-order statistics; Additive noise; Computer errors; Decision feedback equalizers; Delay; Error analysis; Estimation error; Filters; Mean square error methods; Robustness; Statistics;
