The paper presents schemes for rapid on-line error probability estimation of digital communications links. Several estimator structures are proposed based on the assumption of sample independence, including weighted least squares (WLS) and maximum likelihood (ML) forms. The continuous-form ML estimator is shown to lie on the Rao-Cramer bound, making it a most efficient estimator of probability of error. The design, performance, implementation complexity and behavior of these estimators is described for AWGN.>

Maximum a posteriori (MAP) sequence estimation for channels with intersymbol interference (ISI) has previously required knowledge of the channel sampled impulse response (SIR). Generally the SIR coefficients are determined via least mean squares (LMS) or recursive least squares (RLS) estimation algorithms. For many unguided media channels such as mobile radio and high frequency (HF) radio exhibiting a time-varying SIR, these estimators must be adaptive. Often they fail to track adequately and are a major source of detector deterioration. A novel blind maximum likelihood sequence estimation (BMLSE) formulation without the need for external channel SIR estimation is proposed and implementation issues discussed. Its performance is simulated and compared to the contemporary technique, MLSE with external LMS channel estimation.>

A statistically based method of bit error rate (BER) which does not necessitate the transmission of test patterns or the interruption of data for measurement purposes is presented. It is demonstrated that the method allows accurate estimation of BER several orders of magnitude faster than the Monte Carlo method. Design of an optimal BER estimator based on the maximum-likelihood principle is proposed. The performance of the technique is demonstrated by simulations for the case of QPSK modulation in AWGN and for a live Rayleigh-fading HF link. The ability of the method to accurately predict BER using relatively few samples means that it is particularly suitable for high-speed BER estimation.>