This concise paper determines the required laser power to achieve a given probability of bit error using a pulse-interval modulation (PIM) (discrete pulse position modulation) system with resolution much smaller than a laser pulsewidth. An approximation to the first crossing density for a threshold detector operating on a filtered Poisson process is used. Both analytic and computer simulation results are presented.

This correspondence evaluates the performance of the maximum likelihood (ML) and several suboptimal arrival time estimators for optical pulses. The performance analysis of a "sliding window" counter followed by a threshold detector is achieved by deriving an expression for the first-crossing density of the output of the counter.

Expressions are obtained for the probability of error of a binary intensity-modulated direct-detection optical communication system consisting of an ideal photodetector followed by a nonideal photoelectron counter, in this case anRClow-pass filter. Calculation of probability of error requires the determination of the output statistics of the nonideal counter. Numerical techniques are used to evaluate the expression for probability of error and optimum thresholds as a function of signal level. The optimum filter bandwidth required to simulate an ideal counter is also evaluated numerically. Results indicate that, for the particular case considered, the nonideal receiver requires an additional 1 dB of signal power to achieve performance equivalent to the ideal receiver.

Digital baseband and digital subcarrier noncoherent optical communication systems are considered in this paper. Expressions are developed for the bit error probability of optical subcarrier systems which use a nonliner polarization modulator and either a one-detector or a two-detector receiver, The expressions are evaluated numerically, and the results are used to compare the one- and two-detector subcarrier systems with the corresponding one- and two-detector baseband systems for a fLxed bit error probability.

The nonlinear interpolation problem is formulated in state variable form. Using the techniques of nonlinear filter theory, an exact solution is obtained in the sense that a partial differential equation for the evolution of the conditional probability density of the state vector at a fixed point in time is derived. The solution for the finite-dimensional-state space case is determined since it has considerable utility in digital implementations. A computer implementation was performed and the improvements obtained by interpolation over normal filtering techniques were evaluated for processing binary video telemetry data.