Adaptive thresholding for free-space optical communication receivers with multiplicative noise

Abstract

In optical communication receivers with large multiplicative noise components, bit error rates (BER) can be improved by orders of magnitude by using a detection threshold based on a likelihood ratio test (LRT) instead of a matched filter type detector which assumes equal variances of the bit levels; however, the threshold development requires that the bit means and variances be known. In free-space communication systems, atmospheric conditions can cause large variations in optical transmission and subsequently in the bit level means and variances. An adaptive thresholding method has been developed which uses an LRT threshold for detection while tracking the bit means and variances with a Kalman filter algorithm that can be implemented with any number of samples per bit. Previous Kalman filter development, designed for slower data rates, required multiple samples per bit. The Kalman filter discussed in this paper requires only one sample per bit and is suitable for high-speed data links. The development of this Kalman filter routine are discussed. The results of simulations comparing BER performance of the adaptive LRT algorithm to the matched filter algorithm and to theoretical predictions are shown. Additional simulations compare the performance of the Kalman filter adaptive LRT with a maximum likelihood estimator for tracking means and variances.