Detection for binary transmission based on the empirical characteristic function

We present a new, suboptimum, method for the detection of signals in noise for which standard methods of inference are difficult to implement. The method is based on the empirical characteristic function (ECF) and exploits the correlation structure of the ECF evaluated at the finite number of points. We assume discrete time detection so that N i.i.d. data samples are available per symbol. We examine the performance of the proposed method for the mixture of α-stable and Gaussian noise. The detectors based on the ecf show substantial improvements in performance compared to linear detectors and exhibit better performance than the locally optimum (LO) detectors