'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
Cataloged from PDF version of article.Optimal stochastic signaling is studied under second
and fourth moment constraints for the detection of scalar-valued
binary signals in additive noise channels. Sufficient conditions
are obtained to specify when the use of stochastic signals
instead of deterministic ones can or cannot improve the error
performance of a given binary communications system. Also,
statistical characterization of optimal signals is presented, and it
is shown that an optimal stochastic signal can be represented by a
randomization of at most three different signal levels. In addition,
the power constraints achieved by optimal stochastic signals are
specified under various conditions. Furthermore, two approaches
for solving the optimal stochastic signaling problem are proposed;
one based on particle swarm optimization (PSO) and the other
based on convex relaxation of the original optimization problem.
Finally, simulations are performed to investigate the theoretical
results, and extensions of the results to -ary communications
systems and to other criteria than the average probability of
error are discussed
