Optimal stochastic signaling for power-constrained binary communications systems

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

Stochastic signaling in the presence of channel state information uncertainty

Cataloged from PDF version of article.In this paper, stochastic signaling is studied for power-constrained scalar valued binary communications systems in the presence of uncertainties in channel state information (CSI). First, stochastic signaling based on the available imperfect channel coefficient at the transmitter is analyzed, and it is shown that optimal signals can be represented by a randomization between at most two distinct signal levels for each symbol. Then, performance of stochastic signaling and conventional deterministic signaling is compared for this scenario, and sufficient conditions are derived for improvability and nonimprovability of deterministic signaling via stochastic signaling in the presence of CSI uncertainty. Furthermore, under CSI uncertainty, two different stochastic signaling strategies, namely, robust stochastic signaling and stochastic signaling with averaging, are proposed. For the robust stochastic signaling problem, sufficient conditions are derived for reducing the problem to a simpler form. It is shown that the optimal signal for each symbol can be expressed as a randomization between at most two distinct signal values for stochastic signaling with averaging, as well as for robust stochastic signaling under certain conditions. Finally, two numerical examples are presented to explore the theoretical results. (C) 2012 Elsevier Inc. All rights reserve

Optimal Parameter Encoding Based on Worst Case Fisher Information under a Secrecy Constraint

In this letter, optimal deterministic encoding of a uniformly distributed scalar parameter is performed in the presence of an eavesdropper. The objective is to maximize the worst case Fisher information of the parameter at the intended receiver while keeping the mean-squared error (MSE) at the eavesdropper above a certain level. The eavesdropper is modeled to employ the linear minimum MSE estimator based on the encoded version of the parameter. First, the optimal encoding function is derived when there exist no secrecy constraints. Next, to obtain the solution of the problem in the presence of the secrecy constraint, the form of the encoding function that maximizes the MSE at the eavesdropper is explicitly derived for any given level of worst case Fisher information. Then, based on this result, a low-complexity algorithm is provided to calculate the optimal encoding function for the given secrecy constraint. Finally, numerical examples are presented. © 1994-2012 IEEE

On the optimality of stochastic signaling under an average power constraint

In this paper, stochastic signaling is studied for scalar valued binary communications systems over additive noise channels in the presence of an average power constraint. For a given decision rule at the receiver, the effects of using stochastic signals for each symbol instead of conventional deterministic signals are investigated. First, sufficient conditions are derived to determine the cases in which stochastic signaling can or cannot outperform the conventional signaling. Then, statistical characterization of the optimal signals is provided and it is obtained that an optimal stochastic signal can be represented by a randomization of at most two different signal levels for each symbol. In addition, via global optimization techniques, the solution of the generic optimal stochastic signaling problem is obtained, and theoretical results are investigated via numerical examples. ©2010 IEEE

Effects of channel state information uncertainty on the performance of stochastic signaling

In this paper, stochastic signaling is studied for power-constrained scalar valued binary communications systems in the presence of uncertainties in channel state information (CSI). First, it is shown that, for a given decision rule at the receiver, stochastic signaling based on the available CSI at the transmitter results in a randomization between at most two different signal levels for each symbol. Then, the performance of stochastic signaling and conventional deterministic signaling is compared, and sufficient conditions are derived for improvability and nonimprovability of deterministic signaling via stochastic signaling in the presence of CSI uncertainty. Finally a numerical example is presented to explore the theoretical results. © 2011 IEEE

Stochastic signaling under second and fourth moment constraints

Stochastic signaling is investigated under second and fourth moment constraints for the detection of scalar-valued binary signals in additive noise channels. Sufficient conditions are derived to determine when the use of stochastic signals instead of deterministic ones can or cannot enhance the error performance of a given binary communications system. Also, a convex relaxation approach is employed to obtain approximate solutions of the optimal stochastic signaling problem. Finally, numerical examples are presented, and extensions of the results to M-ary communications systems and to other criteria than the average probability of error are discussed

A survey on optimal stochastic signaling and detector randomization [Optimal stokastik i̇şaretleme ve sezici rasgeleleştirme üzerine bir derleme]

In this paper, a survey on stochastic signaling and detector randomization is presented for average power-constrained binary communications systems. First, the case of a single fixed detector at the receiver is considered, and then the joint design of detector and optimal signaling is studied. In addition, the optimal receiver design is examined in the presence of detector randomization and stochastic signaling. It is observed that the average probability of error achieved via detector randomization cannot be larger than that achieved via stochastic signaling in the presence of optimal MAP detectors. Finally, a numerical study is presented to illustrate an example. © 2011 IEEE