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Browsing by Subject "Stochastic signals"

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    On the optimality of stochastic signaling under an average power constraint
    (IEEE, 2010-09-10) Göken, Çağrı; Gezici, Sinan; Arıkan, Orhan
    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.
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    Optimal channel switching in the presence of stochastic signaling
    (IEEE, 2013) Dulek, B.; Varshney P.K.; Tutay, Mehmet Emin; Gezici, Sinan
    Optimal channel switching and detector design is studied for M-ary communication systems in the presence of stochastic signaling, which facilitates randomization of signal values transmitted for each information symbol. Considering the presence of multiple additive noise channels (which can have non-Gaussian distributions in general) between a transmitter and a receiver, the joint optimization of the channel switching (timesharing) strategy, stochastic signals, and detectors is performed in order to achieve the minimum average probability of error. It is proved that the optimal solution to this problem corresponds to either (i) switching between at most two channels with deterministic signaling over each channel, or (ii) time-sharing between at most two different signals over a single channel (i.e., stochastic signaling over a single channel). For both cases, the optimal solutions are shown to employ corresponding maximum a posteriori probability (MAP) detectors at the receiver. Numerical results are presented to investigate the proposed approach. © 2013 IEEE.
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    Optimal stochastic signal design and detector randomization in the Neyman-Pearson framework
    (IEEE, 2012-03) Dülek, Berkan; Gezici, Sinan
    Power constrained on-off keying communications systems are investigated in the presence of stochastic signaling and detector randomization. The joint optimal design of decision rules, stochastic signals, and detector randomization factors is performed. It is shown that the solution to the most generic optimization problem that employs both stochastic signaling and detector randomization can be obtained as the randomization among no more than three Neyman-Pearson (NP) decision rules corresponding to three deterministic signal vectors. Numerical examples are also presented. © 2012 IEEE.
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    Stochastic signaling under second and fourth moment constraints
    (IEEE, 2010) Göken, Çağrı; Gezici, Sinan; Arıkan, Orhan
    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.

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