Browsing by Subject "Signal level"

Now showing 1 - 5 of 5

Open Access
Average fisher information optimization for quantized measurements using additive independent noise
(IEEE, 2010) Balkan, Gokce Osman; Gezici, Sinan
Adding noise to nonlinear systems can enhance their performance. Additive noise benefits are observed also in parameter estimation problems based on quantized observations. In this study, the purpose is to find the optimal probability density function of additive noise, which is applied to observations before quantization, in those problems. First, optimal probability density function of noise is formulated in terms of an average Fisher information maximization problem. Then, it is proven that optimal additive "noise" can be represented by a constant signal level. This result, which means that randomization of additive signal levels is not needed for average Fisher information maximization, is supported with two numerical examples. ©2010 IEEE.
Open Access
Effects of channel state information uncertainty on the performance of stochastic signaling
(IEEE, 2011) Göken, Çağrı; Gezici, Sinan; Arıkan, Orhan
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.
Open Access
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.
Open Access
Optimal stochastic parameter design for estimation problems
(Institute of Electrical and Electronics Engineers, 2012) Soganci, H.; Gezici, Sinan; Arıkan, Orhan
In this study, the aim is to perform optimal stochastic parameter design in order to minimize the cost of a given estimator. Optimal probability distributions of signals corresponding to different parameters are obtained in the presence and absence of an average power constraint. It is shown that the optimal parameter design results in either a deterministic signal or a randomization between two different signal levels. In addition, sufficient conditions are obtained to specify the cases in which improvements over the deterministic parameter design can or cannot be achieved via the stochastic parameter design. Numerical examples are presented in order to provide illustrations of theoretical results.
Open Access
Stochastic signaling in the presence of channel state information uncertainty
(Elsevier, 2013) Goken, C.; Gezici, Sinan; Arıkan, Orhan
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.