Browsing by Subject "Theoretical result"

Now showing 1 - 10 of 10

Open Access
A Bayesian approach to respiration rate estimation via pulse-based ultra-wideband signals
(IEEE, 2009) Soǧancı, Hamza; Gezici, Sinan; Arıkan, Orhan
In this paper, theoretical limits on estimation of respiration rates via pulse-based ultra-wideband (UWB) signals are studied in the presence of prior information about respiration related signal parameters. First, a generalized Cramer-Rao lower bound (G-CRLB) expression is derived, and then simplified versions of the bound are obtained for sinusoidal displacement functions. In addition to the derivation of the theoretical limits, a two-step suboptimal estimator based on matched filter (correlation) processing and maximum a posteriori probability (MAP) estimation is proposed. It is shown that the proposed estimator performs very closely to the theoretical limits under certain conditions. Simulation results are presented to investigate the theoretical results.
Open Access
Convexity properties of outage probability under Rayleigh fading
(IEEE, 2012) Dülek, Berkan; Vanlı, N. Denizcan; Gezici, Sinan
In this paper, convexity properties of outage probability are investigated under Rayleigh fading for an average power-constrained communications system that employs maximal-ratio combining (MRC) at the receiver. By studying the first and second order derivatives of the outage probability with respect to the transmitted signal power, it is found out that the outage probability is a monotonically decreasing function with a single inflection point. This observation suggests the possibility of improving the outage performance via on-off type power randomization/sharing under stringent average transmit power constraints. It is shown that the results can also be extended to the selection combining (SC) technique in a straightforward manner. Finally, a numerical example is provided to illustrate the theoretical results. © 2012 IEEE.
Open Access
Effects of additional independent noise in binary composite hypothesis-testing problems
(IEEE, 2009-09) Bayram, Suat; Gezici, Sinan
Performance of some suboptimal detectors can be improved by adding independent noise to their observations. In this paper, the effects of adding independent noise to observations of a detector are investigated for binary composite hypothesistesting problems in a generalized Neyman-Pearson framework. Sufficient conditions are derived to determine when performance of a detector can or cannot be improved via additional independent noise. Also, upper and lower limits are derived on the performance of a detector in the presence of additional noise, and statistical characterization of optimal additional noise is provided. In addition, two optimization techniques are proposed to calculate the optimal additional noise. Finally, simulation results are presented to investigate the theoretical results. © 2009 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
Low-order controller design for haptic systems under delayed feedback
(2012) Liacu, B.; Koru, A. T.; Özbay, Hitay; Niculescu, S. -I.; Andriot, C.
In this paper, we consider PD controller design for haptic systems under delayed feedback. More precisely, we present a complete stability analysis of a haptic system where local dynamics are described by some second-order mechanical dynamics. Next, using two optimization techniques (H ∞ and stability margin optimization) we propose an optimal choice for the controller gains. The derived results are tested on a three degree of freedom real-time experimental platform to illustrate the theoretical results. © 2012 IFAC.
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 resonance in binary composite hypothesis-testing problems in the Neyman-Pearson framework
(Elsevier, 2012-02-20) Bayram, S.; Gezici, Sinan
Performance of some suboptimal detectors can be enhanced by adding independent noise to their inputs via the stochastic resonance (SR) effect. In this paper, the effects of SR are studied for binary composite hypothesis-testing problems. A Neyman-Pearson framework is considered, and the maximization of detection performance under a constraint on the maximum probability of false-alarm is studied. The detection performance is quantified in terms of the sum, the minimum, and the maximum of the detection probabilities corresponding to possible parameter values under the alternative hypothesis. Sufficient conditions under which detection performance can or cannot be improved are derived for each case. Also, statistical characterization of optimal additive noise is provided, and the resulting false-alarm probabilities and bounds on detection performance are investigated. In addition, optimization theoretic approaches to obtaining the probability distribution of optimal additive noise are discussed. Finally, a detection example is presented to investigate the 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.
Open Access
Time delay estimation in cognitive radio systems
(IEEE, 2009-12) Koçak, Fatih; Çelebi, H.; Gezici, Sinan; Qaraqe, K. A.; Arslan, H.; Poor, H. V.
In cognitive radio systems, secondary users can utilize multiple dispersed bands that are not used by primary users. In this paper, time delay estimation of signals that occupy multiple dispersed bands is studied. First, theoretical limits on time delay estimation are reviewed. Then, two-step time delay estimators that provide trade-offs between computational complexity and performance are investigated. In addition, asymptotic optimality properties of the two-step time delay estimators are discussed. Finally, simulation results are presented to explain the theoretical results. © 2009 IEEE.