70 research outputs found

    CRLB Based Optimal Noise Enhanced Parameter Estimation Using Quantized Observations

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    Cataloged from PDF version of article.In this letter, optimal additive noise is characterized for parameter estimation based on quantized observations. First, optimal probability distribution of noise that should be added to observations is formulated in terms of a Cramer–Rao lower bound (CRLB) minimization problem. Then, it is proven that optimal additive “noise” can be represented by a constant signal level, which means that randomization of additive signal levels is not needed for CRLB minimization. In addition, the results are extended to the cases in which there exists prior information about the unknown parameter and the aim is to minimize the Bayesian CRLB (BCRLB). Finally, a numerical example is presented to explain the theoretical results

    Stochastic signaling in the presence of channel state information uncertainty

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    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 stochastic signaling for power-constrained binary communications systems

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    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

    Convexity Properties of Detection Probability Under Additive Gaussian Noise: Optimal Signaling and Jamming Strategies

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    Cataloged from PDF version of article.In this correspondence, we study the convexity properties for the problem of detecting the presence of a signal emitted from a power constrained transmitter in the presence of additive Gaussian noise under the Neyman-Pearson (NP) framework. It is proved that the detection probability corresponding to the α-level likelihood ratio test (LRT) is either strictly concave or has two inflection points such that the function is strictly concave, strictly convex, and finally strictly concave with respect to increasing values of the signal power. In addition, the analysis is extended from scalar observations to multidimensional colored Gaussian noise corrupted signals. Based on the convexity results, optimal and near-optimal time sharing strategies are proposed for average/peak power constrained transmitters and jammers. Numerical methods with global convergence are also provided to obtain the parameters for the proposed strategies. © 1991-2012 IEE

    Optimal Stochastic Parameter Design for Estimation Problems

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    Cataloged from PDF version of article.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

    Optimal Randomization of Signal Constellations on Downlink of a Multiuser DS-CDMA System

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    Cataloged from PDF version of article.In this study, the jointly optimal power control with signal constellation randomization is proposed for the downlink of a multiuser communications system. Unlike a conventional system in which a fixed signal constellation is employed for all the bits of a user (for given channel conditions and noise power), power control with signal constellation randomization involves randomization/time- sharing among different signal constellations for each user. A formulation is obtained for the problem of optimal power control with signal constellation randomization, and it is shown that the optimal solution can be represented by a randomization among (K+1) or fewer distinct signal constellations for each user, where K denotes the number of users. In addition to the original nonconvex formulation, an approximate solution based on convex relaxation is derived. Then, detailed performance analysis is presented when the receivers employ symmetric signaling and sign detectors. Specifically, the maximum asymptotical improvement ratio is shown to be equal to the number of users, and the conditions under which the maximum and minimum asymptotical improvement ratios are achieved are derived. Numerical examples are presented to investigate the theoretical results, and to illustrate performance improvements achieved via the proposed approach. © 2002-2012 IEEE

    A Bayesian approach to respiration rate estimation via pulse-based ultra-wideband signals

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    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. © 2009 IEEE

    Dual functionality of conjugated polymer nanoparticles as an anticancer drug carrier and a fluorescent probe for cell imaging

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    Cataloged from PDF version of article.Multifunctional nanoparticles based on a green emitting, hydrophobic conjugated polymer, poly[(9,9-bis{propeny}fluorenyl-2,7-diyl)-co-(1,4- benzo-{2,1,3}-thiodiazole)] (PPFBT), that acts both as a fluorescent reporter and a matrix to accommodate an anti-cancer compound, camptothecin (CPT), were prepared, characterized and their potential as a fluorescent probe for cell imaging and as a drug delivery vehicle were evaluated via in vitro cell assays. The cell viability of human hepatocellular carcinoma cell line (Huh7) was investigated in the absence and presence of CPT with sulforhodamine B (SRB) and real-time cell electronic sensing (RT-CES) cytotoxicity assays

    Stochastic signal design on the downlink of a multiuser communications system

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    Stochastic signal design is studied for the downlink of a multiuser communications system. First, a formulation is proposed for the joint design of optimal stochastic signals. Then, an approximate formulation, which can get arbitrarily close to the optimal solution, is obtained based on convex relaxation. In addition, when the receivers employ symmetric signaling and sign detectors, it is shown that the maximum asymptotical improvement ratio is equal to the number of users, and the conditions under which that maximum asymptotical improvement ratio is achieved are presented. Numerical examples are provided to explain the theoretical results. © 2012 IEEE

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

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    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
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