Browsing by Subject "Gaussian channel"

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Open Access
Maximization of average number of correctly received symbols over multiple channels in the presence of idle periods
(Elsevier Inc., 2016) Keskin, M. F.; Kurt, M. N.; Tutay, M. E.; Gezici, Sinan; Arıkan, Orhan
In this study, optimal channel switching (time sharing) strategies are investigated under average power and cost constraints for maximizing the average number of correctly received symbols between a transmitter and a receiver that are connected via multiple flat-fading channels with additive Gaussian noise. The optimal strategy is shown to correspond to channel switching either among at most three different channels with full channel utilization (i.e., no idle periods), or between at most two different channels with partial channel utilization. Also, it is stated that the optimal solution must operate at the maximum average power and the maximum average cost, which facilitates low-complexity approaches for obtaining the optimal strategy. For two-channel strategies, an upper bound is derived, in terms of the parameters of the employed channels, on the ratio between the optimal power levels. In addition, theoretical results are derived for characterizing the optimal solution for channel switching between two channels, and for comparing performance of single channel strategies. Sufficient conditions that depend solely on the systems parameters are obtained for specifying when partial channel utilization cannot be optimal. Furthermore, the proposed optimal channel switching problem is investigated for logarithmic cost functions, and various theoretical results are obtained related to the optimal strategy. Numerical examples are presented to illustrate the validity of the theoretical results.
Open Access
Maximization of correct decision probability via channel switching over Rayleigh fading channels
(IEEE, 2016) Keskin, Musa Furkan; Kurt, Mehmet Necip; Tutay, Mehmet Emin; Gezici, Sinan; Arıkan, Orhan
In this study, optimal channel switching (time sharing) strategies are investigated under average power and cost constraints in order to maximize the average number of correctly received symbols between a transmitter and a receiver that are connected via multiple additive Gaussian noise channels. The optimal strategy is shown to perform channel switching either among at most three channels with full channel utilization (i.e., no idle periods), or between at most two channels with partial channel utilization. In addition, it is stated that the optimal solution must operate at the maximum average power and the maximum average cost, which facilitates low-complexity approaches for calculating the optimal strategy. For two-channel strategies, an upper bound in terms of the noise standard deviations of the employed channels is provided for the ratio between the optimal power levels. Furthermore, a simple condition depending solely on the systems parameters is derived, under which partial channel utilization cannot be optimal. Numerical examples are presented to demonstrate the validity of the theoretical results.
Open Access
Optimal time sharing strategies for parameter estimation and channel switching problems
(2014) Soğancı, Hamza
Time sharing (randomization) can offer considerable amount of performance improvement in various detection and estimation problems and communication systems. In the first three chapters of this dissertation, time sharing among different signal levels is considered for parametric estimation problems. In the final chapter, time sharing among different channels is investigated for an average power constrained communication system. In the first chapter, the aim is to improve the performance of a single fixed estimator by the optimal stochastic design of signal values corresponding to parameters. It is obtained that the optimal parameter design corresponds to time sharing between at most two different signal values. In the second chapter, the problem in the first chapter is generalized to a scenario where there are multiple parameters and multiple estimators. In this scenario, two different cost functions are considered. The first cost function is the total risk of all the estimators. The optimal solution for this case is time sharing between at most two different signal values. The second cost function is the maximum risk of all the estimators. For this case, it is shown that the optimal parameter design is time sharing among at most three different signal values. In the third chapter, the linear minimum mean squared error (LMMSE) estimator is considered. It is observed that time sharing is not needed for the LMMSE estimator, but still the performance can be improved by modifying the signal level. In the final chapter, the optimal channel switching problem is studied for Gaussian channels, and the optimal channel switching strategy is determined in the presence of average power and average cost constraints. It is shown that the optimal channel switching strategy is to switch among at most three channels.