Ahmet Dundar Sezer

Optimal Channel Switching Strategy for Average Capacity Maximization

In this study, an optimal channel switching strategy is proposed for average capacity maximization in the presence of average and peak power constraints. Necessary and sufficient conditions are derived to determine when the proposed optimal channel switching strategy can or cannot outperform the optimal single channel strategy, which performs no channel switching. Also, it is obtained that the optimal channel switching strategy can be realized by channel switching between, at most, two different channels. In addition, a low-complexity optimization problem is derived to obtain the optimal channel switching strategy. Furthermore, based on some necessary conditions that need to be satisfied by the optimal channel switching solution, an alternative approach is proposed for calculating the optimal channel switching strategy. Numerical examples are provided to exemplify the derived theoretical results and to provide intuitive explanations.

Optimal channel switching for average capacity maximization

Optimal channel switching is proposed for average capacity maximization in the presence of average and peak power constraints. A necessary and sufficient condition is derived in order to determine when the proposed optimal channel switching approach can or cannot outperform the optimal single channel approach, which performs no channel switching. Also, it is stated that the optimal channel switching solution can be realized by channel switching between at most two different channels. In addition, a low-complexity optimization problem is derived in order to obtain the optimal channel switching solution. Numerical examples are provided to exemplify the derived theoretical results.

Optimal Detector Randomization in Cognitive Radio Systems in the Presence of Imperfect Sensing Decisions

In this study, optimal detector randomization is developed for secondary users in a cognitive radio system in the presence of imperfect spectrum sensing decisions. It is shown that the minimum average probability of error can be achieved by employing no more than four maximum a-posteriori probability (MAP) detectors at the secondary receiver. Optimal MAP detectors and generic expressions for their average probability of error are derived in the presence of possible sensing errors. Also, sufficient conditions are presented related to improvements due to optimal detector randomization.

Optimal channel switching in multiuser systems under average capacity constraints

Abstract In this paper, the optimal channel switching problem is studied for average capacity maximization in the presence of multiple receivers in the communication system. First, the optimal channel switching problem is proposed for average capacity maximization of the communication between the transmitter and the secondary receiver while fulfilling the minimum average capacity requirement of the primary receiver and considering the average and peak power constraints. Then, an alternative equivalent optimization problem is provided and it is shown that the solution of this optimization problem satisfies the constraints with equality. Based on the alternative optimization problem, it is obtained that the optimal channel switching strategy employs at most three communication links in the presence of multiple available channels in the system. In addition, the optimal strategies are specified in terms of the number of channels employed by the transmitter to communicate with the primary and secondary receivers. Finally, numerical examples are provided in order to verify the theoretical investigations.

Average Capacity Maximization via Channel Switching in the Presence of Additive White Gaussian Noise Channels and Switching Delays

The optimal channel switching problem is studied for average capacity maximization in the presence of additive white Gaussian noise channels and channel switching delays. First, an optimization problem is formulated for the maximization of the average channel capacity, considering channel switching delays and constraints on average and peak powers. Then, an equivalent optimization problem is obtained to facilitate theoretical investigations. The optimal strategy is derived and the corresponding average capacity is specified when channel switching is performed among a given number of channels. Based on this result, it is shown that channel switching among more than two different channels is not optimal. In addition, the maximum average capacity achieved by the optimal channel switching strategy is formulated as a function of the channel switching delay parameter and the average and peak power limits. Then, scenarios under which the optimal strategy corresponds to the exclusive use of a single channel or to channel switching between two channels are described. Furthermore, sufficient conditions are obtained to determine when the optimal single channel strategy outperforms the optimal channel switching strategy. The numerical results are presented to provide the examples of the theoretical results and to illustrate the effects of channel switching delays.

Optimal Power Allocation for Average Detection Probability Criterion Over Flat Fading Channels

In this paper, the problem of optimal power allocation over flat fading additive white Gaussian noise channels is considered for maximizing the average detection probability of a signal emitted from a power constrained transmitter in the Neyman–Pearson framework. It is assumed that the transmitter can perform power adaptation under peak and average power constraints based on the channel state information fed back by the receiver. Using results from measure theory and convex analysis, it is shown that this optimization problem, which is in general nonconvex, has an equivalent Lagrangian dual that admits no duality gap and can be solved using dual decomposition. Efficient numerical algorithms are proposed to determine the optimal power allocation scheme under peak and average power constraints. Furthermore, the continuity and monotonicity properties of the corresponding optimal power allocation scheme are characterized with respect to the signal-to-noise ratio for any given value of the false alarm probability. Simulation examples are presented to corroborate the theoretical results and illustrate the performance improvements due to the proposed optimal power allocation strategy.

Optimal channel switching for average capacity maximization in the presence of switching delays

In this study, the optimal channel switching problem is investigated for average capacity maximization in the presence of channel switching delays. First, the optimal strategy is obtained and the corresponding average capacity is derived when channel switching is performed among a given number of channels. Then, it is proved that channel switching among more than two different channels is not optimal. Also, the maximum average capacity achieved by the optimal channel switching strategy is expressed as a function of the channel switching delay parameter and the average and peak power limits. Then, scenarios in which the optimal strategy corresponds to the use of a single channel or to channel switching between two channels are described. Numerical examples are presented for showing the effects of channel switching delays.