Abstract-The problem of opportunistic access of parallel channels occupied by primary users is considered. Under a continuoustime Markov chain modeling of the channel occupancy by the primary users, a slotted transmission protocol for secondary users using a periodic sensing strategy with optimal dynamic access is proposed. To maximize channel utilization while limiting interference to primary users, a framework of constrained Markov decision processes is presented, and the optimal access policy is derived via a linear program. Simulations are used for performance evaluation. It is demonstrated that periodic sensing yields negligible loss of throughput when the constraint on interference is tight.Index Terms-Constrained Markov decision processes, dynamic spectrum access, resource allocation.
Abstract-The problem of cognitive access of channels of primary users by a secondary user is considered. The transmissions of primary users are modeled as independent continuous-time Markovian on-off processes. A secondary cognitive user employs a slotted transmission format, and it senses one of the possible channels before transmission. The objective of the cognitive user is to maximize its throughput subject to collision constraints imposed by the primary users. The optimal access strategy is in general a solution of a constrained partially observable Markov decision process, which involves a constrained optimization in an infinite dimensional functional space. It is shown in this paper that, when the collision constraints are tight, the optimal access strategy can be implemented by a simple memoryless access policy with periodic channel sensing. Analytical expressions are given for the thresholds on collision probabilities for which memoryless access performs optimally. Extensions to multiple secondary users are also presented. Numerical and theoretical results are presented to validate and extend the analysis for different practical scenarios.
Abstract-The problem of dynamically accessing a set of parallel channels occupied by primary users is considered. The secondary user is allowed to sense and to transmit in a single channel. By exploiting idle periods between bursty transmissions of primary users, and by using a periodic sensing strategy, optimal dynamic access is achieved by maximizing the throughput of the secondary user while constraining collision probability with the primary user. The optimal dynamic spectrum access problem can then be formulated within the framework of Constrained Markov Decision Processes (CMDPs). The optimal control policy is identified via a linear program, and its performance is analyzed numerically and through Monte Carlo simulations. Finally, we compare the optimal scheme to an ideal benchmark case when simultaneous sensing of all channels is assumed.
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