Utility Maximization with Packet Collision Constraint in Cognitive Radio Networks (original) (raw)

Effective Capacity and Delay Optimization in Cognitive Radio Networks

In this paper, we study the fundamental trade-off between delay-constrained primary and secondary users in cognitive radio networks. In particular, we characterize and optimize the trade-off between the secondary user (SU) effective capacity and the primary user (PU) average packet delay. Towards this objective, we employ Markov chain models to quantify the SU effective capacity and average packet delay in the PU queue. Afterwards, we formulate two constrained optimization problems to maximize the SU effective capacity subject to an average PU delay constraint. In the first problem, we use the spectrum sensing energy detection threshold as the optimization variable. In the second problem, we extend the problem and optimize also over the transmission powers of the SU. Interestingly, these complex non-linear problems are proven to be quasi-convex and, hence, can be solved efficiently using standard optimization tools. The numerical results reveal interesting insights about the optimal performance compared to the unconstrained PU delay baseline system.

Resource Allocation in Cognitive Radio Networks: A Comparison Between Game Theory Based and Heuristic Approaches

Wireless Personal Communications, 2009

ABSTRACT Cognitive Radio (CR) approach can be considered as a promising and suitable solution to solve in an efficient and flexible way the increasing and continuous demand of services and radio resources. This paper shows the potential benefits of the adoption of a cognitive radio strategy to the coexistence problem. Two different approaches have been considered: the first one is based on the Game Theory while the second one is formalized as a constrained maximum search and represent the optimum solution. The Game theory approach, suitable for a distributed implementation, provides performances comparable to the heuristic one which is a centralized optimization problem. The paper analyzes the performances of both approaches in terms of secondary rates and spectral efficiency provided by the secondary system.