Joint Distributed Access Point Selection and Power Allocation in Cognitive Radio Networks
Mingyi Hong, Alfredo Garcia, Jorge Alviar

TL;DR
This paper proposes a joint, distributed approach for access point selection and power allocation in cognitive radio networks, improving spectrum efficiency by considering interdependent spectrum management tasks.
Contribution
It formulates a novel non-cooperative game integrating discrete AP selection and continuous power sharing, with algorithms for distributed NE computation.
Findings
Algorithms efficiently find Nash Equilibria in the joint spectrum management game.
Simulation results demonstrate improved uplink rates and spectrum utilization.
The approach outperforms traditional separate spectrum management methods.
Abstract
Spectrum management has been identified as a crucial step towards enabling the technology of the cognitive radio network (CRN). Most of the current works dealing with spectrum management in the CRN focus on a single task of the problem, e.g., spectrum sensing, spectrum decision, spectrum sharing or spectrum mobility. In this work, we argue that for certain network configurations, jointly performing several tasks of the spectrum management improves the spectrum efficiency. Specifically, we study the uplink resource management problem in a CRN where there exist multiple cognitive users (CUs) and access points (APs), with each AP operates on a set of non-overlapping channels. The CUs, in order to maximize their uplink transmission rates, have to associate to a suitable AP (spectrum decision), and to share the channels belong to this AP with other CUs (spectrum sharing). These tasks are…
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