The goal of this paper is to study the learning abilities of adaptive networks in the context of cognitive radio networks and to investigate how well they assist in allocating power and communications resources in the frequency domain. The allocation mechanism is based on a social foraging swarm model that lets every node allocate its resources (power/bits) in the frequency regions where the interference is at a minimum while avoiding collisions with other nodes. We employ adaptive diffusion techniques to estimate the interference profile in a cooperative manner and to guide the motion of the swarm individuals in the resource domain. A mean square performance analysis of the proposed strategy is provided and confirmed by simulation results. Numerical examples show that cooperative spectrum sensing improves the performance of the swarm-based resource allocation technique considerably. © 2011 EURASIP.

Bio-inspired swarming for dynamic radio access based on diffusion adaptation / DI LORENZO, Paolo; Barbarossa, Sergio; A. H., Sayed. - (2011), pp. 402-406. ((Intervento presentato al convegno 19th European Signal Processing Conference, EUSIPCO 2011 tenutosi a Barcelona.

Bio-inspired swarming for dynamic radio access based on diffusion adaptation

DI LORENZO, PAOLO;BARBAROSSA, Sergio;
2011

Abstract

The goal of this paper is to study the learning abilities of adaptive networks in the context of cognitive radio networks and to investigate how well they assist in allocating power and communications resources in the frequency domain. The allocation mechanism is based on a social foraging swarm model that lets every node allocate its resources (power/bits) in the frequency regions where the interference is at a minimum while avoiding collisions with other nodes. We employ adaptive diffusion techniques to estimate the interference profile in a cooperative manner and to guide the motion of the swarm individuals in the resource domain. A mean square performance analysis of the proposed strategy is provided and confirmed by simulation results. Numerical examples show that cooperative spectrum sensing improves the performance of the swarm-based resource allocation technique considerably. © 2011 EURASIP.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11573/402340
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