Cognitive radio operation with opportunistic spectrum access has been proposed to utilize spectrum holes left unused by a primary system owning the spectrum license. The key of cognitive radio operation is the ability to detect weak primary signals and to control the transmission of cognitive users in a way that interference between the two systems is minimized. In this paper we evaluate how a sensor network deployed to provide distributed spectrum sensing can assist cognitive operation. Specifically, we consider sensor networks with regular topology, where a high level of cooperation also means that sensors far from the source of the primary signal are involved in the sensing process. Assuming energy detection and hard-decision combining we derive worst case probabilities of missed detection and false alarm, determine the necessary level of cooperation among the sensors and evaluate how the sensor density and the sensing time affect the performance of distributed sensing. ©2009 IEEE.
Detecting low-power primary signals via distributed sensing to support opportunistic spectrum access / V., Fodor; I., Glaropoulos; Pescosolido, Loreto. - (2009), pp. 1-6. (Intervento presentato al convegno 2009 IEEE International Conference on Communications, ICC 2009 tenutosi a Dresden; Germany nel 14 June 2009 through 18 June 2009) [10.1109/icc.2009.5198909].
Detecting low-power primary signals via distributed sensing to support opportunistic spectrum access
PESCOSOLIDO, Loreto
2009
Abstract
Cognitive radio operation with opportunistic spectrum access has been proposed to utilize spectrum holes left unused by a primary system owning the spectrum license. The key of cognitive radio operation is the ability to detect weak primary signals and to control the transmission of cognitive users in a way that interference between the two systems is minimized. In this paper we evaluate how a sensor network deployed to provide distributed spectrum sensing can assist cognitive operation. Specifically, we consider sensor networks with regular topology, where a high level of cooperation also means that sensors far from the source of the primary signal are involved in the sensing process. Assuming energy detection and hard-decision combining we derive worst case probabilities of missed detection and false alarm, determine the necessary level of cooperation among the sensors and evaluate how the sensor density and the sensing time affect the performance of distributed sensing. ©2009 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
