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Proceedings ArticleDOI

To evaluate aggregate interference for underlay cognitive radio network

Anirudh Ranga
- pp 0225-0227
TLDR
The Moment generating function and gamma approximation are in its exact and approximated form, which are calculated for measurement of interference power.
Abstract
In this paper we try to evaluate the aggregate interference on a primary user caused by random number of cognitive radios (secondary users). Some parameters like path loss, Rayleigh fading and shadowing are also studied. The Moment generating function and gamma approximation are in its exact and approximated form, which are calculated for measurement of interference power.

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Citations
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Proceedings ArticleDOI

Aggregate Interference Prediction Based on Back-Propagation Neural Network

TL;DR: This paper gives design guidelines of BP neural network appropriate for aggregate interference prediction via revealing the impact of several key factors on the prediction accuracy, such as the number of input parameters to the neural network, the coordinate system in use, and thenumber of hidden neurons.
References
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Journal ArticleDOI

Cognitive radio: brain-empowered wireless communications

TL;DR: Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks: radio-scene analysis, channel-state estimation and predictive modeling, and the emergent behavior of cognitive radio.
Journal ArticleDOI

COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS - The Throughput Potential of Cognitive Radio: A Theoretical Perspective

TL;DR: The trade-off between regulation and autonomy inherent in the design and performance of cognitive networks is examined through a simple example, which shows that the optimal amount of licensing is equal to the duty cycle of the traffic arrivals.
Journal ArticleDOI

Cognitive Network Interference

TL;DR: This work proposes a new statistical model for aggregate interference of a cognitive network, which accounts for the sensing procedure, secondary spatial reuse protocol, and environment-dependent conditions such as path loss, shadowing, and channel fading, and demonstrates the effectiveness of this model in evaluating the system performance of cognitive networks.
Proceedings ArticleDOI

Interference and Deployment Issues for Cognitive Radio Systems in Shadowing Environments

TL;DR: A model for calculating the aggregate interference encountered by primary receivers in the presence of randomly placed cognitive radios (CRs) shows that if the CRs have apriori knowledge of the radio environment map (REM), then a much larger number of CRs can be deployed especially in a high density environment.
Journal ArticleDOI

Aggregate Interference and Capacity-Outage Analysis in a Cognitive Radio Network

TL;DR: It is shown that the beacon transmitter at the PU receiver imposes less interference and, hence, better capacity-outage probability to the PU than the beacon transmitters located at a PU transmitter.
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