Resource allocation for spectrum underlay in cognitive radio networks
By Long Bao Le, Ekram Hossain. IEEE Transactions on Wireless Communications, 2008
469 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/6b4871fe0fc0188a2d220d3db2c0495c41ae9202
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Geoffrey Y. Li
- Lu Lu
- Shaoqian Li
- Ertan Onur
- Yuan-Wu Yi
- Ignas G. Niemegeers
- R. Venkatesha Prasad
- Vasilios A. Siris
In Electrical and Electronic Engineering
- Geoffrey Y. Li
- Lu Lu
- Shaoqian Li
- Ertan Onur
- Yuan-Wu Yi
- Ignas G. Niemegeers
- R. Venkatesha Prasad
- Vasilios A. Siris
Citations in the corpus
- Harmonic mean rate fairness for cognitive radio networks with heterogeneous traffic (2013, methodology): “The following conventional fairness criteria have been frequently used for different resource allocation schemes (e.g. [ 9–11]) The max–min fairness criteria provides perfect fairness for all secondary links.”
- Device-to-Device Communications Underlaying Cellular Networks (2013, methodology): “A linear programming deflation algorithm has been introduced to maximize the number of admitted secondary users with QoS requirements in [10] while gradual removal schemes have been proposed to maximize the transmission rate of the secondary link with the max-min criterion in [11].”
- Spectrum Assignment in Cognitive Radio Networks: A Comprehensive Survey (2013, background): “[71], [74], [75]) use the traditional target objectives for max-min fairness and proportional fairness.”
- Fairness in Wireless Networks:Issues, Measures and Challenges (2014, background): “are formulated based on max-min and proportional fairness in [31].”