ACO-Based Algorithm in Cognitive Radio Networks
Author(s):
Siny Daniel , Mount Zion College of Engineering,Kadammanitta
Keywords:
ACO, ACO-ESSP, CR, CSS, PU, throughput maximization
Abstract:
For a dense network of collaborative cognitive radio (CR) sensors with limited energy supply, the maximization of throughput is considered. In this case, the sensors are heterogeneous and are battery powered. To optimally schedule the activities of the sensors and to provide the required sensing performance, an ant colony-based energy-efficient sensor scheduling algorithm (ACO-ESSP) is proposed to increase the overall secondary system throughput. The proposed algorithm is an enhanced version of the conventional ant colony optimization algorithm. It is specifically tailored to the formulated sensor scheduling problem. A more realistic sensor energy consumption model is used here and CR networks employing heterogeneous sensors (CRNHSs) is considered. Simulations demonstrate that this approach improves the system throughput efficiently and effectively compared with other algorithms.
Other Details:
| Manuscript Id | : | IJSTEV2I11061
|
| Published in | : | Volume : 2, Issue : 11
|
| Publication Date | : | 01/06/2016
|
| Page(s) | : | 137-142
|
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