Faculty of Information & Communication Technology, Universiti Teknikal Malaysia Melaka
10.22075/ijnaa.2020.4577
Abstract
Either natural or man-made a disaster is defined as unexpected destructive event that causes damages and malfunction of existing systems and services all around the disaster area, these destructive effects are unfortunately beyond the capability of local authorities to recover and respond immediately, the disaster recovery plans are immediately initiated so that rescue and aid operations can help those who are trapped in disaster area to survive, those efforts need to be controlled and coordinated with reliable communication systems that are more likely partially or fully disabled due to the disaster, the capabilities of cognitive radio technology enables it to play a significant role in providing efficient communication services for the rescue teams and headquarters as well as trapped victims, in this paper, we survey the cognitive radio architectures that can replace the Software Defined Radio SDR in order to reduce the network expenses in terms of network size and network computational complexity .
AlAqad, K., Burhanuddin, M., Harum, N. (2020). Cognitive Radio Platforms for Disaster Response Networks : Survey. International Journal of Nonlinear Analysis and Applications, 11(Special Issue), 169-182. doi: 10.22075/ijnaa.2020.4577
MLA
Khaled F. AlAqad; M.A. Burhanuddin; Norharyati Binti Harum. "Cognitive Radio Platforms for Disaster Response Networks : Survey". International Journal of Nonlinear Analysis and Applications, 11, Special Issue, 2020, 169-182. doi: 10.22075/ijnaa.2020.4577
HARVARD
AlAqad, K., Burhanuddin, M., Harum, N. (2020). 'Cognitive Radio Platforms for Disaster Response Networks : Survey', International Journal of Nonlinear Analysis and Applications, 11(Special Issue), pp. 169-182. doi: 10.22075/ijnaa.2020.4577
VANCOUVER
AlAqad, K., Burhanuddin, M., Harum, N. Cognitive Radio Platforms for Disaster Response Networks : Survey. International Journal of Nonlinear Analysis and Applications, 2020; 11(Special Issue): 169-182. doi: 10.22075/ijnaa.2020.4577