TY - JOUR
T1 - Energy Efficient Resource Allocation for Cognitive Radios: A Generalized Sensing Analysis
AU - Alabbasi, AbdulRahman
AU - Rezki, Zouheir
AU - Shihada, Basem
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2014/12/31
Y1 - 2014/12/31
N2 - In this paper, two resource allocation schemes for energy efficient cognitive radio systems are proposed. Our design considers resource allocation approaches that adopt spectrum sharing combined with soft-sensing information, adaptive sensing thresholds, and adaptive power to achieve an energy efficient system. An energy per good-bit metric is considered as an energy efficient objective function. A multi-carrier system, such as, orthogonal frequency division multiplexing, is considered in the framework. The proposed resource allocation schemes, using different approaches, are designated as sub-optimal and optimal. The sub-optimal approach is attained by optimizing over a channel inversion power policy. The optimal approach utilizes the calculus of variation theory to optimize a problem of instantaneous objective function subject to average and instantaneous constraints with respect to functional optimization variables. In addition to the analytical results, selected numerical results are provided to quantify the impact of soft-sensing information and the optimal adaptive sensing threshold on the system performance.
AB - In this paper, two resource allocation schemes for energy efficient cognitive radio systems are proposed. Our design considers resource allocation approaches that adopt spectrum sharing combined with soft-sensing information, adaptive sensing thresholds, and adaptive power to achieve an energy efficient system. An energy per good-bit metric is considered as an energy efficient objective function. A multi-carrier system, such as, orthogonal frequency division multiplexing, is considered in the framework. The proposed resource allocation schemes, using different approaches, are designated as sub-optimal and optimal. The sub-optimal approach is attained by optimizing over a channel inversion power policy. The optimal approach utilizes the calculus of variation theory to optimize a problem of instantaneous objective function subject to average and instantaneous constraints with respect to functional optimization variables. In addition to the analytical results, selected numerical results are provided to quantify the impact of soft-sensing information and the optimal adaptive sensing threshold on the system performance.
UR - http://hdl.handle.net/10754/348514
UR - http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7000583
UR - http://www.scopus.com/inward/record.url?scp=84929306003&partnerID=8YFLogxK
U2 - 10.1109/TWC.2014.2387161
DO - 10.1109/TWC.2014.2387161
M3 - Article
SN - 1536-1276
VL - 14
SP - 2455
EP - 2469
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 5
ER -