TY - GEN
T1 - Energy efficiency and SINR maximization beamformers for cognitive radio utilizing sensing information
AU - Alabbasi, AbdulRahman
AU - Rezki, Zouheir
AU - Shihada, Basem
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2014/6
Y1 - 2014/6
N2 - In this paper we consider a cognitive radio multi-input multi-output environment in which we adapt our beamformer to maximize both energy efficiency and signal to interference plus noise ratio (SINR) metrics. Our design considers an underlaying communication using adaptive beamforming schemes combined with the sensing information to achieve an optimal energy efficient system. The proposed schemes maximize the energy efficiency and SINR metrics subject to cognitive radio and quality of service constraints. Since the optimization of energy efficiency problem is not a convex problem, we transform it into a standard semi-definite programming (SDP) form to guarantee a global optimal solution. Analytical solution is provided for one scheme, while the other scheme is left in a standard SDP form. Selected numerical results are used to quantify the impact of the sensing information on the proposed schemes compared to the benchmark ones.
AB - In this paper we consider a cognitive radio multi-input multi-output environment in which we adapt our beamformer to maximize both energy efficiency and signal to interference plus noise ratio (SINR) metrics. Our design considers an underlaying communication using adaptive beamforming schemes combined with the sensing information to achieve an optimal energy efficient system. The proposed schemes maximize the energy efficiency and SINR metrics subject to cognitive radio and quality of service constraints. Since the optimization of energy efficiency problem is not a convex problem, we transform it into a standard semi-definite programming (SDP) form to guarantee a global optimal solution. Analytical solution is provided for one scheme, while the other scheme is left in a standard SDP form. Selected numerical results are used to quantify the impact of the sensing information on the proposed schemes compared to the benchmark ones.
UR - http://hdl.handle.net/10754/362466
UR - http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6875061
UR - http://www.scopus.com/inward/record.url?scp=84906569556&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2014.6875061
DO - 10.1109/ISIT.2014.6875061
M3 - Conference contribution
SN - 9781479951864
SP - 1391
EP - 1395
BT - 2014 IEEE International Symposium on Information Theory
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -
