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April 19, 2014

Networking Lab explores Energy Efficiency and SINR Maximization Beamformers for Cognitive Radio

Abdulrahman Alabbasi, a PhD student at the Networking LAB led by Prof. Basem Shihada, has published a paper titled “Energy Efficiency and SINR Maximization Beamformers for Cognitive Radio Utilizing Sensing Information” in the International Symposium on Information Theory (ISIT) 2014. ISIT is considered among the top leading conferences in information theory.
 

In this work we consider a cognitive radio multi-input multi-output environment in which we adapt the beamformer weights 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 soft sensing information to achieve an optimal energy efficient system. 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 that the optimal solutions are global. Analytical solution is provided for one scheme, while the other scheme is left in a standard SDP form. We further quantify the impact of the sensing information on the proposed schemes compared to the benchmark ones. The recorded improvement reaches up to 2 bits/Joule/Hz.

Abdulrahman Alabbasi obtained his BSc. from IUG University in Gaza, Palestine, from the electrical engineering department with excellence. He pursued his Master degree from the Electro-Communications university in Tokyo, Japan. Currently, he is pursuing his PhD in the electrical engineering department of KAUST at the Networking LAB. His research focuses on resource allocation, spectrum sharing, and spectrum sensing of wireless communication systems.