Project Start Date
Project End Date

The objective of this project is to develop a framework for facilitating green spectrum for cognitive radio protocols in wireless networks. The project aims at identifying the energy hungry components, spectrum activity, user mobility, user access patterns, spectrum sensing intervals, and spectrum interference levels. Also, proposing energy efficient secondary user scheduling in cognition, where user access decision is done based on interference measurements, user locations, and user eligibility. Finally, develop CogWnet, which is a software framework to manage cognitive radio functionality and provide optimal parameters configuration for wireless channel. The Framework is based on cross-layer design to collect sensory information from all layers in TCP/IP stack along with application QoS requirements. CogWnet will act as an implementation framework for our green cognition techniques


KAUST Baseline Funding


  • Green Wireless Cognition: Future Ecient Spectrum Sharing, 2nd Annual KICP Research Symposium, KAUST, KSA, April 2012. [PPT]

Software Packages

  • CogEE v1.0, 2016. Matlab code to evaluate the energy efficiency in cognitive systems

  • CogOut v1.0, 2015. Matlab code to compute the outage in cognitive systems

  • CogWNet v1.0, 2011. USRP2 implementation of an awareness cognitive network resource allocation systems (CogWNet) for facilitating cognition and optimize spectrum utilization Downloaded 220 times Downloaded 143 times Downloaded 156 times

By downloading any of our software packages, you acknowledge that these software packages are provided for the research purposes only and are not permitted for commercialization purposes. Also, you are aware of the fact that additional support is not offered, nor authors liable under any circumstances. If you happen to use any parts of our software packages, you acknowledge to provide a correct referencing providing the software package URL.

Related Publications

I. Qerm and B. Shihada◊, Energy Efficient Power Allocation in Multi-tier 5G Networks Using Enhanced Online Learning, IEEE Transactions on vehicular Technology, Accepted, 2017.
AlQerm, I., & Shihada, B. (2017). Hybrid cognitive engine for radio systems adaptation. 2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC). doi:10.1109/ccnc.2017.7983233
Alabbasi, A., & Shihada, B. (2016). Energy efficient cross layer design for spectrum sharing systems. 2016 IEEE Wireless Communications and Networking Conference. doi:10.1109/wcnc.2016.7565051
AlQerm, I., & Shihada, B. (2016). A cooperative online learning scheme for resource allocation in 5G systems. 2016 IEEE International Conference on Communications (ICC). doi:10.1109/icc.2016.7511617
Alabbasi, A., Rezki, Z., & Shihada, B. (2015). Energy Efficient Resource Allocation for Cognitive Radios: A Generalized Sensing Analysis. IEEE Transactions on Wireless Communications, 14(5), 2455–2469. doi:10.1109/twc.2014.2387161
Alabbasi, A., Rezki, Z., & Shihada, B. (2014). Energy Efficiency and SINR Maximization Beamformers for Spectrum Sharing With Sensing Information. IEEE Transactions on Wireless Communications, 13(9), 5095–5106. doi:10.1109/twc.2014.2323962